Sensor nutrient management swcs williams

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Sensor-based Nitrogen Management for Cotton in

Coastal Plain Soils

Sensor-based Nitrogen Management for Cotton in

Coastal Plain SoilsPhillip Williams, Ahmad Khalilian,

Michael Marshall, Jose Payero,

Ali Mirzakhani

71st SWCS International Annual ConferenceLouisville, KY, July 24-27, 2016

ACKNOWLEDGMENTSThis Demonstration project is supported by:

USDA/NRCS CIGAward No. 69-3A75-14-268

Clemson Public Service Activities

This Demonstration project is supported by:

USDA/NRCS CIGAward No. 69-3A75-14-268

Clemson Public Service Activities

ClayClay

SandSand

Sandy LoamSandy Loam

Field variations result in the developmentof plants with a tremendous amount ofgrowth variability, which have a majorimpact on fertilizer management strategies.

Cotton Yield

Cot

ton

Lint

(lbs

/acr

e)

Soil EC (mS/m)

R2

= 0.9202

0

300

600

900

1200

0 2 4 6 8

Soil EC, at planting

N Rate (lbs/A)

LowEC: Medium High

0

500

1000

1500

2000

2500

0 20 40 60 80 100 120 140

Effects of soil EC and N rate on seed cotton yields (lbs/acre)

Seed

Cot

ton

Yiel

d

Several researchers have developed algorithms for sensor-based N applications for corn, cotton & wheat.

However, due to higher precipitation, significant variation in soil texture, low soil organic matter content, and low nutrient holding capacity of soils in Coastal Plain regions, N-application algorithms, developed at other regions, either under- or over-estimated nitrogen rates for crop production.

EC Zones

Seed

Cot

ton

Yiel

d Effects of Nitrogen Management

Systems on Cotton Yield

Clemson

Farmer

OSU

Low Medium High0

500

1000

1500

2000

2500

3000

Clemson Yield Prediction Equations

INSEY

Seed

 Cotton Yield

y = 320.31e112.2x

R² = 0.761

y = 502.82e116.07x

R² = 0.8837

0

500

1000

1500

2000

2500

3000

3500

0 0.005 0.01 0.015 0.02 0.025

Irrigated

Dry Land

Algorithm ComparisonClemson Algorithm OSU Algorithm

YP0= 235.96 e 2216.2 * INSEY

INSEY= NDVI/Cumulative GDD

RI = 1.8579 * RINDVI – 0.932

%N= 0.09

NUE = 0.50

(YP0 * RI –YP0) * %NN Rate =NUE

YP0= 413.46 e 104.98 * INSEY

INSEY= NDVI/# Days After emergence

RI = High NDVI/Field Avg. NDVI

%N= 0.04

NUE= 0.50

EC Zones

Seed

Cot

ton

Yiel

d (lb

s./a

cre)

Sensor:47 lb./A Conv.:90 lb./A ($48% less)

Low Medium High0

1000

2000

3000

On average, growers in the US apply about 90 lb./acre N for cotton, for a total of 1.7 million tons.

Sensor-based N application has the potential to reduce nitrogen rates by half. Even a 20% reduction in nitrogen rate could save our cotton growers over $100 million annually.

Objective To demonstrate the benefits of

sensor-based nitrogen management strategies to growers, utilizing plant NDVI, Clemson algorithms for Irrigated and dry land cotton, soil amendments, and soil electrical conductivity (EC) data (management zones).

Overall Objective To assist cotton, corn, and wheat

farmers in the Southeastern Coastal Plain region, to adopt innovative and proven conservation technologies for achieving 4R (right source, rate, time, and place) nutrient management.

Demonstration Sites (2015-16)

Al Cribb FarmWalker Nix FarmJeff Lucas FarmWilliams FarmJB FarmsBates FarmEdisto REC (3 sites)Pee Dee REC (2 sites)

Identifying management zones

Establishing nitrogen rich strips

Measuring NDVI utilizing sensors

Calculating nitrogen requirements

Methods for Managing Nitrogen

Soil ElectricalConductivity (EC) meter

EC Map, Cribb Farm

Identifying management zones

4 rows by 50 feet; More nitrogen than theplants can use is applied (150 lbs/A for cotton).

Establishing nitrogen rich strips

Measuring NDVI utilizing sensorsNDVI = (NIR - Red) / (NIR + Red)

Handheld Data Collection

• Handheld units– Mobile– Cost effective

• Only does small area but gives average

Whole Field NDVI Mapping• Sensors mounted on sprayer booms,

fertilizer applicators, or any mobile field equipment.

• Provides a whole field map that can be used in fertilizer applicators or can apply fertilizer “on-the-go”.

Aerial Mapping• Unmanned Aerial Vehicle (UAV) can be

used to fly over fields and collect data that can then be made into a prescription map.

Calculating nitrogen requirements• Excel file can be used to calculate N rates.• NDVI data from UAV, handheld, or field

equipment can be used as input.

Mobile Application and Website

The application is designed for smartphones, tabletsand computers.

Planting DateNDVI: N Rich StripNDVI: FieldMax Yield HistoryIrrigated or Dryland

N-rates for each zone

Variable-rate Nitrogen Applicator Rawson Hydraulic Controller

2015 Test Results

Farm Previous Crop

N At Planting (lbs./acre)

Sensor‐based N Zone 1    Zone 2

(lbs./acre)

Grower N rate

(lbs./acre)

N Saved (lbs. /acre)

Savings ($/acre)

Walker Peanuts 0 40 20 90 50 ‐70 30 ‐ 42

Al Cribb Cotton 45 0 0 90 45 27

Jeff Lucas Clover Chicken 

litter 0 0 90‐100 90‐100 54‐60

Pee Dee Cotton 0 40‐100    Ave. 60 75 15 9

Statistically there were no differences in cotton yields between farmers’ practice and sensor-based method at all locations

There is a potential to use mid-season plant NDVI data for variable-rate application of N fertilizer in cotton production, in a user friendly manner that growers and extension can utilize.

Summary

Soil EC management zones should be used for calculating nitrogen application rates in the Southeastern Coastal Plain region. This in addition to sensor technology can work in conjunction to give growers more information to make better management decisions.

Summary

Soil amendments (such as poultry litter) and/or previous crops (such as a legume like peanuts or soybeans) had a significant effect on required nitrogen rates determined by a sensor.

Summary

Sensor-based N management techniques, reduced nitrogen usage by 15 to 100 lbs./acre in cotton, compared to growers‘ application rates. This resulted in $9 to $60 savings/acre.

Summary

Questions?Questions?