Grey WF Phase II Final Report Updated 30.06.2013 · 2014-09-26 · Approximately 40% of the cotton...

GreyWaterFootprintIndicatorofWaterPollutionintheProductionofOrganicvs.ConventionalCottonin

India

Authors

Nicolas Franke and Ruth Mathews, Water Footprint Network

Acknowledgments

The project presented in this report was funded by the C&A Foundation.

We would like to thank Erika Zarate and Derk Kuiper for their contribution to Phase 1 of this project

and to Guoping Zhang and Arjen Hoekstra for their review.

We would like to thank the Grey Water Footprint Expert Panel, for their contributions to the grey

water footprint guidelines: Aaldrik Tiktak (Netherlands Environmental Assessment Agency,

Netherlands), Alain Renard (Sustainable Business Development, C&A, Brussels), Bernd Lennartz

(Faculty for Agricultural and Environmental Sciences Rostock University, Germany), Himanshu Joshi

(Indian Institute of Technology at Roorkee (U.P.), India), Julian Dawson (The James Hutton Institute,

Craigiebuckler, Scotland UK), Ranvir Singh (Massey University, New Zealand), Roger Moussa (French

National Institute of Agricultural Research, France), Richard Coupe (U.S. Geological Survey, Pearl,

Mississippi), Mark Huijbregts (Radboud University Nijmegen, Netherlands), Colin Brown (University

of York – UK), Mathias Zessner (Vienna University of Technology, Austria), and Merete Styczen (KU‐

Life, Copenhagen, Denmark).

We would also like to thank Mr. Sumit Garg and Ms. Rosanne Gray from CottonConnect for their

valuable work related to the collection and verification of data from the farms in India.

We are grateful to Mr. Phil Chamberlain and Alain Renard from C&A for their support of the Water

Footprint Network’s mission and for the application of the grey water footprint method at C&A.

The material and conclusions contained in this publication are for information purposes only and the

authors offer no guarantee for the accuracy and completeness of its contents. All liability for the

integrity, confidentiality or timeliness of this publication or for any damages resulting from the use

of information herein is expressly excluded. Under no circumstances shall the partners be liable for

any financial or consequential loss relating to this product. The publication is based on expert

contributions, has been refined in a consultation process and carefully compiled into the present

form. The partners of the initiative consider it a living document that will be adapted to the

circumstances based on new findings and concepts, future experiences and lessons learnt.

Contents

Grey Water Footprint Organic vs. Conventional Cotton

3

Contents

Figures and Tables .............................................................................................................................. 4

Foreword ................................................................................................................................................... 5

Executive Summary ................................................................................................................................... 6

1. Introduction .................................................................................................................................... 8

2. Objective ........................................................................................................................................ 9

3. Method and data ............................................................................................................................ 9

3.1. Grey water footprint .......................................................................................................................... 9

3.1.1. The grey water footprint of a farm ..................................................................................... 10

3.1.2. The grey water footprint per unit of crop ........................................................................... 10

3.2. Grey water footprint expert panel guidelines .................................................................................. 11

3.2.1. Handling of organic pesticides ............................................................................................ 11

3.2.2. Nitrogen and phosphorous leaching from compost ........................................................... 12

3.2.3. Leaching‐runoff fractions of phosphorous and pesticides .................................................. 12

3.2.4. Ambient water quality standards and natural background concentrations ....................... 13

3.3. Recalculation of GWF of Phase I ....................................................................................................... 14

3.3.1. Values used for leaching‐runoff fractions ........................................................................... 14

3.3.2. Values used for maximum allowable concentrations ......................................................... 14

3.3.3. Values used for natural background concentration ............................................................ 15

3.4. Farms sampled ................................................................................................................................. 15

3.5. Analysis of farming practices ............................................................................................................ 17

4. Results .......................................................................................................................................... 18

4.1. Conventional farming systems ......................................................................................................... 18

4.2. Organic farming systems .................................................................................................................. 19

4.3. Comparison between conventional and organic farming systems .................................................. 20

5. Conclusion .................................................................................................................................... 23

References ........................................................................................................................................ 24

Annex I – Expert Panel ............................................................................................................................. 25

Annex II – Quality standards and natural background concentrations used .......................................... 26

Annex III – Conventional and organic fertilizers and pesticides used by farmers for cotton cultivation in India, for the two samples analysed ....................................................................................................... 28

Annex IV – Grey water footprint for the 240 conventional farms ...................................................... ‐ 38 ‐

Annex V – Grey water footprint for the 240 organic farms ................................................................ ‐ 63 ‐

Figures and Tables


4

FiguresandTables

Figures

Figure 1: Location of the Indian districts selected for this study. (Zarate et al., 2011) ............................... 16

Figure 2: Description of the samples used for the evaluation of grey water footprints from conventional

and organic cotton cultivation in India. (Zarate et al., 2011) ...................................................................... 16

Figure 3: Grey water footprint related to the corresponding yield for the conventional farmers. ............ 18

Figure 4: Grey water footprint related to the corresponding yield for the organic farmers. ..................... 19

Figure 5: Comparing grey water footprint related to the corresponding yield between conventional and

organic farmers. .......................................................................................................................................... 21

Tables

Table 1: Minimum and maximum default values to be used for leaching‐runoff fractions. ....................... 13

Table 2: Average default values to be used for leaching‐runoff fractions. ................................................. 13

Table 3: Maximum allowable concentration for phosphorous suggested by the Expert Panel. ................. 15

Table 4: Determining pesticides for the grey water footprint in conventional farming. ............................. 19

Table 5: Overall results of conventional and organic farming. ................................................................... 20

Table 6: Top 10 highest grey water footprint per tonne comparing conventional and organic farms. ...... 21

Table 7: Determining fertilizers for the grey water footprint. ..................................................................... 22

Table 8: Members of the grey water footprint expert panel 2012. ............................................................. 25

Table 9: Quality standards and natural background concentrations used for grey water footprint

calculations. ................................................................................................................................................. 26

Table 10: Summary of fertilizers and its composition for conventional farming. (Zarate et al., 2011) ...... 28

Table 11: Summary of pesticides and its composition for conventional farming. (Zarate et al., 2011) ...... 30

Table 12: Summary of fertilizers and its composition for organic farming. (Zarate et al., 2011) ............... 33

Table 13: Summary of pesticides used for organic farming. (Zarate et al., 2011) ...................................... 35

Foreword


5

Foreword

Sustainability has a long‐standing tradition at C&A, and has been an integral part of corporate

management for over 20 years. The availability and quality of water resources is a key concern for textile

companies as population growth, changing lifestyle patterns and increasing urbanization and

industrialization, coupled with climate change implications, are increasing pressures on limited water

supplies. With a globally distributed supply chain, C&A’s business touches many areas facing long‐term

water shortages or poor water quality due to unsustainable use.

In support of its strategy to improve the sustainability of its cotton clothing supply chain and ultimately

improve the sustainability of the industry as a whole, C&A engaged the Water Footprint Network (WFN)

to conduct a comparison of the grey water footprint, an indicator of water pollution, arising from

conventional versus organic cotton agriculture. Using data collected from farms in India, this study is the

first of its kind to document the grey water footprint reduction opportunities in cotton farming through

changes in farming practices. The results point to how C&A and others could help farmers reduce the

pollution load coming from cotton agriculture and lessen its impact on freshwater resources.

In the context of the world’s water challenges, there is an urgent need for sustainable use of limited

water resources. This publication documents the relationship between farming practices and water

pollution in a way that gives hope that with practicable changes in farming practices, water quality can

be improved, with benefits for all. We share this report in order to facilitate the journey for others who

wish to take strategic action on improving the sustainability, efficiency and equitability of the use and

management of our precious water resources.

The fashion company C&A is one of the leading fashion companies in Europe, with the aim of offering to

its customers fashion at affordable prices for the whole family. Sustainability is not just a recent fashion

phenomenon for C&A, since it has underpinned its business model in evolving ways in its over 170 years

of business. C&A Foundation is committed to improving the lives of the hundreds of thousands of people

who make valuable contributions – as farmers, garment workers, store employees, local communities

and more – to the cotton and apparel value chain. In collaboration with Water Footprint Network, a

global multi‐stakeholder initiative focused on sustainable, fair, and efficient use of freshwater resources

through the use of Water Footprint Assessment, the joint partnership has provided valuable insights on

actionable response strategies for corporate leadership in water management.

We hope you find this document of value.

Leslie Johnston,

Executive Director C&A Foundation

Ruth Mathews,

Executive Director Water Footprint Network

Phil Chamberlain,

C&A Head of Sustainable Business Development

Executive Summary


6

ExecutiveSummary

Chemically intensive agriculture became a widespread human practice in the 20th century. Diffuse

pollution generated by this practice has caused serious impacts on the environment and to human

health. Cotton agriculture has contributed to these problems due to its reliance on pesticides and

fertilizers. In its commitment to reduce these impacts in its cotton clothing supply chain, C&A engaged

the Water Footprint Network to compare pollution levels released to the environment of conventional

versus organic farming practices.

The purpose of this study is to support C&A in working towards a sustainable supply chain by quantifying

and comparing the impacts of organic and conventional cotton farming on freshwater pollution using the

grey water footprint (GWF) as an indicator of water pollution. The global water footprint standard

(Hoekstra et al., 2011) was used to calculate the GWF. The GWF is defined as the volume of freshwater

that is required to assimilate the load of pollutants based on natural background concentrations and

existing ambient water quality standards.

Approximately 40% of the cotton fibre used in C&A’s clothing is cultivated in India. Therefore two farm

samples, one composed of 240 conventional cotton farms and one composed of 240 organic cotton

farms in the states of Gujarat and Madhya Pradesh, where analysed. In 2011, a Phase I study identified

the need to get expert guidance on the parameters used in calculating the GWF. This Phase II study

engaged an expert panel to develop GWF guidelines and these were used to recalculate the Phase 1

results.

An international panel of experts was convened to develop guidance on how certain parameters could

best be handled when calculating the GWF of diffuse pollution from agriculture. The main outcome of

the Expert Panel is a guidance document that addresses the question on how to estimate context‐

dependent leaching‐runoff fractions, how to determine natural concentrations and how to select

ambient water quality standards. Based on the clarification of these key issues, the GWF for the two

samples from Phase I were recalculated, which allowed further analysis of the relationship between

specific farming practices and the GWF.

The GWF results of the production of organic vs. conventional cotton in lndia confirmed that

conventional farming practices generally have a higher GWF than organic farming practices. Although

the total production of 635 metric tonnes in one year for the conventional farms is slightly higher than

the 577 tonnes of organic production, it does not justify the 5.5 times larger total GWF (951.583 m3/year

for the conventional farms and 30.703.437 m3/year for the organic farms). The average GWF for the

production of one tonne of cotton using conventional farming is around 266.042 m3/t, which is about

five times as high as for organic farming, which is around 53.257 m3/t. This difference reflects the high

WF of pesticides used in conventional cotton farming.

When comparing both farming systems, it became clear that the transition towards organic cotton could

be a good measure to achieve a more sustainable supply chain. Organic farming practices showed a

Executive Summary


7

smaller GWF and therefore a lower impact on water resources, while having similar land productivities

as in conventional farming. However, it must be remembered that due to the limitations of research on

the impacts of organic pesticides on freshwater ecosystems and human health, these were not

considered in this analysis. This is an area in need of attention to ensure that no unintended

consequences come from a transition to organic farming practices. Additionally, it must be remembered

that farming practices also influence other environmental issues; the water footprint methodology could

be used for further analysis of different agricultural practices by looking at additional sustainability

factors such as volumes of water consumed (blue water footprint) by different agricultural practices and

their relation to water scarcity.

Introduction


8

1. Introduction

Chemically intensive agriculture became a widespread human practice in the past century, covering in

great extent the need for food and fibre of humankind. Diffuse pollution generated by this practice has

caused serious impacts on the environment, all around the world. In India, various studies report

problems of human health and deterioration of water bodies and ecosystems, due to the widespread use

of agrochemicals. C&A has therefore committed to mitigating these pressures by promoting the

transition towards a more sustainable cotton production.

Approximately 40% of the cotton fibre used in C&A’s clothing is cultivated in India. Therefore, in 2010,

C&A asked the Water Footprint Network (WFN) to compare water pollution generated by organic and

conventional cotton cultivation in India, with the aim to promote more sustainable farming practices. It

was the first time that the grey water footprint (GWF) methodology was applied to quantify and

compare the impacts of organic and conventional cotton farming on freshwater pollution.

C&A and WFN completed this iconic project in 2011. The results obtained showed a significant difference

between the freshwater pollution from conventional and organic cotton cultivation in the two Indian

states considered (Gujarat and Madhya Pradesh). Although the organic practice showed to be not free

from impacts on water resources (it has a contribution related to leaching of Nitrogen and Phosphorus

contained in organic fertilizers), the GWF of conventional farming was significantly larger due to the

pesticides used.

On the other hand the study showed that the average yield in the organic sample was smaller than the

one in the conventional sample, but the increased impacts on water resources were still hard to justify.

There were nevertheless organic farms that, with lower GWFs, achieved a higher yield than others using

conventional farming practices.

Due to the innovative nature of applying the GWF to organic farming practices and insufficient

developments in water quality analysis in India, the values chosen for parameters used in the

calculations of the GWF were based on limited information and certain assumptions had to be made.

In order to provide a more robust comparison between the GWF for conventional and organic farming

practices and to learn more about which agricultural practices could reduce the GWF, a Phase II project

was proposed, with the aim to review the assumptions made in the first study. This second phase also

aims to provide some information to C&A for formulating its sustainability strategy including farm‐

specific response strategies and future agricultural practices which would take into account the

reduction of water resources pollution.

Objective


9

2. Objective

The objective of this study is to support C&A in working towards sustainability in their supply chain, by

quantifying and comparing the impacts of organic and conventional cotton farming on freshwater

pollution.

The GWF methodology was used to analyse two farm samples, each one composed of 240 cotton farms

in India, and taken from the states of Gujarat and Madhya Pradesh. The first sample comprises

conventional farms and the second one organic farms.

This study is based on an earlier project and has the objective of clarifying the assumptions made in the

first study, revising the GWF accounting and further analysing the sustainability of specific farming

practices.

This study gives a more robust comparison between the different farming systems than the earlier GWF

study (Zarate et al., 2011) and will allow C&A to better identify more sustainable cotton farming

practices.

3. Methodanddata

3.1. Greywaterfootprint

The grey water footprint (GWF) was calculated using the methodology described in The Water Footprint

Assessment Manual – Setting the Global Standard (Hoekstra et al., 2011). The GWF is an indicator of

freshwater pollution that can be associated with a certain production process, like cultivating a crop. It is

defined as the volume of freshwater that is required to assimilate the load of pollutants based on natural

background concentrations and existing ambient water quality standards

The loads of pollutants from non‐point sources to receiving water bodies that create the grey water

footprint from agriculture are notoriously difficult to quantify (Zarate, 2010a). Chemical substances

applied on the fields go through different degradation and transport processes through the soil until

finally reaching water bodies. To which extent each of the processes will affect the overall loss of a

substance depends on the physicochemical properties of the substance, the soil characteristics,

climatic conditions, terrain slope and land management practices (Racke et al., Dabrowski et al., 2009).

Loss of pollutants to water bodies can happen through leaching, runoff or return flow (Dabrowski et al.,

2009, Zarate, 2010a).

Because of this complexity, a three‐tier approach (Zarate, 2010a) was proposed to evaluate the grey

water footprint due to diffuse pollution:

Tier 1 ‐ using a single fixed leaching‐runoff fraction to translate data on the amount of chemicals applied

to the field to an estimate of the amount of chemicals reaching the water bodies;

Method and data


10

Tier 2 ‐ applying valid while simplified model approaches to estimate leaching amount of chemicals

under study; and

Tier 3 ‐ applying sophisticated modelling techniques to estimate the amount of leaching chemicals.

This study is based on the tier 1 approach, using fixed leaching – runoff fractions for the estimation of

loads of pollutants reaching water bodies. This method can be used as a quick screening method useful for

understanding impacts of a given agricultural practice on water resources.

