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Field Crops Research 101 (2007) 104–116

Genetic variability and interrelationship among various morphological

and quality traits in quinoa (Chenopodium quinoa Willd.)

Atul Bhargava *, Sudhir Shukla, Deepak Ohri

Division of Genetics and Plant Breeding, National Botanical Research Institute, Lucknow 226001, India

Received 29 September 2006; accepted 10 October 2006

Abstract

Evaluation of seed yield, morphological variability and nutritional quality of 27 germplasm lines of Chenopodium quinoa and 2 lines of C.

berlandieri subsp. nuttalliae was carried out in subtropical North Indian conditions over a 2-year period. Seed yield ranged from 0.32 to 9.83 t/ha,

higher yields being shown by four Chilean, two US, one Argentinian and one Bolivian line. Two lines of C. berlandieri subsp. nuttalliae exhibited

high values for most of the morphological traits but were low yielding. Seed protein among various lines ranged from 12.55 to 21.02% with an

average of 16.22 � 0.47%. Seed carotenoid was in the range of 1.69–5.52 mg/kg, while leaf carotenoid was much higher and ranged from 230.23 to

669.57 mg/kg. Genetic gain as percent of mean was highest for dry weight/plant, followed by seed yield and inflorescence length. All

morphological traits except days to flowering, days to maturity and inflorescence length exhibited significant positive association with seed

yield. The association of leaf carotenoid with total chlorophyll and seed carotenoid was positive and highly significant. The path analysis revealed

that 1000 seed weight had highest positive direct relationship with seed yield (1.057), followed by total chlorophyll (0.559) and branches/plant

(0.520). Traits showing high negative direct effect on seed yield were leaf carotenoid (�0.749), seed size (�0.678) and days to flowering (�0.377).

Total chlorophyll exerted strongest direct positive effect (0.722) on harvest index, followed by seed yield (0.505) and seed protein (0.245).

# 2006 Elsevier B.V. All rights reserved.

Keywords: Chenopodium quinoa; Seed yield; Harvest index; Protein; Carotenoid; Heritability; Genetic advance; Correlation; Selection approaches

1. Introduction

Quinoa (Chenopodium quinoa Willd.), an Andean crop, has

recently gained worldwide attention because of its ability to grow

in various stress conditions like soil salinity, acidity, drought,

frost, etc. (Vacher, 1998; Jensen et al., 2000; Bhargava et al.,

2003a, 2006a; Jacobsen et al., 2003). Apart from this, its grain is a

rich source of a wide range of minerals, vitamins, oil containing

large amounts of linoleate, linolenate and natural antioxidants

(Koziol, 1992; Repo-Carrasco et al., 2003) and high quality

protein containing ample amounts of sulphur rich amino acids

(Koziol, 1992). These benefits coupled with increasing demand

for quinoa and insufficient supply from quinoa producing

countries of South America necessitates introduction of the crop

to newer areas. Quinoa was introduced in England in 1970 and

later in Denmark. The crop has gained firm ground in the region

and many varieties suited to local conditions have been released

(Mastebroek and Limburg, 1996; Jacobsen, 2003). In the United

* Corresponding author. Tel.: +91 522 2205831; fax: +91 522 2205836.

E-mail address: atul_238@rediffmail.com (A. Bhargava).

0378-4290/$ – see front matter # 2006 Elsevier B.V. All rights reserved.

doi:10.1016/j.fcr.2006.10.001

States, work with quinoa started in the early 1980s and presently

its consumption is approximately 1500 t/ha. However, in Asia,

concerted research efforts on quinoa are lacking and the crop has

not been provided due importance.

The Indo-Gangetic plain (IGP), a region of land covering

large areas of India, Pakistan, Nepal and Bangladesh, is

characterized by fertile soils, favourable climate and an

abundant supply of water (Aggarwal et al., 2004). In India,

the states of Uttar Pradesh and Bihar constitute an important

transect of the IGP which is characterized by hot, subhumid

climate with bulk of rainfall received during the monsoon

season. The winters in the transect are cool and nearly uniform

climatic features are present in these states with slight

deviations. However, this area is also amongst the most prone

areas of the world to degradation of natural resources due to

intense human activity. There is growing concern about the

decline in soil fertility, changes in water table depth,

deterioration in the quality of irrigation water, and rising

salinity in the region (Joshi and Tyagi, 1994; Aggarwal et al.,

2004). A large portion of the population in this region has little

access to protein rich diet since wheat and rice are the principal

food crops grown and consumed in the area. The increasing

A. Bhargava et al. / Field Crops Research 101 (2007) 104–116 105

population demands an increase in food production along with

a shift towards environmentally sound sustainable agriculture.