3.1.1. Thegreywaterfootprintofafarm

The grey water footprint of a given process, in this case the cotton cultivation in a farm, is calculated by

dividing the pollutant load reaching water bodies (L, in mass per time) by the difference between the

ambient water quality standard for that pollutant (the maximum allowable concentration cmax, in

mass/volume) and its natural background concentration in the receiving water body (cnat, in

mass/volume):

The load of a pollutant entering water bodies is calculated as a fraction from the total application of this

pollutant on the field. This is represented by the dimensionless factor α, which stands for the leaching‐

runoff fraction, defined as the fraction of applied chemicals reaching freshwater bodies. The variable

Appl represents the application of chemicals on or into the soil for a certain farm (in mass/time).

Application rates are normally reported in mass per acre per period of time (AR, mass/area/time);

therefore, in order to calculate the variable Appl for a given farm, the application rate needs to be

multiplied by the area of the farm (A):

Appl = AR x A [mass/time]

Any agrochemical applied to the field is in most of the cases a mixture of substances, not all of them

critical to the environment. The critical substances, those of our interest, are known as “active

ingredients”, and are reported in percentages by the provider on the labels of agrochemical products

(see Annex III).

3.1.2. Thegreywaterfootprintperunitofcrop

The grey component in the water footprint of growing a crop can be computed per tonne of crop product

(WFproc,grey, m3/ton) for each farm, and it is calculated as the grey water footprint of the farm (from

previous section) divided by its crop yield (Y, tonne/acre).

Method and data


11

In Phase I of this study certain assumptions had to be made for calculating the GWF, which could

influence the final result. These assumptions were further researched in this phase and are presented

below.

In order to discuss the assumptions made in Phase I, an international panel of experts (see Annex I) was

convened. The panel advised on how certain parameters could best be handled when calculating the

GWF of diffuse pollution from agriculture. The main outcome of the Expert Panel is a guidance document

that addresses the question on how to estimate context‐dependent leaching‐runoff fractions and how to

get natural concentrations and select ambient water quality standards (Franke et al., 2013). The

document also includes recommendations for default values to be used for the different parameters

when data are lacking.

Key issues that had to be clarified were:

How should organic pesticides be handled in the GWF calculations, in particular related to

leaching‐runoff fractions and ambient water quality standards for active ingredients?

How does the application of compost and other organic fertilizers affect the cycle of nutrients

and leaching‐runoff fractions?

What context‐specific leaching‐runoff fractions should be used or, in their absence, what

assumptions should be taken?

When ambient water quality standards do not exist for a specific substance or when standards

vary greatly between different countries or regions (e.g. EU versus US standards), what

standards can best be used?

Based on the clarification of these key issues, the GWF for the two samples from Phase I were

recalculated, which allowed further analysis of the relationship between specific farming practices and

the GWF.

The following section 3.2 presents the major outcomes of the Expert Panel and the information used for

the recalculation of Phase I.

3.2. Greywaterfootprintexpertpanelguidelines

Based on the discussions and agreements of the GWF Expert Panel, the following decisions were made

regarding the assumptions taken in Phase I.

3.2.1. Handlingoforganicpesticides

In Phase I it was assumed that organic pesticides have no impact on water resources. This assumption

was made, because there was very little information found regarding active ingredients, leaching and

ambient water quality standards for organic pesticides.

The Expert Panel has confirmed that there is very little information regarding active ingredients, leaching

and ambient water quality standards for organic pesticides.

Method and data


12

The lack of information is to one point rooted in that organic pesticide practitioners insist that natural

pesticides do not have to be tested, since they are natural substances, and to another extent because

researchers have not bothered to study the effects of organic pesticides because it is assumed that

"natural" chemicals are automatically safe. Still, there are many natural substances with potential

impacts if occurring in concentrations higher than usual, which could put into question this assumption

and it is not unusual to find warnings on allowed pesticides in organic agriculture, to use them with

caution, because the toxicological effects or their persistence in the soil are unknown.

In order to be effective, natural pesticides often have to be applied with higher frequency than synthetic

ones. Another argument to treat organic pesticides with caution is their prohibition in some countries.

For example, in several countries it is allowed to use sulphur and copper for organic farming, while in

Denmark copper‐compounds are not allowed in any form of agriculture.

As a conclusion, at this point in time the GWF of organic pesticides cannot be assessed due to the lack of

information. Nevertheless organic pesticides should be handled with care. So the assumption that

organic pesticides don’t have any impact on water resources may lead to an underestimation of the

GWF. The impact of organic pesticides on aquatic and terrestrial ecosystems is an area needing further

research.

3.2.2. Nitrogenandphosphorousleachingfromcompost

In Phase I it was assumed that nitrogen and phosphorus leaching from compost is zero when compost is

applied below a certain application rate. This assumption provided a quick and rough way to proceed

during the first phase of the project.

After discussions with the Expert Panel, we conclude that nitrogen and phosphorous in compost should

be handled like any other nitrogen and phosphorous source. The nutrients in compost are bound to

organic material, and therefore, when temperatures are above 5°C, mineralisation processes start which

may lead to leaching. As for other organic nitrogen sources, there is also a risk that nitrate is formed

during a period in which there is no vegetation cover on the land, also leading to a risk of leaching. For

phosphorous it depends on the accumulation in the soil over time compared to the phosphorous‐

sorption capacity of the soil. So depending on the local circumstances there may or may not be a risk of

leaching. The argument for compost is often that the nutrients are not easily available, but they will

become available over time. The use of compost can result in a more friendly fertilization practice if well

managed by the farmer, as with other nutrient sources.

The Expert Panel clarified that nitrogen and phosphorous concentrations in compost should be taken

into consideration in the GWF recalculations in Phase II. Therefore the total nitrogen and phosphorous

contained in the compost was used to calculate the GWF.

3.2.3. Leaching‐runofffractionsofphosphorousandpesticides

The leaching‐runoff fractions of phosphorus and pesticides used in Phase I were 2% and 0.5%

respectively. These leaching‐runoff fractions were based on literature research and concluded as suitable

Method and data


13

for the study. Both values chosen for leaching‐runoff fractions are within the ranges of the suggested

values by the Expert Panel (see Table 1) and therefore were reasonable to use in Phase I.

Table 1: Minimum and maximum default values to be used for leaching‐runoff fractions.

Phosphorous Pesticides

Min and Max

Leaching‐

Runoff‐Fraction

αmin αmax αmin αmax

0.0001 0.05 0.0001 0.1

The ranges are very large. The actual leaching‐runoff fraction will depend on a variety of environmental

factors and management practices as described by the Expert Panel. Since no information on these local

influencing factors is available for the farm sample used in the current study, the Expert Panel suggests

using global average values of 3% for phosphorous and 1% for pesticides (see Table 2).

Table 2: Average default values to be used for leaching‐runoff fractions.

Phosphorous Pesticides

Average

Leaching‐

Runoff‐Fraction

0.03 0.01

The GWF of Phase I was recalculated using these values, which will lead to higher values for both

chemicals of concern.

3.2.4. Ambientwaterqualitystandardsandnaturalbackgroundconcentrations

The Water Footprint Methodology recommends the use ambient water quality standards and only in

their absence, drinking water standards can be used. In many regions there are no ambient water quality

standards available for all chemicals of concern; for these cases, the Expert Panel suggests to apply the

stricter value out of the following guidelines:

EC (2008) – European environmental quality standards in the field of water policy.

USEPA (2010b) ‐ US EPA national recommended water criteria for aquatic life.

CCME (2007) ‐ Canadian water quality guidelines for the protection of aquatic life.

These guideline values were suggested since they are the most comprehensive in terms of numbers of

parameters covered, as well as their wide application. These guidelines have been used as a reference

for many countries to establish country specific standards.

Regarding natural background concentrations, the Expert Panel recommends to use local information

where available. The natural background concentration of a chemical depends on many regional factors

(e.g. geology, physical and chemical conditions, climate) and is therefore quite difficult to estimate. If

natural background levels are not known or difficult to estimate, the Expert Panel recommends using

Method and data


14

one third of the maximum allowable concentrations as the natural background concentration. For

pesticides the natural background concentrations to be used are zero (as in Phase I), since these are not

of natural origin.

3.3. RecalculationofGWFofPhaseI

In Phase I the GWF for two farm samples were analysed, each one composed of 240 farms, cultivating

cotton in the states of Gujarat and Madhya Pradesh in India. The first sample comprises conventional

farms and the other one organic farms. The GWF method at the Tier 1 level (a basic screening level

which calculates the loads of pollutants to water bodies based on a fixed leaching‐runoff fraction) was

used (see Hoekstra et al., 2011, Box 3.7). In Phase II we applied the Tier 1 approach as well, but

reinforced through the input of the Expert Panel to give more robust and reliable results.

3.3.1. Valuesusedforleaching‐runofffractions

The leaching‐runoff fraction values used for the recalculation were the default global average values

suggested by the experts:

10% for nitrogen,

3% for phosphorous, and

1% for pesticides.

In Phase I, a 10% leaching‐runoff fraction for nitrogen was used as well, but it was considered that

organic compost does not affect water bodies when the application rate stays below 50 t/ha. This

assumption was rejected by the Expert Panel. Therefore the load of nitrogen entering a water body was

recalculated, taking compost into account. Both nitrogen and phosphorous were taken into account for

leaching and runoff from application of compost. The leaching‐runoff fraction for phosphorous used in

Phase I was 2% and for pesticides was 0.5%. By using the higher values suggested by the Expert Panel,

the estimated GWFs for these two substances will increase.

3.3.2. Valuesusedformaximumallowableconcentrations

The water quality standards used for pesticides, phosphorous and nitrogen in Phase I were taken from

drinking water regulations, which were 0.1 µg/l for all pesticides (according to EC (1998)), 0.2 mg/l (= 200

µg/l) for phosphorus (according to Chinese Drinking Water Regulations) and 10000 µg/l for nitrogen

(according to Indian Drinking Water Standard).

As recommended by The Water Footprint Assessment Manual and the Expert Panel, the values used for

the recalculation were the ambient water quality standards EC (2008), USEPA (2010b), and CCME (2007).

If no such standards were available, the drinking water quality standards from the EU (1998) were used.

The values used and their sources are listed in Annex II. For the chemicals for which ambient water

quality standards were found, the limits are stricter than the ones used in Phase I, which will lead to a

larger GWF than calculated in Phase I.

The Expert Panel recommends the standards in Table 3 for phosphorous. For this study a maximum

Method and data


15

allowable concentration of 35 µg/l was chosen, since a concentration above this value would lead to

eutrophic conditions (excessive nutrient conditions).

Table 3: Maximum allowable concentration for phosphorous suggested by the Expert Panel.

Substance Group Nutrients

Maximum Allowable Concentration (µg/l)

Referenced Guideline

Phosphorus ultra‐oligotrophic <4 oligotrophic 4‐10 mesotrophic 10‐20 meso‐eutrophic 20‐35 eutrophic 35‐100 hyper‐eutrophic >100

CCME

The maximum allowable concentrations used for the recalculation of nitrogen (as nitrate) is 13 000 µg/l

(according to Canadian Standards which are stricter than USEPA or EU standards), which is a higher

concentration than the drinking water standards used in Phase I, and could result in lower GWFs.

3.3.3. Valuesusedfornaturalbackgroundconcentration

In Phase I, natural background concentrations for all chemicals of concern were assumed to be zero. This

may lead to an underestimation of the GWF, since water bodies that have a natural background

concentration of a certain substance will actually have less assimilation capacity for this substance.

In the recalculation, the natural background concentrations recommended by the Expert Panel were

used (one third of the maximum allowable concentration), since no local information was available.

Therefore the value used for nitrogen was 4333 µg/l and for phosphorous 12 µg/l. For pesticides the

natural background concentration used was zero, as in Phase I.

3.4. Farmssampled

In this study, 480 farms in total, 240 each for conventional and organic agricultural practices,

respectively, were sampled. The samples were taken by Cotton Connect, a non‐for‐profit organization

active in India helping farmers in the improvement of agricultural practices (Zarate et al., 2011). The

samples were taken in the states of Gujarat and Madhya Pradesh (Figures 1 and 2). The two states

together are home to C&A’s majority of cotton supply: 70‐75% for conventional and 80‐85% for organic

cotton. In addition, these two states produce about 40% of India’s total conventional cotton and about

61% of India’s total organic cotton.

Method and data


16

Figure 1: Location of the Indian districts selected for this study. (Zarate et al., 2011)

Figure 2: Description of the samples used for the evaluation of grey water footprints from conventional and organic cotton cultivation in India. (Zarate et al., 2011)

Method and data


17

3.5. Analysisoffarmingpractices

Following The Water Footprint Assessment Manual (reference?), we can formulate two criteria that

determine whether the GWF of growing a crop is sustainable:

1. Geographic context: the GWF of crop cultivation at a certain farm is unsustainable when situated

in a hotspot, i.e. in a catchment area where the total grey water footprint (the aggregate of all

GWFs in the area) exceeds the carrying capacity of the catchment area.

2. Practices at the farm itself: the GWF of crop cultivation at a certain farm is unsustainable in itself

– independent of the geographic context – when the GWF can be reduced or avoided altogether

(at acceptable societal cost).

In this study, we focus on the farming practices and look whether the GWF can be reduced at an

acceptable societal cost. The latter will be judged based on a comparative analysis between farms,

assuming that what can be achieved in terms of a low GWF in combination with a good yield on one farm

can be achieved on other farms as well. The analysis will help to identify best practices, which can be

transferred to other farmers through training and technical assistance.

To calculate the average yield across all farms studied, the yields from the different farms were weighted

based on the farm’s production area. Therefore the weighted average is expectedly higher than the

unweighted, since farms with larger acreage will contribute more to total cotton production. The

average GWF across the farms was weighted based on the total production per farm. The GWF is

expressed in m3/tonne, so farms with larger production (tonnes/yr) will contribute more to the total

GWF in the states considered.

Each farming practice (conventional and organic) was first evaluated individually. In this way, we could

assess within each farming practice whether the water footprint can be reduced without loss in yield. In

a second step, a comparison between the two farming systems was made.

Results


18

4. Results

4.1. Conventionalfarmingsystems

Figure 3 shows the GWF results per tonne for the conventional farms and their corresponding yield per

acre. The outliers of the analysis where left out of the figure for better visualization of the results. A

detailed presentation is given in the table in Annex IV.

The average GWF for the production of one tonne of conventional cotton is 266.042 m3 (see green line in

Figure 3) and the average yield is 0.5 tonne per acre m3 (see yellow line in Figure 3). Block A1 shows

those farms with large GWF and low yield, while block B1 shows the farms with large GWF but high yield.

Block C1 and block D1 show the farms having smaller GWF with low and high yield, respectively. As the

figure shows, farmers can have a good yield without generating very high GWF (block D1). It appears that

farmers with smaller GWF and high yields (in block D1) are the better practitioners while the farmers

with large GWF and low yield (block A1) have large room for improvement.

Figure 3: Grey water footprint related to the corresponding yield for the conventional farmers.

The high GWFs seem to be mainly due to the type of the pesticides applied and their application rate

(see Annex II for maximum allowable concentrations and Annex IV for the application rates). Under the

same agricultural circumstances (management practices, environmental conditions, and farm size) the

application rate seems to be the dominant factor influencing the GWF (see Annex IV). Pesticides which

lead to a high GWF in this study are presented in Table 4.

A1 B1

C1 D1

Results


19

Table 4: Determining pesticides for the grey water footprint in conventional farming.

Pesticides of concern

Endosulphan

Cypermetrine

Difenthiuron

TriAzophos

Cyclohexanam

Fluchloralin

Acephate

Acetamiprid

Dimethyl Sylphoxide

Quinalphos

Carbendazim

Thiomethoxam

Distilled Methyl Soyate

4.2. Organicfarmingsystems

Similar to the analysis for the GWF of the conventional farms, Figure 4 shows the GWF per tonne for the

organic farms and their corresponding yield per acre. Also here the outliers of the analysis where left out

of the figure for better visualization of the results and a detailed presentation is given in the table in

Annex V.

Figure 4: Grey water footprint related to the corresponding yield for the organic farmers.