There is a need for cultivation of crops that requires minimum

inputs, but can counter the nutritional deficiency prevalent in

the general population of this region. Quinoa can be termed

‘underutilized’, especially for India, since inspite of its wide

adaptability, rusticity and nutritional superiority, its commer-

cial potential has remained untapped. Quinoa’s highly

proteinaceous grain can help to make diets more balanced in

this region and can play an important role in combating ‘silent

hunger’ among poor populations in India who have little access

to protein rich diet. Quinoa’s ability to produce high protein

grains under ecologically extreme conditions makes it

important for the diversification of future agricultural systems,

especially in high altitude area of the Himalayas and North

Indian Plains. The worldwide popularity of quinoa and initial

promising reports from India (Bhargava et al., 2003a) makes it

imperative for its evaluation in this transect of the IGP to

explore its potential as an alternative winter crop in the region.

The main aim of quinoa breeders is the development of

cultivars with high grain yield and quality components, adapted

to diverse agro-climatic regions. Inspite of the immense

nutritive importance of the crop, not much work has been done

for its genetic improvement leading to lack of information on

many aspects. Breeding a crop for new and targeted

environments requires the use of a range of cultivars/genotypes

since it allows us to quantify intraspecific variability for

different traits and their interactions. Genetic variability in the

base population plays a very important role in any crop-

breeding program. The extent of diversity present in the

germplasm determines the limits of selection for improvement.

The characters of economic importance are generally

quantitative in nature and exhibit considerable degree of

interaction with the environment. Thus, it becomes imperative

to compute the variability present in the material and its

partitioning into genotypic, phenotypic and environmental

ones. Improvement of yield requires an in-depth knowledge of

the magnitude of variation present in the available germplasm,

interdependence of quantitative characters with yield, extent of

environmental influence on these factors, heritability and

genetic gain of the material. Correlation coefficients show

relationships among various traits along with the degree of

linear relation between these characters. But, correlation

studies provide incomplete information on the relative

importance of the direct and indirect effects of individual

traits on yield. Thus, simple correlations are less likely to

provide a clear picture of the importance of each component

trait in determining yield. In such condition, it becomes

necessary to study the path coefficient analysis, which takes

into account not only the causal relationship, but also the degree

of relationship among the traits. Path analysis, also known as

standardized partial-regression coefficient, partitions the

correlation coefficients into direct and indirect effects and

thereafter allows the separation of direct influence of each trait

on yield from the indirect effects caused by mutual association

among the traits themselves (Garcia del Moral et al., 2003).

Reports on variability and association among different traits in

quinoa are rare, based on few yield components and are based

on experiments carried out in America and Europe (Risi and

Galwey, 1989; Rojas et al., 2003). Detailed experimental results

on morphological and qualitative variability, and correlation

and path analysis from Asia, particularly the Indo-Gangetic

plains are altogether absent. Therefore, the present study was

conducted with the following objectives:

(a) T

o ascertain the suitability of quinoa as a new winter crop in

the Indo-Gangetic plains of northern India.

(b) T

o evaluate the morphological and qualitative character-

istics of quinoa germplasm.

(c) T

o elucidate interrelationships among yield and yield

components using correlation analysis and supplementing

correlation results using path coefficient analysis.

(d) T

o determine the selection criteria for increasing seed yield

and harvest index.

2. Materials and methods

2.1. Experimental site

The experiment was conducted at the experimental field of

National Botanical Research Institute, Lucknow. The experi-

mental site is situated at an altitude of 120 m above sea level at

26.5 8N latitude and 80.5 8E longitude. In the Indo-Gangetic

plains of North India there are two main crop seasons, summer

(kharif—March to July) and winter (rabi—October to

February). Chenopodium grows mostly during the rabi season.

During the rabi season, the minimum and maximum

temperature ranges from 2.5 to 19 and 14 to 29 8C, respectively.

2.2. Experimental set up

Field experiments were conducted in the crop years 2002–

2003 and 2003–2004 on sandy loam soil at the experimental

site. The weather parameters prevailing during both the

experimental years have been provided in Table 1. Twenty-

seven germplasm lines of C. quinoa and two lines of its closest

relative, C. berlandieri subsp. nuttalliae (all introduced) were

sown as a rabi crop in mid November in both the years and

evaluated for various morphological and quality traits. The

colour of the seeds was determined as translucent, white,

yellow, orange, red, ochre, brown purple or black. The first four

were categorized as light while the latter five as dark (Table 2).

All the lines selected were tetraploid (2n = 36), and had been

collected from varying altitudes and locations (Table 2). The

field was disc ploughed and then harrowed and raked to obtain a

good seed bed before sowing. The experimental design was a

randomized block with three replications. The plot size for each

replication was 2 m � 2 m. Each plot had 6 rows spaced 30 cm

apart and each row had 10 plants separated at 20 cm from each

other. For the whole crop season, weeding followed by hoeing

was done at an interval of 15 days. Irrigation was provided as

and when needed. No chemical fertilizer was applied either

before or during the experiment. These was primarily done to

ascertain the potential of the crop for subsistence agriculture

Table 1

Weather conditions during the first and second experiments

Temperature

(8C)

Dew point

(8C)

Wind

(km/h)

Maximum Minimum Mean

Experiment I (2002–2003)

November 24 16 20 14 3

December 18 11 15 10 4

January 15 7 11 8 3

February 24 11 18 12 6

March 30 16 23 13 7

April 38 23 30 15 9

Experiment II (2003–2004)

November 28 14 21 12 2

December 21 11 16 11 4

January 10 8 9 7 3

February 25 12 19 11 4

March 34 17 26 13 5

April 37 23 30 16 7

A. Bhargava et al. / Field Crops Research 101 (2007) 104–116106

since a large chunk of the farmers in the region are financially

weak and seek crops with fewer inputs. We tried to emulate the

same type of cultivation practice as followed in the Peruvian

altiplano, where farmers do not use any kind of fertilizers for

Table 2

Germplasm lines, their source, origin and seed colour

Germplasm line Source

C. quinoa Willd. CHEN 58/77 IPK Gatersleben, Germany

C. quinoa Willd. CHEN 67/78 IPK Gatersleben, Germany

C. quinoa Willd. CHEN 71/78 IPK Gatersleben, Germany

C. quinoa Willd. CHEN 33/84 IPK Gatersleben, Germany

C. quinoa Willd. CHEN 84/79 IPK Gatersleben, Germany

C. quinoa Willd. CHEN 92/91 IPK Gatersleben, Germany

C. quinoa Willd. CHEN 7/81 IPK Gatersleben, Germany

C. quinoa Willd. PI 614938 USDA

C. quinoa Willd. PI 478408 USDA

C. quinoa Willd. PI 478414 USDA

C. quinoa Willd. PI 596498 USDA

C. quinoa Willd. Ames 13219 USDA

C. quinoa Willd. Ames 13719 USDA

C. quinoa Willd. PI 587173 USDA

C. quinoa Willd. PI 510532 USDA

C. quinoa Willd. PI 614883 USDA

C. quinoa Willd. PI 584524 USDA

C. quinoa Willd. Ames 22156 USDA

C. quinoa Willd. Ames 13762 USDA

C. quinoa Willd. PI 614881 USDA

C. quinoa Willd. PI 510537 USDA

C. quinoa Willd. PI 510547 USDA

C. quinoa Willd. Ames 22158 USDA

C. quinoa Willd. PI 510536 USDA

C. quinoa Willd. PI 478410 USDA

C. quinoa Willd. PI 433232 USDA

C. quinoa Willd. Ames 21909 USDA

C. berlandieri subsp. nuttalliae PI 568155

(Saff.) Wilson and Heiser

USDA

C. berlandieri subsp. nuttalliae PI 568156

(Saff.) Wilson and Heiser

USDA

a From germplasm database record of the collection or donation site, which migb Since C. quinoa Willd. is not native to USA, this indicates the location of a g

quinoa and the plant survives mainly on residues of manure or

fertilizer from the previous crop (Aguilar and Jacobsen, 2003).