A2 B2

C2

D2

Results


20

The average GWF for the production of one tonne of organic cotton is around 53.257m3 (see green line

in Figure 4) and the average yield is around 0.45 tonnes per acre (see yellow line in Figure 4). We can see

that organic farming practices can also have large differences in the GWF and yield. Organic farmers can

yield a very good production without generating a high GWF (block D2). Farms within the area of large

GWF and low yield (block A2) have wide room for improving their agricultural performance from a yield

and GWF point of view. Farms within the block D2 (small GWF and high yield) can be considered as best

practitioners in this sampling pool.

In the case of organic farming, the agro‐chemicals analysed in this study were limited to nitrogen and

phosphorous. This means that the GWFs in organic farming are due to the fertilizers used (mainly due to

Compost and Farm Yard Manure, see annex V).

The results of the GWF calculations have shown that the critical pollutant of organic farming is

phosphorous. This is an interesting result, because nitrogen is often seen as the more critical pollutant in

the GWF analysis for diffuse source pollution. Although the concentrations of nitrogen in the used

fertilizers are slightly higher than phosphorous (see annex III), the maximum allowable concentration for

nitrogen as nitrate (13 000 µg/l) is less strict than for phosphorous (35 µg/l) and therefore nitrogen

becomes a less critical element than phosphorous.

4.3. Comparisonbetweenconventionalandorganicfarmingsystems

The samples for both farming systems consisted of 240 farms, with a total surface of 1272 acres of

conventional farming and 1271 acres of organic farming. The overall results of the two farming systems

are shown in Table 5. Table 5: Overall results of conventional and organic farming.

Farming system

Surface area (acre)

Total production (t/year)

Average yield

(t/acre)

Total GWF (m3/year)

Average GWF (m3/t)

Conventional 1.272 635 0,50 168.951.583 266.042

Organic 1.271 577 0,45 30.703.437 53.257

Although the total production of 635 t in one year for the conventional farms is slightly higher than the

577 t of organic production, it does not justify the 5.5 times larger total GWF. While the GWF of

conventional farming systems is around 168.951.583 m3/year, the one for organic farming is 30.703.437

m3/year. The average GWF for the production of one tonne of cotton using conventional farming is

around 266.042 m3/t, which is about five times as high as for organic farming, which is around 53.257

m3/t. The average yields only differ by 10%, with conventional farming being more productive with 0,5

tonnes per acre versus 0,45 tonnes per acre for organic farms.

Figure 5 shows the GWF and the corresponding yield for the conventional and organic farms analysed

which have a GWF below the average conventional GWF. Only three organic farms have larger GWF than

the average conventional GWF of 266.042 m3/t (see annex V). Besides, one can see, in this figure, that

Results


21

all conventional farms lie above the organic average GWF of 53.257 m3/t. Nevertheless, as the figure

shows, there are conventional farms with smaller GWF and higher yields than organic farms.

Figure 5: Comparing grey water footprint related to the corresponding yield between conventional and organic farmers.

The conventional cotton farms in this study have larger GWFs in general. It is mainly due to the use of

pesticides (see Table 6). The GWF per tonne of cotton due to pesticides in conventional farming is

between 10 and 20 times larger than that due to nutrients in organic farming. Pesticide application

resulting in such a large GWF is largely due to their high toxicity. For the top‐10 conventional farms with

the largest GWF, the pesticide Endosulfan, with a maximum allowable concentration in the aquatic

environment of 0.003 µg/l (according to CCME, 2007), and Cypermethrin, with a maximum allowable

concentration in the aquatic environment of 0.002 µg/l (according to the USEPA), are the ones

determining the GWF. For the top‐10 organic farms the nutrient of concern is phosphorous due to

fertilization with compost.

Table 6: Top 10 highest grey water footprint per tonne comparing conventional and organic farms.

Farming System

Organic Conventional

No. of the farm

Organic GWF (m3/t)

Fertilizer of concern

No. of the farm

Conventional GWF (m3/t)

Pesticide of concern

398 733,696

Compost

(Phosphorous) 91 7,554,105 Endosulphan

Results


22

Farming System

Organic Conventional

No. of the farm

Organic GWF (m3/t)

Fertilizer of concern

No. of the farm

Conventional GWF (m3/t)

Pesticide of concern

423 386,817

Compost


330 366,848

Compost


360 249,012

Compost


397 244,467

Compost


414 199,130

Compost


358 178,251

Compost


207 176,087

Compost


155 176,087

Compost

(Phosphorous) 108 2,800,000 Cypermetrine

189 176,087

Compost


Table 7 shows an overview of the fertilizers contributing to the GWF, for both conventional and organic

farming. An overview of the composition of their active ingredients is given in annex III. The application

rate of fertilizers influences the GWF considerably, since the chemicals of concern (nitrogen and

phosphorous) are contained in each type of fertilizers. In poor farming practices excessive application of

fertilizers can occur or in some cases the fertilizers applied may contain higher content of nitrogen or

phosphorous. Both can lead to higher GWFs than others (see annex IV and V). Table 7: Determining fertilizers for the grey water footprint.

Fertilizers of concern

Conventional Organic

Compost Compost

Farm Yard Manure Farm Yard Manure

Diammonium phosphate Caster Cake

Castor

Urea

MIX

Conclusion


23

5. Conclusion

The aim of this study was to support C&A in its commitment to a more sustainable supply chain, by

comparing the grey water footprint from conventionally and organically grown cotton. The Global Water

Footprint Standard was used to calculate the volumes of water contaminated through the production of

conventional and organic grown cotton and then these were analysed in relation to the yields obtained

by each farming practice. Phase I of this study gave a first estimate of the difference in GWF for

conventionally and organically grown cotton, but a more robust analysis in Phase II, based on expert

recommendations and a detailed comparison of individual farm practices, could provide significant

information to C&A for formulating its sustainability strategy.

Both conventional and organic farming practices showed room for improvement when comparing the

GWF and yield of individual farms within each system. The results showed farms with relatively small

GWFs obtaining relatively good yields. First improvements towards a more sustainable supply chain

could be achieved by promoting better farming management practices (e.g. lower application rates of

pesticides and fertilizers).

When comparing both farming systems, it became clear that the transition towards organic cotton could

be a good measure to achieve a more sustainable supply chain. Organic farming practices showed a

smaller GWF and therefore a lower impact on water resources, while having similar land productivities

as in conventional farming.

Conventional farms result in such large GWFs compared to organic farming mainly due to the use of

pesticides. For the pesticides used in conventional farming a more detailed research could be done, to

better understand there leaching and runoff and toxicity. It would be useful to see if they could easily be

substituted by less toxic pesticides or if their application rates could be better managed.

An important reduction of the GWF and therefore a more sustainable supply chain could be achieved by

organizing farmer training, especially for those shown to be the main contributors to the overall water

footprint. Especially for conventional farming the possibility of substituting the critical pesticides by less

harmful ones, could improve its sustainability.

This study showed that organic farming is more sustainable then conventional farming when considering

the volumes of water resources contaminated. However, one should be bear in mind that due to the

limitations of research on the impacts of organic pesticides on freshwater ecosystems and human health,

these were not considered in this analysis. This is an area in need of attention to ensure that no

unintended consequences come from a transition to organic farming practices. Additionally, it should be

noted that farming practices also influence other environmental issues; other indicators such as the

ecological footprint could help to assess the impacts of farming practices on other sustainability factors.

The GWF has here been proven to be a helpful indicator of water resource sustainability from a pollution

point of view. The water footprint methodology could be used for further analysis of different

agricultural practices by looking at additional sustainability factors such as volumes of water consumed

(blue WF) by different agricultural practices and their relation to water scarcity.

References


24

References

Dabrowski. J.M. Murray. K., Ashton. P.J., Leaner. J.J. (2009) Agricultural impacts on water quality and

implications for virtual water trading decisions. Ecological Economics 68: 1074–1082.

Franke, N.A., Boyacioglu, H., Hoekstra, A.Y., (2013) “Grey Water Footprint Assessment: Tier 1 –

Supporting Guidelines”, Water Footprint Network, Enschede, The Netherlands.

Hoekstra, A.Y., Chapagain, A.K., Aldaya, M.M. and Mekonnen, M.M. (2011) “The water footprint

assessment manual: Setting the global standard”, Earthscan, London, United Kingdom.

CCME (Canadian Council of Ministry of the Environment) (2007) “Canadian water quality guidelines for

the protection of aquatic life: A protocol for the derivation of water quality guidelines for the protection

of aquatic life”, Canadian Council of Ministry of Environment, Winnipeg, Canada.

EC (European Comission) (1998) “Council Directive 98/83/EC of 3 November 1998: on the quality of

water intended for human consumption”, Brussels, Belgium.

EC (2008) “Directive 2008/105/EC of the European Parliament and of the Council of 16 December 2008

on environmental quality standards in the field of water policy”, Brussels, Belgium.

Racke et al. (1997) “Pesticide fate in tropical soils”, Pure & Appl. Chem., Vol. 69, No. 6, pp. 1349‐1371,

1997.

USEPA (United States Environmental Protection Agency) (2010b) “US EPA‐National Recommended Water

Criteria‐Aquatic Life Criteria”, Environmental Protection Agency, Washington D.C., USA.

Zarate, E. (ed) (2010a). WFN grey water footprint working group final report: A joint study developed by

WFN partners, Water Footprint Network, Enschede, Netherlands.

Zarate, E., Zeng, Z., Hoekstra, A.Y. (2011) “Grey water footprint as an indicator of levels of water

pollution in the production of organic vs. conventional cotton in India”, Water Footprint Network in

collaboration with C&A and Cotton Connect, Enschede, The Netherlands.

Annex


25

AnnexI–ExpertPanel

Table 8: Members of the grey water footprint expert panel 2012.

Name Organization Email

Prof Brown Colin University of York ‐ UK [email protected]

Dr Coupe Richard U.S. Geological Survey, Pearl, Mississippi [email protected]

Dr Dawson Julian The James Hutton Institute, Craigiebuckler,

Scotland UK [email protected]

Prof Hoekstra Arjen University of Twente, Netherlands [email protected]

Prof Huijbregts Mark Radboud University Nijmegen, Netherlands [email protected]

Dr Joshi Himanshu Indian Institute of Technology at Roorkee

(U.P.), India [email protected]

Dr Bernd Lennartz Faculty for Agricultural and Environmental

Sciences Rostock University, Germany

bernd.lennartz@uni‐

rostock.de

Dr Moussa Roger French National Institute of Agricultural

Research, France [email protected]

Renard Alain Sustainable Business Development, C&A,

Brussels bi20@retail‐sc.com

Dr Singh Ranvir Massey University, New Zealand [email protected]

Prof Styczen Merete KU‐Life, Copenhagen, Denmark [email protected]

Aaldrik Tiktak Netherlands Environmental Assessment

Agency, Netherlands [email protected]

Prof Zessner Matthias Vienna University of Technology, Austria [email protected]

Annex


26

AnnexII–Qualitystandardsandnaturalbackgroundconcentrationsused

Table 9: Quality standards and natural background concentrations used for grey water footprint calculations.

Chemical

Maximum allowable

concentration (µg/l)

Standard Natural

concentration(µg/l)

Acephate 0.1 EC (1998) 0

Acetamiprid 0.1 EC (1998) 0

Aronex 0.1 EC (1998) 0

Carbendazim 0.1 EC (1998) 0

Carbohydrates 0.1 EC (1998) 0

Cyclohexanam 0.1 EC (1998) 0

Cypermethrin 0.002 USEPA (2010) 0

Deltamethrin 0.0004 CCME (2007) 0

Difenthiuron 0.1 EC (1998) 0

Dimethoate 6.2 CCME (2007) 0

DimethylSulphoxide 0.1 EC (1998) 0

Distilled Methyl Soyate 0.1 EC (1998) 0

Emulsifiers 0.1 EC (1998) 0

Endosulfan 0.003 CCME (2007) 0

Epichlorohydrin 0.1 EC (1998) 0

Fenvalerate 0.1 EC (1998) 0

Fine Silica 0.1 EC (1998) 0

Fluchloralin 0.1 EC (1998) 0

Imidachloprid 0.23 CCME (2007) 0

Indoxacarb 0.1 EC (1998) 0

lambda‐cyhalothrin 0.1 EC (1998) 0

Mancozeb 0.1 EC (1998) 0

Monochrotophos 0.1 EC (1998) 0

Nitrate 13000 CCME (2007) 4333

Annex


27

Chemical

Maximum allowable

concentration (µg/l)

Standard Natural

concentration(µg/l)

Nitrobenzene 27000 USEPA (2010) 0

N‐Tricontanol 0.1 EC (1998) 0

Oxy demeton methyl 0.1 EC (1998) 0

Phosphorous 4 CCME (2007) 1.33

Polyethoxyled 0.1 EC (1998) 0

Polyoxy Glycol 0.1 EC (1998) 0

Pride‐‐Related compounds 0.1 EC (1998) 0

Propylene Glycol 500000 CCME (2007) 0

Pyrrolidone 0.1 EC (1998) 0

Quinalphos 0.1 EC (1998) 0

Ranger 0.1 EC (1998) 0

Seaweed 0.1 EC (1998) 0

Silicak 0.1 EC (1998) 0

Sodium dioctyl sulpho succinate 0.1 EC (1998) 0

Solvent(Xylene) 0.1 EC (1998) 0

Spinosad 0.1 EC (1998) 0

Surfactant 0.1 EC (1998) 0

Thiomethoxam 0.1 EC (1998) 0

Triazophos 0.1 EC (1998) 0

Tricontenel 0.1 EC (1998) 0

Xylene 0.1 EC (1998) 0

Annex


28

AnnexIII–ConventionalandorganicfertilizersandpesticidesusedbyfarmersforcottoncultivationinIndia,forthetwosamplesanalysed

Table 10: Summary of fertilizers and its composition for conventional farming. (Zarate et al., 2011)

fertilizers name ingredient name % source

1 Diammonium

phosphate (DAP) Nitrogen 4.14 %

personal communication with CC

Phosphorus 20%

2 Urea Nitrogen 10.81% personal communication with

CC

3 (Single) Super

phosphate Phosphorus 8%


4 Farm Yard

Manure Nitrogen 0.5%

http://www.vanashree.in/fym.htm Phosphorus 0.25 %

Potassium 0.04%

5 Potash Potassium 14.94 % personal communication with

CC

6 Ash Phosphorous 0.44 % http://www.hort.purdue.edu/ext/w

oodash.html Potassium 10%

7 Compost Nitrogen 1% http://www.klickitatcounty.org/SolidWaste/fileshtml/organics/com

postCalc.htm

Phosphorous 0.9% http://www1.agric.gov.ab.ca/$department/deptdocs.nsf/all/eng4466