Each germplasm line was sown in a separate plot and

thinning was done to maintain plant density within rows.

Irrigation was applied as and when needed. No fungicide or

insecticide was used during the experiment. Hand weeding was

carried out once in 20 days to remove unwanted plants.

2.3. Parameters estimated

Ten plants from the central rows of each germplasm line in

each replication were randomly tagged and data were recorded

on these plants for the following morphological traits:

(a) D

Sta

–

–

–

–

–

–

–

–

Cul

Cul

Lan

–

–

Cul

Cul

–

Cul

Cul

–

–

Cul

Cul

Lan

Cul

Cul

–

Lan

Lan

Lan

ht n

ermp

ays to flowering: the number of days from the date of

emergence to the date at which about 50% of the plants in a

plot showed blooming.

(b) D

ays to maturity: days to maturity was taken from date of

emergence to the date when the crop was ready for

harvesting, i.e. seeds had become mature and the plant had

started drying.

(c) P

lant height (cm): the average height from the ground level

to the tip of the inflorescence on the main stem at the time of

harvesting was measured.

tusa Origina Altitudea (m) Seed colour

– 4000 Light

Puno, Peru – Dark

Bolivia – Light

– – Light

Cuzco, Peru 3200 Light

Columbia – Light

– – Light

Oruro, Bolivia – Light

tivar La Paz, Bolivia 3800 Light

tivar La Paz, Bolivia 3800 Dark

drace Cuzco, Peru 3030 Light

La Paz, Bolivia 3700 Light

New Mexico, USAb – Light

tivated Jujuy, Argentina – Light

tivated Peru 3000 Light

Jujuy, Argentina – Light

tivated Chile – Light

tivar Chile – Light

New Mexico, USAb – Light

Jujuy, Argentina – Light

tivated Peru – Dark

tivated Peru – Dark

drace Chile – Light

tivated Peru – Dark

tivar La Paz, Bolivia 3800 Light

Chile – Light

drace Oruro, Bolivia 3870 Light

drace Mexico 1680 Dark

drace Mexico 2700 Dark

ot indicate biological adaptation.

lasm donation, and might not indicate biological adaptation.

A. Bhargava et al. / Field Crops Research 101 (2007) 104–116 107

(d) L

eaf area (cm2): leaf area was measured for three positions,

viz. top, middle and lower, using the leaf area meter of Delta

T Devices Ltd., when the plant was in full bloom.

(e) P

rimary branches/plant: the total number of branches

growing from the main stem at different node positions,

including the basal branches.

(f) I

nflorescence length (cm): the mean length of three

inflorescence was taken randomly from different positions.

(g) I

nflorescence/plant: the number of inflorescence per plant

was counted at the time of harvest.

(h) S

eed size (mm): the seed size was measured following the

method suggested by Bertero et al. (2004).

(i) T

housand seed weight (g): a sample of 1000 seeds from the

bulked seed of each line was weighted.

(j) D

ry weight/plant (g): whole plants excluding the roots,

secondary branches and leaves were sun dried and weighted.

(k) H

arvest index: this was calculated by the following

formula:

harvest index ¼ seed yield=plant

dry weight=plant

(l) S

eed yield (t/ha): the seed of all the plants of each plot were

bulked and weighed and the seed yield/plot was then

converted to tonnes per hectare (t/ha).

Apart from this, four quality traits were also estimated

namely:

(a) T

otal chlorophyll (mg/g): total chlorophyll was calculated

from fresh leaves collected from the tagged plants at the 9-

week-old stage as per the method proposed by Jensen (1978).

(b) L

eaf carotenoid (mg/kg): the carotenoid content of leaves

was determined from fresh leaves collected from the tagged

plants at the 9-week-old stage as per the method described

by Jensen (1978).

(c) S

Table 3

eed carotenoid (mg/kg): seed carotenoid content was

estimated from the bulked seed of each line according to

Jensen (1978).

Mean squares of the analysis of variance for 12 morphological and 4 quality

traits in Chenopodium

(d) S

Traits Mean sum of squares

eed protein (%): the protein content was estimated from

the bulked seed of each germplasm line following the

method suggested by Peterson (1977).

Year I Year II G � year

Days to flowering 114.26** 131.55** 149.20

Days to maturity 513.15** 569.12** 484.62

Plant height (cm) 4003.66** 3840.29** 1019.06

Leaf area (cm2) 169.25** 188.11** 119.24

Branches/plant 96.12** 105.54** 101.50

Inflorescence length (cm) 5.46** 5.02 7.19*

Inflorescence/plant 5196.60** 5346.18** 4623.10

Seed size (mm) 0.14** 0.15** 0.12

1000 seed weight (g) 2.19** 2.30** 2.04

Dry weight/plant (g) 444.29** 418.82** 384.10

Harvest index 0.32** 0.35** 0.19

Seed yield (t/ha) 23.13** 26.29** 19.79

Total chlorophyll (mg/g) 0.337** 0.349** 0.302

Leaf carotenoid (mg/kg) 28559.40** 29014.54** 20126.43

Seed carotenoid (mg/kg) 2.49** 2.31** 1.93

Seed protein (%) 20.16** 19.44** 13.32

*P = 0.05; **P = 0.01.

2.4. Statistical analysis

The raw data was compiled by taking the means of all the

plants taken for each treatment and replication for different traits

in both the experimental years. The pooled means of both the

years were subjected to further statistical and biometrical

analysis. Simple statistical parameters, viz. mean, standard error,

variance and coefficient of variation were analyzed according to

Singh and Chaudhary (1985). Heritability is defined the fraction

of genetic variation in relation to environmental variance. For

computing broad sense heritability, the following formula

proposed by Singh and Chaudhary (1985) was used:

H ¼ s2g

s2 p

where s2g = genotypic variance and s2p = phenotypic var-

iance.

Genetic advance is referred as the difference between the

genotypic mean of selected lines and genotypic mean of

population. Genetic advance as percentage of mean was

calculated by the following formula (Singh and Chaudhary,

1985):

genetic advance ð%Þ ¼ genetic advance ðtraitÞmean ðtraitÞ � 100

Correlation analysis was performed to determine the

relationships between yield and all the component traits, both

at genotypic and phenotypic levels according to Johnson et al.

(1955a). The phenotypic level included both genotypic and

environmental factors, while genotypic analysis focused

strictly on genetic effects and excluded the environmental

ones. Path coefficients were then computed (Dewey and Lu,

1959) to separate the direct and indirect effects of correlation

coefficient. A significant positive correlation between a trait

and yield, high positive direct effect by that trait on yield and

minimal negative indirect effect by that trait on yield via other

traits, were the three factors that categorized the trait as

effective for yield improvement.

3. Results

3.1. Variability studies

The analysis of variance for two separate years revealed

significant differences among the strains for all the 16 characters,

which validated further statistical and genetic analysis (Table 3).

These results indicate the presence of a high degree of

morphological and qualitative variation among the lines studied.

The year � variety/line interaction was non-significant for all the

traits except for inflorescence length (Table 3).

Table 4

Mean performance of 29 lines for 12 morphological traits in Chenopodium

Germplasm lines Origin Days to

flowering

Days to

maturity

Plant

height

(cm)

Leaf

area

(cm2)

Primary

branches/

plant

Inflorescence

length (cm)

Inflorescence/

plant

Seed

size

(mm)

1000 seed

weight (g)

Dry

weight/

plant (g)

Harvest

index

Seed

yield

(t/ha)