8 MIX(18:18:18) Nitrogen 4.14%


Phosphorus 7.74 %

Potassium 14.94 %

9 MIX(19:19:19) Nitrogen 4.37 % personal communication with

CC Phosphorus 8.17 %

Annex


29


Potassium 15.77 %

10 MIX(10:26:26) Nitrogen 2.3%


Phosphorus 11.18 %

Potassium 21.58 %

11 MIX(20:20:0) Nitrogen 4.6% personal communication with

CC Phosphorus 8.6%

12 MIX Nitrogen 3.85 %

Phosphorus 7.92 %

Potassium 3.14 %

13 AgroMax Ferrous 2.5%


Molybednum 8%

Zinc 3%

14 BioVita Phosphorous 0.44 % http://www.tradezz.com/buy_2626907_dk-Biovita-Fertilizer.htm

15 Castor Fertilizer Nitrogen 4%

http://www.castoroil.in/reference/glossary/castor_cake.html

Phosphorous 1%

Potassium 1%

16 pond soil

17 Gypsum Calcium

Annex


30

Table 11: Summary of pesticides and its composition for conventional farming. (Zarate et al., 2011)

pesticides name ingredient name % source

1 Acephate Acephate 77.3% personal communication with CC

Sodium dioctyl sulpho succinate 0.5%

2 Admire Imidachloprid 17.8% personal communication with CC

Pyrrolidone 1%

DimethylSulphoxide 38.4%

3 Asataf Acephate 77.3% personal communication with CC


4 Ash Phosphorous 0.4% http://www.hort.purdue.edu/ext/wood

ash.html

Potassium 10%

5 Avont Indoxacarb 14.5% personal communication with CC

Distilled Methyl Soyate 57.5%

Polyethoxyled 6%

6 Basalin Fluchloralin 45% personal communication with CC

7 Bavistin Carbendazim 50% personal communication with CC

Adjuvants 50%

8 Boomflower Nitrobenzene 20%

9 BT Zyme Seaweed 5% personal communication with CC

Carbohydrates 5%

10 Confidor Imidachloprid 17.8% personal communication with CC

Pyrrolidone 1%

Dimethyl Sulphoxide 38.4%

11 Confidor+BT Zyme

Imidachloprid 17.8% personal communication with CC

Pyrrolidone 1%

Dimethyl Sulphoxide 0%

12 Cypermethrin Cypermethrin(e) 25% personal communication with CC

Creslox-1 4.5%

Creslox-2 4.5%

13 Cypermethrine Cypermethrine 25% personal communication with CC

Creslox-1 4.5%

Creslox-2 4.5%

14 Ektara(Aktara) Thiomethoxam(Thiamethoxam) 25% personal communication with CC

Adjuvants 50%

Annex


31


15 Emidor Imidachloprid 17.8% personal communication with CC

Pyrrolidone 1%

DimethylSulphoxide 38.4%

16 Endosulphon Endosulphon 39% personal communication with CC

Epichlorohydrin 2%

Aronex 48%

17 Fenvalrate Fenvalerate 0.5% personal communication with CC

Solvent(Xylene) 2%

Silicak 4%

18 Hildan Endosulphon 39% personal communication with CC

Epichlorohydrin 2%

Aronex 48%

18 Hostathion Trizaophos 40% personal communication with CC

Polyoxy Glycol 7%

Emulsifiers 3%

20 Karate lambda-cyhalothrin 2.5% personal communication with CC

Adjuvants 25.0%

21 Lucin Powder Acephate 77.3% personal communication with CC


22 M 45 Mancozeb 75% personal communication with CC

Surfactant 25%

23 Metasytox Oxydemeton methyl 25% personal communication with CC

Emulsifiers 75%

24 Miracle N-Tricontanol 0.1%

25 Mix(19:19:19) Nitrogen 19% personal communication with CC

Phosphorous 19%

Potash 19%

26 Monocel Monochrotophos 36% personal communication with CC

Cyclohexanam 64%

27 Monochrotophos

Monochrotophos 36% personal communication with CC

Cyclohexanam 64%

28 Nuvacron Monochrotophos 36% personal communication with CC

Cyclohexanam 64%

29 Pegasus Difenthiuron 50% personal communication with CC

Adjuvants 50%

30 Polo Difenthiuron 50% personal communication with CC

Annex


32


Adjuvants 50%

31 Pride Acetamiprid 20% personal communication with CC

Related compounds 80%

32 Quinalphos Quinalphos 25% personal communication with CC

Other ingredients 75%

33 Ranger Picloram 16.8% personal communication with CC

2,4 D Amine Salt 34.6%

34 Rogor Dimethoate 35.5% personal communication with CC

Xylene 30%

Cyclohexanam 15%

35 shakti25 Cypermethrine 25% personal communication with CC

Creslox-1 4.5%

Creslox-2 4.5%

36 Spark Deltamethrin 1% personal communication with CC

Triazophos 35.0%

37 Starking Acephate 77.3% personal communication with CC


Fine Silica 22.2%

38 Starkthene Acephate 77.3% personal communication with CC


Fine Silica 22.2%

39 Sulphur Mancozeb 75% personal communication with CC

Surfactant 25%

40 Tata Mida Monochrotophos 36% personal communication with CC

Cyclohexanam 64%

41 Thiodon Endosulphon 39% personal communication with CC

Epichlorohydrin 2%

Aronex 48%

42 Tracer Spinosad 45% personal communication with CC

Propylene Glycol 45%

43 Trizaophos Trizaophos http://www.wolframalpha.com/entitie

s/chemicals/triazophos/ma/ne/cf/

44 Urea 2% Nitrogen 47%

Annex


33

Table 12: Summary of fertilizers and its composition for organic farming. (Zarate et al., 2011)


1 Ash Phosphorous 1% http://www.hort.purdue.edu/ext/woodash.html

Potassium 10%

2 Bio Fertilizer Nitrogen 15% http://www.google.com/#hl=zh-

CN&rlz=1R2AMSA_enCN424&q=Bio+Fertilizer+Nitrogen&oq=Bio+Fertilizer+Nitrogen&aq=f&aqi=&aql=&gs_sm=e&gs_upl=15866l17114l1l7l7l0l6l0l0l187l187l0.1&bav=on.2,or.r_gc.r_pw.&fp=6c59c6313942c5ad&biw=1259

&bih=595

Phosphorous 5.2%

Potassium 5.3%

3 Buttermilk Calcium

4 Castor Cake Nitrogen 6.4% http://www.castoroil.in/reference/glossary/castor_c

ake.html Phosphorous 0.8%

Potassium 1%

5 Castor DOC Nitrogen 5.5% http://www.agriculturesou

rce.com/p-castor-doc-645181.html

Phosphorous 1.9%

Potassium 1.1%

6 Compost Nitrogen 1%

http://www.klickitatcounty.org/SolidWaste/fileshtml/organics/compostCalc.ht

m

Phosphorous 0.9% http://www1.agric.gov.ab.ca/$department/deptdocs.

nsf/all/eng4466

7 CowUrine+Ash Nitrogen 3%


m

8 Farm Yard Manure Nitrogen 0.5% http://www.vanashree.in/f

ym.htm Phosphorous 0.3%

Potassium 0%

9 Green fodder compost Nitrogen 3.4%


m


nsf/all/eng4466

10 Gypsum Calcium

Annex


34


11 Jivamrit Nitrogen 3%


m

12 Karanj Cake Nitrogen 4% http://www.natureneem.com/index_fichiers/Karanj

a_oil.htm Phosphorous 0.9%

Potassium 1.3%

13 Matka Khad Nitrogen 3%


m

14 Neem cake Nitrogen 5% http://www.ozonebiotech.

com/neemcake.html Phosphorous 1%

Potassium 1.5%

15 Neem Fertilizer Nitrogen 5% http://www.ozonebiotech.

com/neemcake.html Phosphorous 1%

Potassium 1.5%

16 Organic Fertilizer Nitrogen 7%

17 Rock Phosphate Phosphorous 18%

http://www.dummies.com/how-

to/content/fertilizing-your-organic-garden.html

18 Vermi Compost Nitrogen 1%


m


nsf/all/eng4466

Annex


35

Table 13: Summary of pesticides used for organic farming. (Zarate et al., 2011)

Name of pesticide Active ingredient Description Source

1 Akda Ark swallow-wort Bio pesticide. 2 Akhada Ark

3 Amrit Sanjeevani Bio pesticide. http://www.costingagreenfuture.com/blog/?p=86

4 Ash Phosphate and Potash 5 Bajra Ata Millet flour Plant. 6 Bel Ark

7 Besharam Ark Plant. http://projects.icbse.com/biology-339

8 Bio Potash

Water soluble (Foliar / Fertigation / Drip purposes) and Granulated (for soil applications) forms.

http://www.esuppliersindia.com/prathista-industries-ltd-/bio-potash-pr613665-sFP-swf.html

9 Biophos Phosphate, Potassium, Sulphur and Calcium

http://www.gardenews.co.nz/biophos.html

10 Bioxone C9H6Cl2N2O3

Another name is Methazole. It is an herbicide in the family of herbicides known as oxadiazolones.

http://pubchem.ncbi.nlm.nih.gov/summary/summary.cgi?cid=4690

11 Biozyne Growth hormones, Trace elements, Minerals and Vitamins.

Bio pesticide. It is toxin free eco-friendly bio-degradable product

http://www.indiamart.com/iial/chemical-fertilizers.html

12 Biveri Basin 13 Boron Boron

14 Buttermilk Buttermilks the liquid left behind after churning butter out of cream.

http://en.wikipedia.org/wiki/Buttermilk

15 Chili Chili peppers (Capsicum spp.) can be used to make a spray or dust to control pests.

http://www.farmradio.org/english/radio-scripts/34-11script_en.asp

16 Coconut water Plant 17 Cow Urine Bio pesticide

18 Dashaparni Ark Bio pesticide. Liquid pesticide to control different pest attack

http://awakeningjagriti.org/economic_development.asp

19 Dhatura Datura

Datura is a genus of nine species of vespertine flowering plants belonging to the family Solanaceae.

http://en.wikipedia.org/wiki/Datura

Annex


36


20 Garlic Garlic is actually called an Allium, a bulb type plant that smells, don’t harm the environment

http://www.3stepads.com/83524/garlic-organic-pesticide/

21 Green Planet Bio pesticide

22 HNPV(Helicoverpa nucleopolyhedrovirus )

Bio pesticide. The commercial helicoverpa NPV is a highly selective biopesticide that infects only H. armigera and H. punctigera larvae. NPV is harmless to humans, wildlife and beneficial insects.

http://www2.dpi.qld.gov.au/fieldcrops/17696.html

23 Jad Ka Pani

24 Jaggery It is a traditional unrefined non-centrifugal whole cane sugar

http://en.wikipedia.org/wiki/Jaggery

25 Karanj Oil Oil of Pongamia piñata seeds

http://biofertilizersandpesticides.com/neem-oil/neem-oil.html

26 Mahakal 27 Makta 28 Medhafoll 29 Megafoll 30 Neem Ark Plant

31 Neem Oil Oil of Azadirachta indica seeds

Neem oil is a vegetable oil pressed from the fruits and seeds of the neem

http://www.livestrong.com/article/74231-karanja-oil-compared-neem-oil

32 Oat ka pani

33 Panchamrit

BBeleric myrobalan, Black pepper, Asafetida,Ghee, Rock salt, Carum ajowan, Potassium carbonate, Castor oil, Black salt, and Cow urine

Panchamrit is an Ayurvedic medicine prescribed for treating constipation, gas, indigestion and ulcers. It’s also kills the hazardous effects of pesticides and fertilizers.

http://www.gomataseva.org/natural-pure-cow-products/digestive-aid/

34 Pushkar

35 Ratan jyot Some of Jatropha oil are toxic to insects and mollusca , and can be used as a natural crop pesticide.

http://www.lijunoilacnepimple.com/lijun01/jatrophaE.htm

36 Shrub Ark Plant. http://en.wikipedia.org/wiki/Shrub

Annex


37


37 Slurry Nutrients and Water

Slurry is the best food for worms. They will eat slurry and convert it into wormy compost, the best of all manures.

http://tgs.freshpatents.com/Organic-Pesticide-bx1.php http://jyoti-kothari.hubpages.com/hub/How-To-Get-Your-Fruit-Trees-To-Produce-Edible-Fruit---Without-Harsh-Chemicals

38 Tobacco Water Nicotine

Tobacco pesticide is particularly effective on soft creatures, such as slugs and aphids.

http://www.ehow.com/how_2227316_use-organic-pesticide-tobacco.html

39 Trichoderma Spores and conidia of Mycoparasitic fungi

It is a Biofungicide, PHOSPHATE Biofertilizer and also produces plant growth promoting substances.

http://www.alibaba.com/product-free/116878878/TRICHODERMA_Organic_Biofungicide_Biofertilizer.html

40 Tulsi Ark Holy Basil Plant.

41 Vermi Wash

A collection of excretory products and excess secretions of earthworms along with micronutrients from soil organic molecules.

VERMI WASH is the liquid fertilizer collected after the passage of water through a column of worm culture. It is very useful as a foliar spray.

http://www.nationalpesticides.com/Vermi_wash.htm

In grey: no information was found

Annex


38

AnnexIV–Greywaterfootprintforthe240conventionalfarmsThe farms are ordered based on the size of their grey water footprint per tonne of produced cotton (from large to small). Each village is indicated by a

unique color.

ID Farm Village Surface area of

application (Acre)

Y

(t/acre)

Production

per farm (t)

Total ‐ GWF

(m3/farm)

Total ‐ GWF

(m3/acre)

GWF

(m3/t)

Pesticide or fertilizer of

concern

Total application

rate (t/acre)

91 Yogeshbhai

Bhanabhai Sureya Piprali 6 0.20 1.2 9,064,926 1,510,821 7,554,105 Endosulphan 0.0005

507 Laxman Bhuriya Chinkavani 1 0.10 0.1 680,550 680,550 6,805,500 Endosulphan 0.0002

316 Kadwabhai

Manjibhai Nadoliya Surei 3 0.20 0.6 3,334,695 1,111,565 5,557,825 Endosulphan 0.0003

227 Lalit Shivram

Rathod Astriya 4 0.44 1.76 8,166,600 2,041,650 4,640,114 Endosulphan 0.0006

508 Jeetendra Patel Garvakhedi 2 0.15 0.3 1,361,100 680,550 4,537,000 Endosulphan 0.0002

465 Hirabhai Motibhai

Makwana Morthala 2 0.20 0.4 1,814,800 907,400 4,537,000 Endosulphan 0.0003

99 Hemabhai Nagjibhai

Sakhriya Piprali 5 0.30 1.5 6,238,375 1,247,675 4,158,917 Endosulphan 0.0004

460 Karsanbhai

Bharatbhai Digama Morthala 2 0.25 0.5 1,451,840 725,920 2,903,680 Endosulphan 0.0002

Annex


39


application (Acre)

Y

(t/acre)

Production

per farm (t)

Total ‐ GWF

(m3/farm)

Total ‐ GWF

(m3/acre)

GWF

(m3/t)


concern

Total application

rate (t/acre)

108 Narsingh Rama

Muniya Mahudipada 1 0.10 0.1 280,000 280,000 2,800,000 Cypermetrine 0.0001

94 Waghabhai

Merabhai Sakhariya Piprali 4 0.28 1.1 2,722,200 680,550 2,474,727 Endosulphan 0.0002

109 Ramera Madiya

Damar Mahudipada 2 0.40 0.8 1,680,000 840,000 2,100,000 Cypermetrine 0.0002

499 Madhabhai

Kanabhai Makwana Tajpar 3 0.66 1.98 4,083,300 1,361,100 2,062,273 Endosulphan 0.0004

265 Dinesh Rameshwar

Patidar Bandera 5 0.20 1 1,750,000 350,000 1,750,000 Cypermetrine 0.0001

319

Arjibhai

Bansirambhai

Nadoliya

Surei 3 0.33 0.99 1,704,913 568,304 1,722,134Diammonium phosphate /

MIX / Compost 0.4357

469

Chaganbhai

Jadhavbhai

Bhesaliya

Mokasara 2 0.70 1.4 2,268,500 1,134,250 1,620,357 Endosulphan 0.0003

308

Rameshbhai

Jairambhai

Makwana

Tajpar 3 0.66 1.98 3,062,475 1,020,825 1,546,705 Endosulphan 0.0003

Annex


40


application (Acre)

Y

(t/acre)

Production

per farm (t)

Total ‐ GWF

(m3/farm)

Total ‐ GWF

(m3/acre)

GWF

(m3/t)


concern

Total application

rate (t/acre)

436 Vihabhai Ajabhai

Dabhi Tajpar 3 0.66 1.98 2,926,365 975,455 1,477,962 Endosulphan 0.0003

132 Subhash Dalsingh

Muniya Mohankot 2 0.40 0.8 980,000 490,000 1,225,000 Cypermetrine 0.0001

470

Dhirubhai

Chaganbhai

Wachhani

Mokasara 3 1.00 3 3,360,000 1,120,000 1,120,000 Cypermetrine 0.0002

201 Bharat Govind

Lacheta Belam 7 0.44 3.08 3,430,000 490,000 1,113,636 Cypermetrine 0.0001

431 Shukabhai

Manjibhai Parmar Sarsna 2 0.10 0.2 218,609 109,304 1,093,043

Diammonium phosphate /

Compost 0.0838

498 Somabhai Ajabhai

Dabhi Tajpar 2 1.50 3 3,266,640 1,633,320 1,088,880 Endosulphan 0.0005

446 Manjibhai

Khamjibhai Jadhav Than 8 0.61 4.88 5,081,440 635,180 1,041,279 Cyclohexanam 0.0002