C. quinoa CHEN 58/77 – 73.55 117.67 45.41 15.71 16.56 2.93 41.19 1.58 1.81 6.31 1.07 2.11

C. quinoa CHEN 67/78 Puno, Peru 74.55 119.44 59.63 6.12 16.70 1.71 91.63 1.34 0.78 5.75 0.74 3.75

C. quinoa CHEN 71/78 Bolivia 79.33 131.67 46.33 26.94 15.44 3.39 127.73 1.97 2.85 7.21 1.43 3.27

C. quinoa CHEN 33/84 – 101.55 144.00 42.33 9.46 16.96 2.42 13.85 1.57 2.07 3.84 1.40 1.33

C. quinoa CHEN 84/79 Cuzco, Peru 86.00 121.67 86.97 17.47 22.11 1.00 117.78 2.21 3.57 10.47 1.32 3.44

C. quinoa CHEN 92/91 Columbia 81.89 123.22 77.49 24.69 14.06 2.25 64.11 2.01 3.70 10.21 0.88 2.25

C. quinoa CHEN 7/81 – 85.11 133.78 123.56 22.14 28.00 4.09 141.55 2.09 3.65 28.00 1.41 9.83

C. quinoa PI 614938 Oruro,

Bolivia

71.00 109.33 11.27 5.67 10.00 1.07 11.67 1.73 1.87 1.11 1.06 0.32

C. quinoa PI 478408 La Paz,

Bolivia

71.33 109.33 17.67 8.93 8.55 0.84 14.65 2.17 2.87 1.26 1.19 0.47

C. quinoa PI 478414 La Paz,

Bolivia

83.66 134.11 78.98 21.53 20.55 1.60 106.48 1.81 3.03 14.00 1.25 6.07

C. quinoa PI 596498 Cuzco, Peru 83.77 129.00 65.87 20.82 17.33 2.47 90.33 2.03 3.08 19.89 0.79 3.93

C. quinoa Ames 13219 La Paz,

Bolivia

81.99 129.98 53.96 11.75 19.21 2.64 114.66 2.06 3.54 15.08 0.73 2.80

C. quinoa Ames 13719 New Mexico,

USA

82.21 120.28 115.52 25.03 27.74 2.67 98.00 2.15 3.65 32.03 0.99 9.33

C. quinoa PI 587173 Jujuy,

Argentina

85.33 125.78 101.03 30.91 16.74 2.25 68.50 2.01 4.09 15.47 0.81 3.17

C. quinoa PI 510532 Peru 86.67 157.11 144.03 22.02 25.55 2.24 138.22 1.51 1.25 52.89 0.29 1.68

C. quinoa PI 614883 Jujuy,

Argentina

70.78 109.89 54.89 12.33 21.89 3.61 45.89 1.73 1.77 3.03 0.97 1.00

C. quinoa PI 584524 Chile 81.33 127.00 115.89 29.64 25.00 2.51 137.55 1.58 3.02 29.86 0.90 6.60

C. quinoa Ames 22156 Chile 80.55 126.00 106.44 26.16 20.44 1.60 85.55 1.93 3.51 17.21 1.21 5.03

C. quinoa Ames 13762 New Mexico,

USA

79.33 132.44 123.72 5.00 23.00 4.31 136.44 1.83 2.75 35.21 0.94 8.50

C. quinoa PI 614881 Jujuy,

Argentina

87.11 127.22 113.00 25.00 24.56 3.01 114.22 2.05 2.94 24.16 1.34 8.25

C. quinoa PI 510537 Peru 84.33 124.00 100.00 14.39 25.44 1.44 136.00 1.78 2.71 13.02 1.32 4.39

C. quinoa PI 510547 Peru 82.11 131.78 66.67 16.02 14.11 2.08 68.92 1.82 3.13 12.67 1.33 4.70

C. quinoa Ames 22158 Chile 80.89 131.11 80.27 23.25 21.24 3.85 40.29 1.95 3.17 12.70 1.18 4.85

C. quinoa PI 510536 Peru 73.78 115.22 31.05 4.42 17.53 1.79 21.03 1.93 2.34 1.38 1.28 0.67

C. quinoa PI 478410 La Paz, Bolivia 82.77 126.78 101.10 17.29 22.61 0.90 118.33 1.80 2.63 29.00 0.43 3.13

C. quinoa PI 433232 Chile 81.00 130.00 108.66 23.01 20.89 4.54 74.22 1.77 2.28 13.11 1.09 3.56

C. quinoa Ames 21909 Oruro, Bolivia 82.55 152.44 82.44 25.87 21.00 2.12 132.22 1.83 3.31 15.97 1.15 9.08

C. berlandieri subsp.

nuttalliae PI 568155

Mexico 91.33 163.33 139.44 21.44 35.74 6.47 114.78 1.58 1.28 28.94 0.26 2.01

C. berlandieri subsp.

nuttalliae PI 568156

Mexico 85.33 152.33 135.44 13.53 29.11 4.77 103.39 1.65 1.37 15.05 0.65 2.32

Mean � S.E. 81.76 � 1.18 129.51 � 2.51 83.76 � 6.79 18.15 � 1.44 20.62 � 1.08 2.64 � 0.24 88.59 � 7.81 1.84 � 0 2.69 � 0.15 16.37 � 2.24 1.01 � 0.06 4.06 � 0.52