307 Dharabhai

Ambabhai Dabhi Tajpar 2 1.00 2 2,041,650 1,020,825 1,020,825 Endosulphan 0.0003

318 Masrubhai

Ramabhai Nadoliya Surei 3 0.40 1.2 1,088,880 362,960 907,400 Endosulphan 0.0001

Annex


41


application (Acre)

Y

(t/acre)

Production

per farm (t)

Total ‐ GWF

(m3/farm)

Total ‐ GWF

(m3/acre)

GWF

(m3/t)


concern

Total application

rate (t/acre)

317

Devabhai

Dhudabhai

Bambhwa

Surei 10 1.60 16 14,518,400 1,451,840 907,400 Endosulphan 0.0004

89 Surabhai Sinabhai

Kokiya Piprali 5 0.32 1.6 1,361,100 272,220 850,688 Endosulphan 0.0001

111

Bakabhai

Chothabhai

Bambhwa

Surei 7 0.61 4.27 3,175,900 453,700 743,770 Endosulphan 0.0001

161 Padam Balaji Sohale Loundi 3 0.40 1.2 850,688 283,563 708,906 Endosulphan 0.0001

49 Shankar Lala Tad Lalarundi 1.5 0.08 0.12 83,184 55,456 693,200 Cyclohexanam 0.0006

377 Ramjibhai

Sureshbhai Kediya Kidiyanagar 5 0.80 4 2,673,913 534,783 668,478


MIX 0.4100

200 Ramesh Hemaji

Parmar Belam 8 0.50 4 2,576,000 322,000 644,000 Cypermetrine 0.0001

147 Walji Galiya Khadiya Chavriya 4 0.28 1.12 672,000 168,000 600,000 Cypermetrine 0.0000

459 Lalabhai Waghabhai

Makwana Morthala 4 0.95 3.8 2,177,760 544,440 573,095 Endosulphan 0.0002

404 Nandkishore

Balkrishna Parihar Mandori 5 1.00 5 2,835,625 567,125 567,125 Endosulphan 0.0002

Annex


42


application (Acre)

Y

(t/acre)

Production

per farm (t)

Total ‐ GWF

(m3/farm)

Total ‐ GWF

(m3/acre)

GWF

(m3/t)


concern

Total application

rate (t/acre)

264 Viharilal Babulal

Patidar Bandera 10 0.10 1 554,348 55,435 554,348


Compost 0.0425

466 Bhagabhai

Sidhabhai Makwana Morthala 1 1.10 1.1 544,440 544,440 494,945 Endosulphan 0.0002

388 Samadbhai

Babubhai Chowhan Palsava‐ 3 0.83 2.49 1,095,691 365,230 440,037 MIX / Castor / Compost 0.2800

158 Ramesh Govind

Meena Loundi 2.5 0.80 2 850,688 340,275 425,344 Endosulphan 0.0001

39 Amra Galiya Ninama Ambapada 6 0.40 2.4 998,208 166,368 415,920 Cyclohexanam 0.0017

256 Ravji Dayabhai

Solanki Sarsna 2 0.35 0.7 286,957 143,478 409,938


Compost 0.1100

339

Karsanbhai

Bhanabhai

Makwana

Umiya 22 0.18 4 1,578,261 71,739 394,565 Diammonium phosphate /

Compost 0.0550

315 Karsanbhai

Samatbhai Mewada Surei 4 0.90 3.6 1,361,100 340,275 378,083 Endosulphan 0.0001

237 Dinesh Shivlal

Patidar Nandra 15 1.00 15 5,670,000 378,000 378,000 Cypermetrine 0.0001

253 Shivlal Babulal

Patidar Somakhedi 5 0.40 2 748,200 149,640 374,100 TriAzophos 0.0003

Annex


43


application (Acre)

Y

(t/acre)

Production

per farm (t)

Total ‐ GWF

(m3/farm)

Total ‐ GWF

(m3/acre)

GWF

(m3/t)


concern

Total application

rate (t/acre)

193 Lokesh Gajaraj Patel Jagatpura 15 0.66 9.9 3,607,875 240,525 364,432 Difenthiuron 0.0002

405 Premchand Kaluram

Parihar Mandori 12 0.86 10.32 3,591,360 299,280 348,000 TriAzophos 0.0002

53 Kalu Thaliya Ninama Lalarundi 1.5 0.16 0.24 83,184 55,456 346,600 Cyclohexanam 0.0006

41 Jeetendra Thawarji

Gomad Ambapada 1 0.12 0.12 41,592 41,592 346,600 Cyclohexanam 0.0004

258 Mahendra Narayan

Patidar Nandra 10 0.80 8 2,672,500 267,250 334,063 Difenthiuron 0.0003

490 Vallabhbhai

Fattebhai Makwana Pipliya(Dhora) 1 1.00 1 294,905 294,905 294,905 Endosulphan 0.0001

455

Narsubhai

Gangaram

Makwana

Than 2.5 0.80 2 544,440 217,776 272,220 Endosulphan 0.0001

208 Santosh Ganpat

Parihar Belam 8 0.75 6 1,596,160 199,520 266,027 TriAzophos 0.0002

235 Narayan Shobharam

Patidar Somakhedi 4 0.43 1.72 445,866 111,467 259,225 Acephate 0.0011

194 Ronit Bharat Patel Jagatpura 8 0.50 4 1,026,240 128,280 256,560 Difenthiuron 0.0002

Annex


44


application (Acre)

Y

(t/acre)

Production

per farm (t)

Total ‐ GWF

(m3/farm)

Total ‐ GWF

(m3/acre)

GWF

(m3/t)


concern

Total application

rate (t/acre)

121 Madiya Noorji

Damar Mahudipada 1 0.10 0.1 24,955 24,955 249,552 Cyclohexanam 0.0000

204 Bhagwan Punaji

Parihar Belam 4 1.30 5.2 1,264,957 316,239 243,261 TriAzophos 0.0008

254 Kamlesh Mohan

Patidar Somakhedi 6 0.50 3 718,272 119,712 239,424 TriAzophos 0.0002

338

Kanjibhai

Mahadevbhai

Makwana

Umiya 3 0.27 0.81 185,283 61,761 228,744 Diammonium phosphate /

Compost 0.0474

497 Devshabhai

Nanjibhai Dabhi Tajpar 6 0.50 3 684,783 114,130 228,261


Compost 0.0875

458

Bhurabhai

Bhikhabhai

Makwana

Morthala 2 0.25 0.5 110,870 55,435 221,739 Diammonium phosphate /

Compost 0.0425

260 Ramlal Phulchand

Patidar Nandra 10 1.00 10 2,138,000 213,800 213,800 Difenthiuron 0.0002

331 Bababhai Jogabhai

Makwana Bhotakiya 6 0.60 3.6 768,522 128,087 213,478 MIX / Castor / Compost 0.0982

210 Vikas Bharat Pawar Belam 5 0.50 2.5 527,819 105,564 211,128 Difenthiuron 0.0002

Annex


45


application (Acre)

Y

(t/acre)

Production

per farm (t)

Total ‐ GWF

(m3/farm)

Total ‐ GWF

(m3/acre)

GWF

(m3/t)


concern

Total application

rate (t/acre)

166 Jagnnath Natthu Pol Bagpal 3 0.33 0.99 207,000 69,000 209,091 Diammonium phosphate /

Compost 0.0529

450 Prabhubhai

Motibhai Makwana Than 4 0.50 2 397,826 99,457 198,913


Compost 0.0763

127 Ukar Surji Singad Jampada 2 0.20 0.4 78,261 39,130 195,652 Diammonium phosphate 0.0300

71 Veerjibhai Ladabhai

Sapra Sarsna 4 0.20 0.8 156,522 39,130 195,652 Diammonium phosphate 0.0300

101 Khimabhai

Pachabhai Rajpur Bhotakiya 8 1.13 9 1,751,501 218,938 194,611 Fluchloralin 0.0000

36 Avla Danna Ninama Lalarundi 1.5 0.20 0.3 58,229 38,819 194,096 Cyclohexanam 0.0004

146 Sakru Sakku Dindor Chavriya 1 0.20 0.2 37,710 37,710 188,550 Cyclohexanam 0.0004

195 Ramesh Bhawariya

Meher Jagatpura 7 0.80 5.6 1,047,620 149,660 187,075 Difenthiuron 0.0002

241 Gyanabhai Ladabhai

Sapra Sarsna 6 0.25 1.5 273,913 45,652 182,609 Diammonium phosphate 0.0350

129 Sambu Rubji

Muniya Mohankot 1 0.20 0.2 36,522 36,522 182,609


Super Phosphate 0.0280

236 Rajendra Thakurlal

Patidar Nandra 5 0.80 4 725,000 145,000 181,250 Carbendazim 0.0003

Annex


46


application (Acre)

Y

(t/acre)

Production

per farm (t)

Total ‐ GWF

(m3/farm)

Total ‐ GWF

(m3/acre)

GWF

(m3/t)


concern

Total application

rate (t/acre)

52 Nanuram Fatta Med Lalarundi 1 0.20 0.2 36,046 36,046 180,232 Cyclohexanam 0.0004

413 Ram Jagdish Patidar Mandori 5 0.90 4.5 801,750 160,350 178,167 Difenthiuron 0.0003

261 Kaluram Sitaram

Patidar Nandra 10 0.75 7.5 1,336,250 133,625 178,167 Difenthiuron 0.0001

506 Rapa Guman Bhigad Got 1 0.28 0.28 49,494 49,494 176,766 Cyclohexanam 0.0005

478 Veljibhai Amarsibhai

Rajpara Mokasara 1.5 2.00 3 525,000 350,000 175,000 Cypermetrine 0.0001

34 Devji Vadda Ninama Lalarundi 1 0.12 0.12 20,661 20,661 172,174


Super Phosphate / Farm Yard

Manure

0.0158

411 Ashok Sriram

Parihar Mandori 2 0.60 1.2 202,174 101,087 168,478


Compost 0.0775

171 Manju Babulal

Kotwal Bagpal 6 0.66 3.96 649,320 108,220 163,970 Acephate 0.0011

59 Mangu Amara

Devda Satrundi 1 0.20 0.2 32,257 32,257 161,283



Manure

0.0247

196 Prakash Shankarlal

Yadav Jagatpura 4 0.88 3.52 563,478 140,870 160,079


Compost 0.1080

Annex


47


application (Acre)

Y

(t/acre)

Production

per farm (t)

Total ‐ GWF

(m3/farm)

Total ‐ GWF

(m3/acre)

GWF

(m3/t)


concern

Total application

rate (t/acre)

126 Sadiya Lula Hatela Mohankot 1 0.28 0.28 44,348 44,348 158,385 Diammonium phosphate /


131 Devisingh Nagla

Muniya Mohankot 6 0.20 1.2 186,332 31,055 155,277 Cyclohexanam 0.0003

223 Ganesh Ambaram

Patidar Astriya 4 0.36 1.44 221,739 55,435 153,986


Compost 0.0425

86 Ramchandra Dina

Bhuriya Chinkavani 1 0.15 0.15 22,182 22,182 147,883 Cyclohexanam 0.0003

144 Kantilal Vaktaji

Muniya Chavriya 2 0.28 0.56 79,857 39,928 142,601 Cyclohexanam 0.0004

359 Hirabhai Ratanbhai

Makwana Umiya 2 0.30 0.6 84,783 42,391 141,304


Compost 0.0325

181 Subhash Mishrilal

Patidar Astriya 6 0.46 2.76 384,840 64,140 139,435 Difenthiuron 0.0001

136 Haresingh Somla

Meda Chinkavani 7 0.60 4.2 582,288 83,184 138,640 Cyclohexanam 0.0004

40 Dilip Shankar

Muniya Ambapada 4 0.20 0.8 110,912 27,728 138,640 Cyclohexanam 0.0003

259 Omprakash

Dhannalal Patidar Nandra 8 1.25 10 1,368,320 171,040 136,832 Difenthiuron 0.0002

Annex


48


application (Acre)

Y

(t/acre)

Production

per farm (t)

Total ‐ GWF

(m3/farm)

Total ‐ GWF

(m3/acre)

GWF

(m3/t)


concern

Total application

rate (t/acre)

122 Rupsingh Nathu

Bhuriya Jampada 2.5 0.20 0.5 66,547 26,619 133,094 Cyclohexanam 0.0002

112 Rupsingh Raichand

Arad Mahudipada 1 0.20 0.2 26,413 26,413 132,065



Manure

0.0203

68 Babariya Gulji

Bhuriya Chinkavani 1 0.20 0.2 26,082 26,082 130,408 Cyclohexanam 0.0001

197 Gangaram Mohan

Parihar Jagatpura 4 1.10 4.4 563,478 140,870 128,063


Compost 0.1080

501 Babanu Guman

Bhigad Got 2 0.32 0.64 79,857 39,928 124,776 Cyclohexanam 0.0003

462 Sanabhai Sukhabhai

Sapra Morthala 6 0.35 2.1 254,348 42,391 121,118


Compost 0.0325

453

Prafulben

Harishbhai

Dodhiwala

Than 7 0.62 4.34 511,761 73,109 117,917 Diammonium phosphate /

Compost 0.0561

361

Ratanbhai

Bhurabhai

Makwana

Umiya 10 0.50 5 570,652 57,065 114,130 Diammonium phosphate /

Compost 0.0438

Annex


49


application (Acre)

Y

(t/acre)

Production

per farm (t)

Total ‐ GWF

(m3/farm)

Total ‐ GWF

(m3/acre)

GWF

(m3/t)


concern

Total application

rate (t/acre)

212 Motilal Sakharam

Patel Astriya 4 0.60 2.4 267,168 66,792 111,320 Distilled Methyl Soyate 0.0002

120 Nathu Hukiya

Damar Mahudipada 2 0.40 0.8 88,730 44,365 110,912 Cyclohexanam 0.0001

263 Rajendra Dhannalal

Patidar Bandera 2 0.35 0.7 77,638 38,819 110,912 Cyclohexanam 0.0004

245 Radhesham

Mangilal Patidar Somakhedi 10 0.65 6.5 717,391 71,739 110,368


Compost 0.0550

503 Amramli Guman

Gharel Got 1 0.32 0.32 34,239 34,239 106,997


Farm Yard Manure 0.0263

266 Bhagwan

Rameshwar Patidar Bandera 4 0.25 1 103,891 25,973 103,891 Acephate 0.0003

502 Adada Bhada Meda Got 1 0.40 0.4 41,072 41,072 102,680 Cyclohexanam 0.0003

420 Ganesh Nemichand

Patidar Bhudri 3 0.56 1.68 167,165 55,722 99,503


Compost 0.0427

392 Jaipalbhai Babubhai

Jogiya Palsava‐ 7 0.50 3.5 346,957 49,565 99,130 Castor / Compost 0.0380

116 Wala Nanaji Parmar Chinkavani 1 0.20 0.2 19,565 19,565 97,826 Diammonium phosphate /


Annex


50


application (Acre)

Y

(t/acre)

Production

per farm (t)

Total ‐ GWF

(m3/farm)

Total ‐ GWF

(m3/acre)

GWF

(m3/t)


concern

Total application

rate (t/acre)

28 Ganesh Nathu

Bhuriya Jampada 2 0.30 0.6 57,674 28,837 96,124 Cyclohexanam 0.0002

65 Sagrambhai

Chondabhai Rathod Mevasa 5 0.30 1.5 143,478 28,696 95,652 Diammonium phosphate 0.0220

505 Somu Bada Madiya Got 2 0.52 1.04 99,128 49,564 95,315 Cyclohexanam 0.0003

252 Gyanchand Babulal

Parihar Somakhedi 5 0.60 3 277,174 55,435 92,391


Compost 0.0425

390 Merubhai Dalabhai

Rathod Palsava‐ 5 0.40 2 182,609 36,522 91,304 Castor / Compost 0.0280

440 Gobarbhai

Popatbhai Bharwad Bhamrasla 3 0.53 1.59 144,075 48,025 90,613 Cyclohexanam 0.0005

110 Ambaram Mansingh

Dindore Mahudipada 2 0.30 0.6 54,110 27,055 90,183 Acephate 0.0003

336 Jiyabhai Bhanabhai

Gami Umiya 5 0.80 4 358,696 71,739 89,674


Compost 0.0550

186 Manohar

Amirchand Patidar Astriya 2 0.40 0.8 71,739 35,870 89,674


Compost 0.0275

217 Rajendra Raghunath

Kag Bagpal 8 0.38 3 267,652 33,457 89,217


Compost 0.0257

Annex


51


application (Acre)