CD (5%) 2.41 5.14 13.90 2.94 2.21 0.49 15.99 0.06 0.30 4.58 0.12 1.06

CD (1%) 3.26 6.93 18.76 3.97 2.98 0.66 21.57 0.08 0.41 6.18 0.17 1.43

CV 7.82 10.44 43.67 42.75 28.32 49.62 47.48 11.41 31.97 73.85 32.16 68.34

A.

Bh

arg

ava

eta

l./Field

Cro

ps

Resea

rch1

01

(20

07

)1

04

–1

16

10

8

.03

Table 5

Mean performance of 29 lines for 4 quality traits in Chenopodium

Germplasm lines Origin Total chlorophyll (mg/g) Leaf carotenoid (mg/kg) Seed carotenoid (mg/kg) Seed protein (%)

C. quinoa CHEN 58/77 – 1.03 389.83 1.73 13.22

C. quinoa CHEN 67/78 Puno, Peru 1.70 531.03 3.12 21.02

C. quinoa CHEN 71/78 Bolivia 1.82 534.80 3.15 19.37

C. quinoa CHEN 33/84 – 0.55 230.23 1.69 16.92

C. quinoa CHEN 84/79 Cuzco, Peru 1.12 414.73 2.30 18.84

C. quinoa CHEN 92/91 Columbia 1.68 521.83 2.00 13.93

C. quinoa CHEN 7/81 – 1.92 632.40 3.30 17.31

C. quinoa PI 614938 Oruro, Bolivia 1.16 338.23 2.84 17.83

C. quinoa PI 478408 La Paz, Bolivia 1.19 330.03 2.74 15.23

C. quinoa PI 478414 La Paz, Bolivia 1.86 588.23 3.88 17.86

C. quinoa PI 596498 Cuzco, Peru 1.65 551.07 2.68 15.09

C. quinoa Ames 13219 La Paz, Bolivia 1.32 421.03 2.02 12.55

C. quinoa Ames 13719 New Mexico, USA 1.36 466.13 1.75 17.71

C. quinoa PI 587173 Jujuy, Argentina 1.85 580.43 3.86 14.66

C. quinoa PI 510532 Peru 1.34 483.13 2.06 14.51

C. quinoa PI 614883 Jujuy, Argentina 1.25 434.67 3.15 19.48

C. quinoa PI 584524 Chile 2.04 669.56 2.87 13.01

C. quinoa Ames 22156 Chile 1.86 611.83 2.81 14.24

C. quinoa Ames 13762 New Mexico, USA 1.60 519.90 2.08 15.47

C. quinoa PI 614881 Jujuy, Argentina 1.42 481.23 3.33 13.89

C. quinoa PI 510537 Peru 1.59 511.77 3.82 19.78

C. quinoa PI 510547 Peru 1.22 416.30 2.35 20.43

C. quinoa Ames 22158 Chile 1.06 414.63 2.40 16.09

C. quinoa PI 510536 Peru 1.09 371.80 2.84 20.39

C. quinoa PI 478410 La Paz, Bolivia 1.43 480.07 1.97 13.08

C. quinoa PI 433232 Chile 1.51 479.47 2.13 14.23

C. quinoa Ames 21909 Oruro, Bolivia 1.55 504.07 3.15 16.20

C. berlandieri subsp.

nuttalliae PI 568155

Mexico 1.17 601.90 5.52 13.28

C. berlandieri subsp.

nuttalliae PI 568156

Mexico 1.20 528.50 4.73 14.82

Mean � S.E. 1.43 � 0.06 484.09 � 18.37 2.83 � 0.16 16.22 � 0.47

CD (5%) 0.12 37.62 0.32 0.96

CD (1%) 0.16 50.75 0.44 1.29

CV 23.07 20.42 31.80 15.90

A. Bhargava et al. / Field Crops Research 101 (2007) 104–116 109

The mean values for different morphological and quality

traits are presented in Tables 4 and 5. Out of 29 lines, only 11

lines showed above average seed yield. Seed yield ranged from

0.32 to 9.83 t/ha with C. quinoa PI 614938 showing the lowest

yield. Highest seed yield was shown by C. quinoa CHEN 7/81

(9.83 t/ha), followed by C. quinoa Ames 13719 (9.33 t/ha) and

C. quinoa Ames 21909 (9.08 t/ha). These lines also showed

above average mean performance for most of the morpholo-

gical traits. The three lowest yielding lines, viz. C. quinoa PI

614938, C. quinoa PI 478408 and C. quinoa PI 510536 showed

low values for most morphological traits, total chlorophyll and