Y

(t/acre)

Production

per farm (t)

Total ‐ GWF

(m3/farm)

Total ‐ GWF

(m3/acre)

GWF

(m3/t)


concern

Total application

rate (t/acre)

80 Bhutakbhai

Ramjibhai Patel Shikharpur 40 0.30 12 1,043,478 26,087 86,957


Compost 0.0313

81 Kishorebhai

Murlibhai Patel Shikharpur 2 0.15 0.3 26,087 13,043 86,957


Compost 0.0325

240 Ganesh Dhannalal

Patidar Bandera 8 1.00 8 684,160 85,520 85,520 Difenthiuron 0.0001

301 Samdalabhai

Dalabhai Bayad Bhimasar 2 1.00 2 169,565 84,783 84,783


Compost 0.0650

347 Ambabhai

Mahadeva Ravriya Padampar 4 0.50 2 169,565 42,391 84,783


Compost 0.0325

504 Makna Badiya Meda Got 2 0.48 0.96 79,857 39,928 83,184 Cyclohexanam 0.0011

452

Nagarbhai

Pitambarbhai

Makwana

Than 2 1.00 2 163,043 81,522 81,522 Diammonium phosphate /

Compost 0.0625

244 Parbatbhai

Vaghsibhai Rajpara Mokasara 4.5 0.66 2.97 239,478 53,217 80,632


Super Phosphate / Compost0.0408

298 Jaimalbhai Dalabhai

Parmar Bhimasar 3 0.90 2.7 215,217 71,739 79,710


Compost 0.0550

Annex


52


application (Acre)

Y

(t/acre)

Production

per farm (t)

Total ‐ GWF

(m3/farm)

Total ‐ GWF

(m3/acre)

GWF

(m3/t)


concern

Total application

rate (t/acre)

8 Sabhlabhai

Bhurabhai Rathod Mevasa 5 0.80 4 313,043 62,609 78,261 Diammonium phosphate 0.0480

143 Ravji Dhanji Khadiya Chavriya 3 0.32 0.96 73,202 24,401 76,252 Cyclohexanam 0.0002

38 Puriya Hira Ninama Ambapada 1 0.28 0.28 21,196 21,196 75,699 Diammonium phosphate /


442 Ramabhai

Popatbhai Bhamrasla 4 1.00 4 300,000 75,000 75,000 Diammonium phosphate 0.0575

57 Ranchod Gangaram

Anjana Satrundi 2 0.48 0.96 71,739 35,870 74,728



198 Mohan Bhawliya

Goad Jagatpura 5 0.80 4 294,783 58,957 73,696


Compost 0.0452

391 Samatbhai

Savvabhai Gagani Palsava‐ 4 0.50 2 146,087 36,522 73,043 Castor / Compost 0.0280

426 Mohanbhai

Jaisinghbhai Parmar Sarsna 1 0.60 0.6 42,391 42,391 70,652


Compost 0.0325

389 Ladabhai Gangabhai

Dhasali Palsava‐ 5 0.40 2 140,870 28,174 70,435 Compost 0.0216

353 Previnbhai

Parbatbhai Patel Padampar 4 0.45 1.8 125,217 31,304 69,565


Compost 0.0240

Annex


53


application (Acre)

Y

(t/acre)

Production

per farm (t)

Total ‐ GWF

(m3/farm)

Total ‐ GWF

(m3/acre)

GWF

(m3/t)


concern

Total application

rate (t/acre)

50 Govardhan Ninama Ambapada 4 0.40 1.6 110,912 27,728 69,320 Cyclohexanam 0.0003

170 Hariom Hiralal

Jaiswal Bagpal 2 0.70 1.4 95,217 47,609 68,012


Super Phosphate / Compost0.0365

96 Gulabben labhubhai

Rangpara Piprali 2 0.60 1.2 79,696 39,848 66,413



393 Ashokbhai Jevabhai

Mali Bhotakiya 2 1.00 2 130,435 65,217 65,217


Compost 0.0770

76 Ratnabhai Devdasji

Patel Shikharpur 10 0.20 2 130,435 13,043 65,217


Compost 0.0213

78 Ranchhod Narsinh

Patel Shikharpur 10 0.20 2 130,435 13,043 65,217


Compost 0.0213

376 Ganeshbhai

Babubhai Kediya Kidiyanagar 2 0.40 0.8 52,174 26,087 65,217 Diammonium phosphate 0.0200

35 Nanuram Parangi Lalarundi 1 0.20 0.2 13,043 13,043 65,217 Diammonium phosphate 0.0100

422 Jagdish Mangal

Pawar Bhudri 6 0.66 3.96 250,435 41,739 63,241 Diammonium phosphate 0.0320

58 Amar Punjaji Devda Satrundi 2 0.40 0.8 50,543 25,272 63,179 Diammonium phosphate /


Annex


54


application (Acre)

Y

(t/acre)

Production

per farm (t)

Total ‐ GWF

(m3/farm)

Total ‐ GWF

(m3/acre)

GWF

(m3/t)


concern

Total application

rate (t/acre)

421 Kamal Bhivra

Patidar Bhudri 2 0.50 1 62,609 31,304 62,609 Diammonium phosphate 0.0240

251 Chhotu Natthu

Pathan Somakhedi 5 0.80 4 247,826 49,565 61,957


Compost 0.0380

159 Rajesh Harinarayan

More Loundi 5 0.60 3 184,796 36,959 61,599



443 Madhurbhai

Popatbhai Dodiya Bhamrasla 8 0.86 6.88 415,565 51,946 60,402 Acephate 0.0005

133 Ramesh Dalsing

Muniya Mohankot 4 0.48 1.92 115,348 28,837 60,077 Cyclohexanam 0.0003

25 Badda Naniya Athila Jampada 2 0.45 0.9 53,238 26,619 59,153 Cyclohexanam 0.0011

7 Pirjibhai Randhaliya Mevasa 5 1.12 5.6 326,087 65,217 58,230 Diammonium phosphate 0.0500

209 Sadashiv Shankar

Parihar Belam 6 1.00 6 333,248 55,541 55,541


Farm Yard Manure / Mix 0.0426

352 Harjiubhai

Gopalbhai Minar Padampar 2 1.00 2 110,870 55,435 55,435


Compost 0.0425

387 Haribhai

Bhuvanbhai Rathod Palsava‐ 5 0.80 4 221,739 44,348 55,435


Compost 0.0340

Annex


55


application (Acre)

Y

(t/acre)

Production

per farm (t)

Total ‐ GWF

(m3/farm)

Total ‐ GWF

(m3/acre)

GWF

(m3/t)


concern

Total application

rate (t/acre)

349 Khetabhai Velabhai

Dubariya Padampar 6 0.83 4.98 270,783 45,130 54,374


Compost 0.0346

62 Kalu Gavji Dindor Satrundi 1 0.32 0.32 17,283 17,283 54,008



Manure

0.0133

299 Jokaerbhai Ajabhai

Parmar Bhimasar 5 0.80 4 215,217 43,043 53,804


Compost 0.0330

239 Ganesh Ramlal

Patidar Bandera 2 0.85 1.7 91,304 45,652 53,708 Diammonium phosphate 0.0350

64 Kanabhai Bijalbhai

Rathod Mevasa 8 0.70 5.6 299,462 37,433 53,475 Cyclohexanam 0.0004

475

Harjibhai

Dharamsibhai

Rajapara

Mokasara 6 0.83 4.98 266,189 44,365 53,452 Cyclohexanam 0.0004

480 Laljibhai Karsanbhai

Makwana Pipliya(Dhora) 4 0.98 3.92 207,782 51,946 53,006 Acephate 0.0005

61 Ramaji Bhuvan

Maida Satrundi 1 0.40 0.4 21,196 21,196 52,989



302 Laxmanbhai

Bhimabhai Bayad Bhimasar 3 1.16 3.48 182,739 60,913 52,511


Compost 0.0467

Annex


56


application (Acre)

Y

(t/acre)

Production

per farm (t)

Total ‐ GWF

(m3/farm)

Total ‐ GWF

(m3/acre)

GWF

(m3/t)


concern

Total application

rate (t/acre)

230 Rameshkumar

Bhalaji More Loundi 3 0.50 1.5 78,261 26,087 52,174 Diammonium phosphate 0.0200

29 Anasingh Nathu

Bhuriya Jampada 1.5 0.30 0.45 23,292 15,528 51,759 Cyclohexanam 0.0002

337 Manjibhai

Bhanabhai Gami Umiya 2 0.60 1.2 61,304 30,652 51,087


Compost 0.0235

488 Veshyarambhai

Amrabhai Parmar Pipliya(Dhora) 3 0.77 2.31 117,391 39,130 50,819 Diammonium phosphate 0.0300

2 Gendala Ganpat

Patel Garvakhedi 3 0.40 1.2 60,457 20,152 50,380



412 Mohan Ganesh

Patidar Mandori 15 0.83 12.45 623,880 41,592 50,111 Cyclohexanam 0.0004

241

Becharbhai

Gobarbhai

Wachhani

Mokasara 0.5 1.20 0.6 30,000 60,000 50,000 Diammonium phosphate /

Compost 0.0460

410 Krishna Santosh

Patel Mandori 2 0.80 1.6 78,261 39,130 48,913 Diammonium phosphate 0.0300

418 Tilokchand

Revaramji Parihar Bhudri 4 0.88 3.52 169,565 42,391 48,172 Acephate 0.0325

Annex


57


application (Acre)

Y

(t/acre)

Production

per farm (t)

Total ‐ GWF

(m3/farm)

Total ‐ GWF

(m3/acre)

GWF

(m3/t)


concern

Total application

rate (t/acre)

130 Lolsingh Dalla

Damer Mohankot 1 0.50 0.5 23,478 23,478 46,957



37 Lulla Gamod Ambapada 4 0.48 1.92 88,730 22,182 46,213 Cyclohexanam 0.0002

297 Ratanbhai

Khimabhai Parmar Bhimasar 3 0.93 2.79 127,174 42,391 45,582


Compost 0.0325

95 Bhushanbhai

Narsibhai Rangpara Piprali 4 0.25 1 44,870 11,217 44,870 MIX 0.0086

113 Besaya Lula Dindor Chinkavani 2 0.40 0.8 35,492 17,746 44,365 Cyclohexanam 0.0004

322

Ramjibhai

Dudhabhai

Makwana

Bhotakiya 5 1.00 5 218,478 43,696 43,696 Diammonium phosphate /

Castor / Compost 0.0335

12

Devayatbhai

Karmalbhai

Khambhla

Mevasa 4 0.75 3 130,435 32,609 43,478 Diammonium phosphate 0.0250

221 Pradip Jagdish Kag Bagpal 1 0.60 0.6 26,087 26,087 43,478 Diammonium phosphate /

Compost 0.0200

509 Malla Badhiya Meda Garvakhedi 2 0.15 0.3 13,043 6,522 43,478 Farm Yard Manure 0.0050

348 Harishbhai

Parbatbhai Minar Padampar 3 0.83 2.49 108,000 36,000 43,373


Compost 0.0276

Annex


58


application (Acre)

Y

(t/acre)

Production

per farm (t)

Total ‐ GWF

(m3/farm)

Total ‐ GWF

(m3/acre)

GWF

(m3/t)


concern

Total application

rate (t/acre)

454 Bhikhabhai

Motibhai Makwana Than 6 1.00 6 257,131 42,855 42,855 Acephate 0.0004

485 Rameshbhai

Amrabhai Galsar Pipliya(Dhora) 5 0.60 3 127,549 25,510 42,516 Cyclohexanam 0.0003

323 Jasabhai Pachabhai

Kodi Bhotakiya 6 1.00 6 254,348 42,391 42,391


Compost 0.0325

231 Vijay Bhagirath

Savle Loundi 3 0.50 1.5 62,609 20,870 41,739 Diammonium phosphate 0.0160

138 Buariya Galiya

Khadiya Chavriya 2 0.32 0.64 26,619 13,309 41,592 Cyclohexanam 0.0001

380 Rambhai Ajabhai

Rathod Kidiyanagar 5 0.60 3 123,913 24,783 41,304


Compost 0.0190

439 Lagrabhai

Revajibhai Talwania Bhamrasla 6 0.53 3.18 129,913 21,652 40,853 Diammonium phosphate 0.0166

381 Dayabhai Rangabhai

Rathod Kidiyanagar 5 0.60 3 117,391 23,478 39,130 Compost 0.0180

441 Vijaybhai Rahabhai

Bharwad Bhamrasla 4 0.90 3.6 138,783 34,696 38,551 Diammonium phosphate 0.0266

167 Gendalal Gangaram

Mansore Bagpal 7 0.80 5.6 213,890 30,556 38,195


Compost 0.0234

Annex


59


application (Acre)

Y

(t/acre)

Production

per farm (t)

Total ‐ GWF

(m3/farm)

Total ‐ GWF

(m3/acre)

GWF

(m3/t)


concern

Total application

rate (t/acre)

213 Mahesh Ambaram

Patidar Astriya 4 0.36 1.44 54,347 13,587 37,741 Cyclohexanam 0.0001

157 Hariram Narayan

More Loundi 5 0.70 3.5 130,435 26,087 37,267 Diammonium phosphate 0.0200

350 Dayabhai Amrabhai

Parmar Padampar 2 0.75 1.5 54,783 27,391 36,522


Compost 0.0210

63 Bhalsurbhai

Savsibhai Rathod Mevasa 7 0.69 4.8 169,565 24,224 35,326 Diammonium phosphate 0.0186

428 Laljibhai Somabhai

Sapra Sarsna 6 0.50 3 105,366 17,561 35,122 Cyclohexanam 0.0002

486 Babubhai Umarbhai

Pathan Pipliya(Dhora) 3 0.93 2.79 90,000 30,000 32,258 Diammonium phosphate 0.0230

379 Ratanbhai Shinbhai

Kediya Kidiyanagar 5 0.80 4 123,913 24,783 30,978


Compost 0.0190

479

Veerjibhai

Mehranbhai

Makwana

Pipliya(Dhora) 2 0.85 1.7 51,946 25,973 30,556 Acephate 0.0003

27 Ambu Badda Damar Jampada 3 0.30 0.9 24,457 8,152 27,174 Farm Yard Manure 0.0063

145 Balu Galiya Khadiya Chavriya 4 0.48 1.92 52,174 13,043 27,174 Diammonium phosphate /


Annex


60


application (Acre)

Y

(t/acre)

Production

per farm (t)

Total ‐ GWF

(m3/farm)

Total ‐ GWF

(m3/acre)

GWF

(m3/t)


concern

Total application

rate (t/acre)

300 Baddev Dalabhai

Parmar Bhimasar 5 0.90 4.5 114,130 22,826 25,362


Compost 0.0175

5 Kalu Nanda Tipoliya Garvakhedi 4 0.40 1.6 38,819 9,705 24,262 Cyclohexanam 0.0002

406 Jitendra Ganesh

Parihar Bhudri 10 0.95 9.5 216,440 21,644 22,783 Acephate 0.0002

69 Bahadursingh

Anjana Satrundi 2 0.60 1.2 26,739 13,370 22,283


Manuare 0.0103

419 Ishwar Surajmal

Nayak Bhudri 8 1.00 8 141,967 17,746 17,746 Cyclohexanam 0.0002

10 Kashiram Patel Garvakhedi 2 0.40 0.8 13,864 6,932 17,330 Cyclohexanam 0.0005

77 Maljibhai Revabhai

Patel Shikharpur 15 0.53 7.95 136,957 9,130 17,227


Compost 0.0145

375 Baldevbhai

Banabhai Kediya Kidiyanagar 5 1.20 6 84,783 16,957 14,130


Compost 0.0130

82 Pravinbhai

Murlibhai Patel Shikharpur 2 1.00 2 26,087 13,043 13,043


Compost 0.1000

438 Javerbhai Ravjibhai

Dodiya Bhamrasla 6 0.83 4.98 39,928 6,655 8,018 Cyclohexanam 0.0001

Annex


61


application (Acre)

Y

(t/acre)

Production

per farm (t)

Total ‐ GWF

(m3/farm)

Total ‐ GWF

(m3/acre)

GWF

(m3/t)


concern

Total application

rate (t/acre)

280 Parbatbhai

Govardhan Patel Juna Katariya 35 0.06 1.995 12,069 345 6,050 Compost 0.0270

304 Ranjitsinh

Gumansinh jadeja Wandhiya 40 0.01 0.4 2,299 57 5,747 Compost 0.0045

278 Samatbhai Ranchod

Koli Juna Katariya 5 0.16 0.8 2,299 460 2,874 Compost 0.0360

277 Parbat Jetha Patel Juna Katariya 9 0.13 1.17 2,586 287 2,210 Compost 0.0225

92 Balabhai Murjibhai

Devda Wandhiya 9 0.08 0.72 1,149 128 1,596 Compost 0.0100

289 Dharamji Khimji

Patel Narayansari 23 0.10 2.3 3,516 153 1,529 Compost 0.0120

394 Munjibhai

Narayanbhai Patel Wandhiya 8 0.23 1.8 2,586 323 1,437 Compost 0.0253

510 Kishan Devji Patel Juna Katariya 5 0.10 0.5 575 115 1,149 Compost 0.0090

291 Veerjibhai

Kesarbhai Patel Wandhiya 4 0.40 1.6 1,724 431 1,078 Compost 0.0338

365 Kanjibhai Gangjibhai

Patel Narayansari 72 0.12 8.64 8,276 115 958 Compost 0.0090

Annex


62


application (Acre)

Y

(t/acre)

Production

per farm (t)

Total ‐ GWF

(m3/farm)

Total ‐ GWF

(m3/acre)

GWF

(m3/t)


concern

Total application

rate (t/acre)

290 Jairambhai

Pannabhai Patel Narayansari 18 0.11 1.98 1,723 96 870 Compost 0.0075

400 Gokul Mohanbhai


276 Jeevan Devji Patel Juna Katariya 10 0.12 1.2 893 89 744 Compost 0.0070

292 Dharamji

Becharbhai Patel Wandhiya 5 0.40 2 1,437 287 718 Compost 0.0225

274 Ratabhai Ramji


395 Kanjibhai Haribhai

Patel Wandhiya 10 0.40 4 2,586 259 647 Compost 0.0203

399 Ranchodbhai

Mohanbhai Patel Narayansari 9 0.18 1.62 1,034 115 639 Compost 0.0090

150 Lokendra Jani Garvakhedi 7 0.20 1.4 435 62 311 Urea 0.005

386 Kanhabhai

Vithabhai Mali Bhotakiya 3 1.00 3 690 230 230 Compost 0.0180

367 Ramji Velabhai Patel Juna Katariya 10 0.32 3.2 690 69 216 Compost 0.0054

Annex


63

AnnexV–Greywaterfootprintforthe240organicfarmsThe farms are ordered based on the size of their grey water footprint per tonne of produced cotton (from large to small). Each village is indicated by a

unique color.

ID Farm Village Surface area of application

(Acre)

Y (t/acre)

Production per farm (t)

Total ‐ GWF (m3/farm)

Total ‐ GWF (m3/acre)

GWF (m3/t)

Fertilizer of concern Total

application rate (t/acre)

398 Murjibhai Mebhaya

Patel Shikharpur 15 0.12 1.8 1,320,652 88,043 733,696

Compost (phosphorous)7.500

423 Nandkishore Kaluji

Patidar Bhudri 4 0.25 1 386,817 96,704 386,817


330 Pannabhai Hirjibhai

Patel Narayansari 15 0.06 0.9 330,163 22,011 366,848


360 Gajabhai Sugabhai

Rajpur Bhotakiya 3 0.33 0.99 246,522 82,174 249,012


397 Manjbhai Deva Patel Shikharpur 12 0.08 0.96 234,689 19,557 244,467Compost (phosphorous)

1.666

414 Vijusingh Narsingh

Nayak Bhudri 2 0.3 0.6 119,478 59,739 199,130


358 Samatbhai

Shavabhai Makwana Umiya 4 0.35 1.4 249,552 62,388 178,251


207 Manohar Khushalji

Solanki Belam 6 0.5 3 528,261 88,043 176,087


155 Jeetendra Shankar

Chowhan Loundi 2.5 1 2.5 440,217 176,087 176,087


189 Natthu Rajaram

Yadav Jagatpura 5 0.5 2.5 440,217 88,043 176,087


468 Sunderbhai

Mohanbhai Digama Morthala 3 0.23 0.69 105,652 35,217 153,119


437 Mohanbhai

Khimabhai Jolapara Bhamrasla 4 0.75 3 443,478 110,870 147,826


Annex


64


(Acre)

Y (t/acre)




GWF (m3/t)



151 Laxman Gotuji More Loundi 2 0.6 1.2 176,087 88,043 146,739Compost (phosphorous)

7.500

232 Rajendra Mangilal

Chowhan Loundi 2 0.4 0.8 117,391 58,696 146,739


320 Vipul Jevabhai Mali Bhotakiya 3 0.16 0.48 70,435 23,478 146,739Compost (phosphorous)

2.000

211 Harilal Kaluji Jaiswal Bagpal 5 0.7 3.5 498,913 99,783 142,547Compost (phosphorous)

8.500

427 Kushabhai

Becharbhai Solanki Sarsna 6 0.42 2.52 352,174 58,696 139,752


396 Ranchodbhai

Narsobhai Patel Shikharpur 9 0.22 1.98 264,130 29,348 133,399


214 Babulal Govind

Kotwal Bagpal 5 0.6 3 381,522 76,304 127,174


224 Gajanan Shobharav

Patidar Astriya 10 0.7 7 880,435 88,043 125,776


225 Usha Gananan

Patidar Astriya 5 0.7 3.5 440,217 88,043 125,776


425 Uttam Subhash

Patidar Bhudri 2 0.75 1.5 180,261 90,130 120,174


401 Rajnath Sitaram

Patidar Mandori 9 0.5 4.5 540,587 60,065 120,130


408 Dharmesh Sevakram

Patidar Mandori 6 0.5 3 356,478 59,413 118,826


364 Becharbhai

Akhaibhai Patel Narayansari 8 0.15 1.2 140,870 17,609 117,391


417 Shyam Mahadev

Patidar Bhudri 4.5 0.56 2.52 291,952 64,878 115,854


272 Ritesh Phulchand

Patidar Somakhedi 6.5 0.32 2.08 238,960 36,763 114,885


Annex


65


(Acre)

Y (t/acre)




GWF (m3/t)



362 Jivtiben Panchabhai

Makwana Bhotakiya 4 0.75 3 331,304 82,826 110,435


175 Mahadev Shobharao

Patidar Astriya 6 0.83 4.98 534,130 89,022 107,255


295 Veljibhai Bhurabhai



269 Dharmendra

Omprakash Dhariya Nandra 7 0.5 3.5 362,843 51,835 103,670


424 Subhash Gajanan

Patidar Bhudri 6 0.87 5.22 540,783 90,130 103,598


271 Prakash Jagnnath

Patidar Somakhedi 3 0.66 1.98 201,209 67,070 101,621


190 Dinesh Laxman

Pawar Jagatpura 4 0.87 3.48 353,478 88,370 101,574


402 Mohan Ganesh

Patidar Mandori 5 0.6 3 302,935 60,587 100,978


234 Anil Prakash Patidar Somakhedi 5 0.4 2 201,209 40,242 100,604Compost (phosphorous)

3.004

415 Mahadev Bhagwan

Parihar Bhudri 8 0.69 5.52 552,313 69,039 100,057


342 Hasmukhbhai

Shavabhai Makwana Umiya 3.5 0.43 1.505 147,887 42,253 98,263


221 Girdhari Shobharam

Patidar Astriya 15 0.6 9 880,435 58,696 97,826


296 Mansubhai Dudhabhai Makwana

Bhimasar 2 0.75 1.5 146,739 73,370 97,826 Compost (phosphorous)

6.250

373 Samatbhai Bagabhai

Rathod Kidiyanagar 8 0.5 4 375,652 46,957 93,913


Annex


66


(Acre)

Y (t/acre)




GWF (m3/t)



384 Lilaben Kumbhabhai

Rathod Kidiyanagar 9.5 0.5 4.75 446,087 46,957 93,913


341 Devabhai Khedabhai

Makwana Umiya 4 0.5 2 181,957 45,489 90,978


489 Surabhai Vastabhai

Makwana Pipliya(Dhora) 1 0.5 0.5 45,000 45,000 90,000


187 Bankatlal Mangilal

Sen Jagatpura 3 0.66 1.98 177,077 59,026 89,433


180 Urmila Mahadev

Patidar Astriya 5 1 5 442,663 88,533 88,533


303 Pemabhai Pavanbhai

Makwana Bhimasar 2 1 2 176,087 88,043 88,043


416 Ramjibhai Hirabhai

Parmar Sarsna 4 0.45 1.8 156,829 39,207 87,127


473 Shivabhai

Dharmasibhai Rajpura

Mokasara 3 0.2 0.6 52,216 17,405 87,026 Farm Yard Manure

0.013

409 Krishnakant

Ramsevak Patidar Mandori 5 0.7 3.5 296,087 59,217 84,596


370 Jeevanbhai Savjibhai

Patel Narayansari 7 0.14 0.98 82,174 11,739 83,851


105 Karmasibhai

Ravsibhai Rathod Mevasa 2 0.9 1.8 146,739 73,370 81,522


451 Becharbhai Kogabhai

Khatala Mevasa 4 0.55 2.2 177,235 44,309 80,561


222 Mohan Bhimaji

Humber Bagpal 3 0.37 1.11 88,043 29,348 79,318


229 Govind Balram More Loundi 4 0.75 3 237,391 59,348 79,130 Compost (phosphorous)

5.002

Annex


67


(Acre)

Y (t/acre)




GWF (m3/t)



484 Amarsibhai Janabhai

Makwana Pipliya(Dhora) 1 1 1 79,096 79,096 79,096


482 Vinubhai Somabhai



79 Pawan Murlibhai



363 Katiben Ramji Makwana

Bhotakiya 1.5 0.53 0.795 59,668 39,779 75,054 Compost (phosphorous)

3.334

293 Behtarbhai

Ranchodbhai Patel Wandhiya 20 0.2 4 293,478 14,674 73,370


188 Ratanlal Govind

Pawar Jagatpura 6 0.66 3.96 290,191 48,365 73,281


346 Raghubhai

Anantabhai Patel Padampar 3 0.83 2.49 176,087 58,696 70,718


51 Ukar Baluji Dayima Lalarundi 1 0.24 0.24 16,304 16,304 67,935 Farm Yard Manure

0.013

97 Venubhai

Bacchubhai Rathod Piprali 2 0.25 0.5 33,587 16,793 67,174


461 Jeevanbhai

Chaganbhai Shaikh Morthala 2 0.6 1.2 78,261 39,130 65,217


432 Sukhrambhai

Bhuvanbhai Jolapara Bhamrasla 1 0.9 0.9 58,696 58,696 65,217


255 Prabhu Savsibhai

Dholkiya Sarsna 1.5 0.47 0.705 44,022 29,348 62,442


192 Rakesh Gendalal

Yadav Jagatpura 7 0.57 3.99 246,522 35,217 61,785


327 Ranabhai Jogabhai

Parmar Palsava‐ 5 0.8 4 246,522 49,304 61,630


Annex


68


(Acre)

Y (t/acre)




GWF (m3/t)



434 Jagabhai Bhuvanbhai

Jolapara Bhamrasla 5 0.6 3 184,891 36,978 61,630


456 Bhagwanbhai

Motibhai Makwana Than 3.5 0.57 1.995 122,279 34,937 61,293


436 Dhudabhai

Mohanbhai Jolapara Bhamrasla 4 0.725 2.9 176,087 44,022 60,720


335 Bacchubhai

Dharamsibhai Patel Umiya 1 0.6 0.6 36,365 36,365 60,609


203 Prakash Babulal

Parihar Belam 6 0.42 2.52 148,146 24,691 58,788


152 Gajaraj Parasram

More Loundi 4 0.5 2 117,391 29,348 58,696


284 Morji Savji Patel Wandhiya 20 0.2 4 234,783 11,739 58,696 Compost (phosphorous)

1.000

311 Rajabhai Kanabhai

Kansagara Surei 2 0.5 1 57,065 28,533 57,065


191 Mukesh Gendalal

Yadav Jagatpura 7 0.64 4.48 246,522 35,217 55,027


11 Varsing Velji Singad Satrundi 1 0.3 0.3 16,304 16,304 54,348 Farm Yard Manure

0.013

247 Rajesh Sitaram

Patidar Bandera 4 0.4 1.6 85,774 21,443 53,609


403 Ramchandra

balaram Patidar Mandori 8 0.62 4.96 263,687 32,961 53,163


333 Ambavibhai

Raghubhai Minar Padampar 2 1 2 105,652 52,826 52,826


357 Shavabhai Bhurabhai

Makwana Umiya 3 0.4 1.2 63,365 21,122 52,805


407 Ajay Ramchandra

Patidar Mandori 5 0.6 3 151,826 30,365 50,609


Annex


69


(Acre)

Y (t/acre)




GWF (m3/t)



275 Revaji Bhagwan

Patidar Nandra 7 0.57 3.99 199,509 28,501 50,002


262 Vishnu Sitaram

Patidar Bandera 4 0.43 1.72 85,774 21,443 49,869


219 Shantilal Jituji Patel Bagpal 2 0.9 1.8 89,270 44,635 49,594 Compost (phosphorous)

3.750

202 Shivcharan Kaluji

Parihar Belam 6 0.5 3 148,146 24,691 49,382


433 Govardhanbhai Morebhai Jediya

Bhamrasla 5 0.6 3 146,739 29,348 48,913 Compost (phosphorous)

2.500

435 Bagabhai

Bhuvanbhai Jolapara Bhamrasla 2 0.9 1.8 88,043 44,022 48,913


142 Nandu Gangaram

Singad Mahudipada 1 0.2 0.2 9,783 9,783 48,913


467 Laxmanbhai

Devabhai Savriya Morthala 2 0.8 1.6 78,261 39,130 48,913


356 Khetabhai Dalabhai

Parmar Bhimasar 3 1 3 146,152 48,717 48,717


344 Kanjibhai Karsanbhai

Patel Padampar 5 1 5 241,606 48,321 48,321


324 Arjibhai Nanjibhai

Mali Bhotakiya 5 1.1 5.5 264,130 52,826 48,024


334 Jesabhai Karsanbhai

Patel Padampar 4 0.75 3 140,870 35,217 46,957


474 Bhupalbhai

Chowksibhai Rajpura Mokasara 1 0.7 0.7 32,283 32,283 46,118


313 Chothabhai

Danabhai Bambhwa Surei 3 0.71 2.13 97,826 32,609 45,928


125 Dulesingh Mangu

Sarel Mohankot 2 0.4 0.8 36,522 18,261 45,652


Annex


70


(Acre)

Y (t/acre)




GWF (m3/t)



250 Piyush Gyanchand

Patidar Somakhedi 3 0.53 1.59 72,582 24,194 45,649


233 Harikrishna Babulal

Patidar Somakhedi 8 0.5 4 176,087 22,011 44,022


325 Dayabhai Ranabhai

Parmar Palsava‐ 5 0.8 4 176,087 35,217 44,022


294 Purabhai Premjibhai

Patel Wandhiya 10 0.2 2 88,043 8,804 44,022


248 Dharmendra

Harikrishna Patidar Somakhedi 3.5 0.85 2.975 129,460 36,989 43,516


447 Mehrubhai Prabhubhai Khandaliya

Than 2 0.3 0.6 26,087 13,043 43,478 Farm Yard Manure

0.010

383 Banabhai

Kumbhabhai Rathod Kidiyanagar 5.3 0.55 2.915 124,435 23,478 42,688


345 Ambavibhai

Mahadev Patel Padampar 3 0.83 2.49 105,652 35,217 42,431


257 Jitendra Ramlal

Patidar Nandra 5 0.7 3.5 148,043 29,609 42,298


329 Medhabhai Mandanbhai Chawda

Palsava‐ 4 1 4 169,043 42,261 42,261 Compost (phosphorous)

3.600

457 Shaikh Mansukhbhai

Malabhai Piprali 2 0.6 1.2 50,557 25,278 42,130


93 Argujbhai Merabhai

Savriya Piprali 2 0.6 1.2 50,217 25,109 41,848


42 Ralu Hurji Muniya Ambapada 1 0.4 0.4 16,304 16,304 40,761 Farm Yard Manure

0.013

66 Ganesh Kuka Garwal Satrundi 2 0.2 0.4 16,304 8,152 40,761 Farm Yard Manure

0.007

Annex


71


(Acre)

Y (t/acre)




GWF (m3/t)



140 Bheru Badda Singad Mahudipada 3 0.2 0.6 24,457 8,152 40,761 Farm Yard Manure

0.006

199 Manohar Shankar

Parihar Belam 10 0.8 8 326,087 32,609 40,761


463 Tejabhai Punjabhai

Sacvriya Morthala 1 0.4 0.4 16,304 16,304 40,761


104 Ghughabhai

Somabhai Rathod Mevasa 4 0.9 3.6 146,739 36,685 40,761


241 Laxmanbhai Lavjibhai

Sarsna 6 0.4 2.4 97,826 16,304 40,761 Farm Yard Manure

0.013

340 Khodabhai Jogabhai

Makwana Umiya 2 0.6 1.2 46,957 23,478 39,130


321 Jevabhai

Dharamsibhai Mali Bhotakiya 2 1.05 2.1 82,174 41,087 39,130


106 Bhikabhai Lagrabhai

Rathod Mevasa 3 1 3 116,217 38,739 38,739


273 Jetendra Rameshwar

Patidar Nandra 9 0.44 3.96 150,907 16,767 38,108


134 Anasingh Sarel Mohankot 1 0.48 0.48 18,261 18,261 38,043 Compost (phosphorous)

1.005

306 Chaganbhai Khimabhai Dumadiya

Morthala 3 0.66 1.98 73,370 24,457 37,055 Farm Yard Manure

0.019

102 Chaganbhai

Samabhai Sabliya Mevasa 5 0.8 4 146,739 29,348 36,685


103 Bhalsurbhai Jivlabhai

Rathod Mevasa 4 1 4 146,739 36,685 36,685


444 Walsibhai Pragjibhai

Sonagra Than 2 0.25 0.5 17,870 8,935 35,739


Annex


72


(Acre)

Y (t/acre)




GWF (m3/t)



343 Puranbhai

Anantabhai Patel Padampar 4 1 4 140,870 35,217 35,217


267 Mayur Ambaram

Patidar Bandera 5 0.3 1.5 51,978 10,396 34,652


487 Manubhai Punabhai

Makwana Pipliya(Dhora) 2 0.5 1 32,609 16,304 32,609


139 Tersingh Ambaram



236 Gyanchand Dashrath

Patidar Nandra 3 0.57 1.71 54,000 18,000 31,579


332 Sujabhai Dungarbhai

Soda Bhimasar 4 0.95 3.8 117,391 29,348 30,892


9 Nangi Moti Singad Mahudipada 2 0.4 0.8 24,457 12,228 30,571 Farm Yard Manure

0.009

90 Akkabhai Bacchubhai Makwana

Piprali 2 0.4 0.8 24,457 12,228 30,571 Farm Yard Manure

0.009

87 Gagajibhai

Bansirambhai Nandoliya

Surei 3 0.8 2.4 73,370 24,457 30,571 Farm Yard Manure

0.019

270 Ramesh Gulabchand

Patidar Nandra 8 0.75 6 179,896 22,487 29,983


98 Labhubhai Prabhubhai Rangpara


0.014

282 Iratbhai Danabhai

Patel Wandhiya 20 0.25 5 146,739 7,337 29,348


354 Danabhai Dudhabhai

Parmar Bhimasar 4 1 4 117,391 29,348 29,348


Annex


73


(Acre)

Y (t/acre)




GWF (m3/t)



385 Manubhai Babubhai

Chawda Palsava‐ 2 1 2 58,696 29,348 29,348


69 Ranchod Rana

Bhavriya Got 3 0.28 0.84 24,457 8,152 29,115


328 Meghabhai

Babubhai Makwana Palsava‐ 9.5 1.05 9.975 278,804 29,348 27,950


374 Pethabhai Bagabhai

Rathod Kidiyanagar 7 0.86 6.02 164,348 23,478 27,300


375 Kanhabhai

Samatbhai Rathod Kidiyanagar 7 0.86 6.02 164,348 23,478 27,300


33 Sukhram Narayan

Damar Lalarundi 1 0.24 0.24 6,522 6,522 27,174


268 Sukhdev Jagannath

Patidar Bandera 5 0.6 3 81,522 16,304 27,174


483 Devabhai Nihalbhai



123 Rama Nandaji

Gamad Mohankot 3 0.32 0.96 24,457 8,152 25,476


13 Tersing Velji Singad Satrundi 3 0.32 0.96 24,457 8,152 25,476 Farm Yard Manure

0.007

79 Abubhai Bhavriya Got 2 0.32 0.64 16,304 8,152 25,476 Farm Yard Manure

0.006

382 Kumbhabhai

Bhimabhai Rathod Kidiyanagar 6 1 6 147,913 24,652 24,652


471 Waljibhai Sairambhai

Rajpura Mokasara 2 1.1 2.2 54,000 27,000 24,545


54 Rama Thavra Dayima Lalarundi 4 0.24 0.96 23,478 5,870 24,457 Farm Yard Manure

0.005

117 Ratanji Ninama Ambapada 2 0.48 0.96 23,478 11,739 24,457 Farm Yard Manure

0.009

Annex


74


(Acre)

Y (t/acre)




GWF (m3/t)



75 Dinesh Murlibhai

Devda Narayansari 3 0.4 1.2 29,230 9,743 24,359


312 Jasubahen Arjibhai

Nadoliya Surei 3 1.2 3.6 87,050 29,017 24,180


355 Kishorebhai

Khimabhai Makwana Bhimasar 2 1.25 2.5 58,696 29,348 23,478


4 Romisingh Gendalal

Ghatiya Garvakhedi 2 0.4 0.8 18,130 9,065 22,663


472 Raghobhai Motibhai

Rajpura Mokasara 2.5 1.2 3 67,973 27,189 22,658


23 Amarsingh Sarel Jampada 4 0.32 1.12 25,109 7,174 22,418 Farm Yard Manure

0.006

67 Bhurji Thauji Singad Satrundi 3 0.2 0.6 12,717 4,239 21,196 Farm Yard Manure

0.004

445 Sureshbhai

Pragjibhai Sonagra Than 2 0.4 0.8 16,930 8,465 21,163


128 Rafel Antony Bhuriya Mohankot 2 0.3 0.45 9,325 6,217 20,722 Farm Yard Manure

0.005

14 Pema Dholsingh

Khadiya Chavriya 4 0.4 1.6 32,609 8,152 20,380


18 Kodar Harchand



45 Madima Ninama Ambapada 3 0.4 1.2 24,457 8,152 20,380 Farm Yard Manure

0.006

118 Bander Munia Ambapada 4 0.4 1.6 32,609 8,152 20,380 Farm Yard Manure

0.007

56 Mansing Shambhu

Katara Satrundi 1 0.4 0.4 8,152 8,152 20,380


119 Mangalsing Singad Satrundi 3 0.4 1.2 24,457 8,152 20,380 Farm Yard Manure

0.006

Annex


75


(Acre)

Y (t/acre)




GWF (m3/t)



55 Veersingh Vajja

Ninama Lalarundi 1 0.4 0.4 8,152 8,152 20,380


83 Ghuma Kanna

Bhuriya Got 4 0.4 1.6 32,609 8,152 20,380


46 Amdhu Naniya Chinkavani 8 0.4 3 61,141 8,152 20,380 Farm Yard Manure

0.006

492 Harjibhai Shyambhai

Dumadiya Tajpar 2 0.8 1.6 32,609 16,304 20,380


88 Vinabhai Ghusabhai

Nadoliya Surei 2 0.8 1.6 32,609 16,304 20,380


100 Govardhanbhai Jeevanbhai Makwana


0.008

430 Dharamsi

Dhannabhai rangpara

Sarsna 3 0.66 1.98 40,109 13,370 20,257 Farm Yard Manure

0.010

395 Manjibhai

Dharambhai Patel Shikharpur 2 0.3 0.6 11,739 5,870 19,565


107 Kalu Mansingh

Dindor Mahudipada 2 0.4 0.8 15,652 7,826 19,565


281 Ganeshbhai

Bacchubhai Patel Wandhiya 25 0.24 6 117,391 4,696 19,565


314 Kanubhai

Mashakbhai Nandoliya

Surei 4 0.43 1.72 32,609 8,152 18,959 Farm Yard Manure

0.006

6 Laxman Varda Loda Garvakhedi 3 0.48 1.44 27,196 9,065 18,886 Farm Yard Manure

0.057

481 Hirabhai Vatsabhai

Makwana Pipliya(Dhora) 1 1 1 18,652 18,652 18,652


Annex


76


(Acre)

Y (t/acre)




GWF (m3/t)



26 Mrs Saguna Thavariya

Mohankot 3 0.3 0.9 16,141 5,380 17,935 Farm Yard Manure

0.004

74 Dulla Rana Bhavriya Got 3 0.48 1.44 24,457 8,152 16,984 Farm Yard Manure

0.006

3 Bhavashya Ramsingh

Ghatiya Garvakhedi 2 0.48 0.96 16,304 8,152 16,984


429 Lilabhai Lavjibhai Sarsna 16 0.31 4.96 81,522 5,095 16,436 Farm Yard Manure

0.004

16 Narji Ravji Khadiya Chavriya 3 0.32 0.96 15,652 5,217 16,304 Farm Yard Manure

0.004

43 Khushal Kanara

Gomad Ambapada 4 0.4 1.5 24,457 6,522 16,304


135 Bapu Ramaji Sarel Jampada 3 0.5 1.25 20,380 8,152 16,304 Farm Yard Manure

0.006

114 Mana Vesta Bhuriya Chinkavani 3 0.4 1 16,304 6,522 16,304 Farm Yard Manure

0.005

494 Chaganbhai

Kadvabhai makwana Tajpar 2 1 2 32,609 16,304 16,304


448 Ambaram Madhurbhai Makwana

Than 4 0.6 2.4 39,130 9,783 16,304 Farm Yard Manure

0.008

84 Medha Dhanna

Bhuriya Chinkavani 4 0.4 1.6 26,087 6,522 16,304


115 Ramesh Hursingh

Bhabar Chinkavani 4 0.4 1.6 26,087 6,522 16,304


1 Anusaya Lokendra

Jani Garvakhedi 4 0.6 2.4 37,304 9,326 15,543


205 Inder Ramsingh

Parihar Belam 8 0.8 6.4 96,522 12,065 15,082


Annex


77


(Acre)

Y (t/acre)




GWF (m3/t)



206 Mamta Inder Parihar Belam 7 0.8 5.6 84,457 12,065 15,082 Compost (phosphorous)

1.000

477 Parasottambhai Shivasibhai

Mokasara 1 1 1 14,739 14,739 14,739 Farm Yard Manure

0.011

283 Laxman Sojibhai

Patel Wandhiya 20 0.2 4 58,696 2,935 14,674


31 Ukar Varda Vasuniya Lalarundi 2 0.4 0.8 11,087 5,543 13,859 Farm Yard Manure

0.004

326 Sevabhai Ranabhai

Parmar Palsava‐ 3.5 0.86 3.01 41,087 11,739 13,650


21 Ambaram Sarel Jampada 6 0.6 3.6 48,913 8,152 13,587 Farm Yard Manure

0.006

124 Saliya Magu Sarel Mohankot 2 0.48 0.72 9,783 6,522 13,587 Farm Yard Manure

0.005

141 Lalu Gangaram



22 Sukram Sarel Jampada 2 0.48 0.96 13,043 6,522 13,587 Farm Yard Manure

0.005

495 Payabhai Ukabhai

Dervadiya Tajpar 2 1 2 26,804 13,402 13,402


464 Saganbhai

Sangrambhai Savriya Morthala 2 0.65 1.3 16,304 8,152 12,542


85 Sohan Dhanna

Bhuriya Chinkavani 3 0.48 1.44 17,609 5,870 12,228


149 Dilip Bhanvarlal

Bhilodiya Garvakhedi 3 0.72 2.16 26,217 8,739 12,138


48 Pappu Khimchander

Meda Got 3 0.68 1.7 20,380 8,152 11,988


24 Munna Nanar Damar Jampada 4 0.5 2 23,478 5,870 11,739 Farm Yard Manure

0.005

Annex


78


(Acre)

Y (t/acre)




GWF (m3/t)



476 Chanabhai

Bhikhabhai Rajpura Mokasara 8 0.75 6 69,287 8,661 11,548


309 Alabbhai Sadurbhai

Khorakiya Tajpar 2 1.1 2.2 24,457 12,228 11,117


493 Rameshbhai

Danatbhai Jadhav Tajpar 2 1.1 2.2 24,457 12,228 11,117


148 Bhanvarlal Shobharam Bhilodiya

Garvakhedi 4 0.8 3 32,772 8,739 10,924 Farm Yard Manure

0.056

449 Sureshbhai

Nagarbhai Makwana Than 5 0.6 3 32,609 6,522 10,870


70 Babanu Nathu Meda Got 4 0.8 3.2 32,609 8,152 10,190 Farm Yard Manure

0.006

19 Kalu Vesta Sarel Jampada 4 0.6 2.25 22,011 5,870 9,783 Farm Yard Manure

0.005

310 Amirbhai Kadwabhai

Makwana Tajpar 2 1.3 2.6 24,457 12,228 9,406


44 Kathadi ma Ninama Ambapada 4 0.48 1.92 16,304 4,076 8,492 Farm Yard Manure

0.003

32 Malji Narayan Damar Lalarundi 4 0.48 1.92 16,304 4,076 8,492 Farm Yard Manure

0.003

47 Omar Bhuriya Chinkavani 5 0.4 2 16,304 3,261 8,152 Farm Yard Manure

0.003

17 Malji Galiya Khadiya Chavriya 4 0.4 1.7 13,859 3,261 8,152 Farm Yard Manure

0.003

15 Tersingh Amra

Hatela Chavriya 4 0.48 1.92 13,043 3,261 6,793


137 Dhaharu Dholsingh



Annex


79


(Acre)

Y (t/acre)




GWF (m3/t)



245 Suresh Mangilal

Patidar Bandera 8 0.44 3.52 13,043 1,630 3,706

Castor Cake 0.001

154 Jagannath Yadav Loundi 2 0.6 1.2 3,600 1,800 3,000 Compost (phosphorous)

0.001

215 Govardhan

Parshuram Tiwari Bagpal 9 0.6 5.4 11,645 1,294 2,157


246 Mahadev Jagdish

Patidar Bandera 8 0.5 4 8,139 1,017 2,035

Castor Cake 0.001

228 Ganesh Shankar

Patidar Astriya 10 0.7 7 9,783 978 1,398


218 Kadwa Ramaji

Harijan Bagpal 3 0.33 0.99 0 0 0

no info 0.000

371 Devrajbhai

Raghubhai Patel Narayansari 60 0.13 7.8 0 0 0

no info 0.000

372 Gelabhai

Dharamsibhai Patel Narayansari 15 0.03 0.45 0 0 0

no info 0.000

285 Vatsabhai Manubhai

Minaj Juna Katariya 23 0.28 6.44 0 0 0

no info 0.000

286 Akhai Karsanbhai

Fushi Juna Katariya 9 0.11 0.99 0 0 0

no info 0.000

287 Ramji Kanha Ravriya Juna Katariya 30 0.13 3.9 0 0 0 no info

0.000

288 Gela Murli Ravriya Juna Katariya 28 0.14 3.92 0 0 0 no info

0.000

366 Alanda Harkha Patel Juna Katariya 20 0.08 1.6 0 0 0 no info

0.000

369 Veljibhai Khegdibhai

Patel Juna Katariya 25 0.08 2 0 0 0

no info 0.000

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Grey WF Phase II Final Report Updated 30.06.2013 · 2014-09-26 · Approximately 40% of the cotton...

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