leaf carotenoid. Five germplasm lines of quinoa (CHEN 58/77,

Ames 13219, PI 510532, PI 478410 and PI 433232) were poor

both in terms of yield and quality. Both the lines of C.

berlandieri subsp. nuttalliae (PI 568155 and PI 568156)

exhibited high values for most of the morphological traits but

were low yielding (2.01 and 2.32 t/ha, respectively) (Table 4).

Harvest index ranged from 0.26 to 1.43, with C. quinoa CHEN

71/78 showing the highest value (1.43), followed by C. quinoa

CHEN 7/81 (1.41) and C. quinoa CHEN 33/84 (1.40). Seed

protein among the lines ranged from 12.55 to 21.02% with an

average of 16.22 � 0.47%, while seed carotenoid was in the

range of 1.69–5.52 mg/kg with a mean of 2.83 � 0.16 mg/kg

(Table 5). Highest seed protein was found in C. quinoa CHEN

67/78 (21.02%), followed by C. quinoa PI 510547 (20.43%)

and C. quinoa PI 510536 (20.39%) all of which had dark

coloured seeds. The carotenoid content in the leaves ranged

from 230.23 mg/kg for C. quinoa CHEN 33/84 to 669.56 mg/

kg for C. quinoa PI 584524, and was comparatively higher than

that found in the seeds. Seventy percent of the lines having high

leaf carotenoid also had high seed carotenoids. Among the 12

morphological traits, dry weight/plant, seed yield and

inflorescence length exhibited high values for coefficient of

variability while for quality traits these values were relatively

low, the highest being for seed carotenoid (31.80%) and the

lowest for seed protein (15.90%) (Table 5).

The values for variance, coefficient of variation, heritability

and genetic gain for different morphological and quality traits

are presented in Table 6. Phenotypic variance denoting total

variance was maximum for inflorescence/plant among mor-

phological traits and for leaf carotenoid among the quality

traits. The phenotypic coefficient of variation (PCV) values for

all the traits were higher than the corresponding genotypic

values (GCV) values though had small differences. Among all

Table 6

Range, variance, coefficient of variation, heritability and genetic gain for various morphological and quality traits in Chenopodium

Traits Range s2p s2g s2e PCV GCV Heritability (%) Genetic gain (%)

Days to flowering 70.78–101.55 42.36 40.43 1.93 7.96 7.77 95.45 15.65

Days to maturity 109.33–163.33 185.75 182.29 3.46 10.53 10.43 98.14 21.27

Plant height (cm) 11.27–144.03 1347.37 1333.55 13.82 43.82 43.59 98.97 89.35

Leaf area (cm2) 4.42–30.91 62.47 59.16 3.31 43.53 42.36 94.69 84.94

Primary branches/plant 8.55–35.74 35.20 33.59 1.61 28.76 28.10 95.42 56.56

Inflorescence length (cm) 0.84–6.47 1.750 1.73 0.018 50.12 49.85 98.92 102.08

Inflorescence/plant 11.67–141.55 1824.32 1744.54 79.78 48.20 47.14 95.63 94.98

Seed size (mm) 1.34–2.21 0.053 0.045 0.008 12.53 11.49 84.90 21.88

1000 seed weight (g) 0.78–4.09 0.759 0.732 0.027 32.39 31.80 96.44 64.34

Dry weight/plant (g) 1.11–52.89 150.63 144.03 6.60 74.95 73.29 95.62 147.68

Harvest index 0.26–1.43 0.106 0.105 0.001 32.15 32.05 99.42 65.84

Seed yield (t/ha) 0.32–9.83 7.71 7.68 0.032 68.33 68.19 99.59 140.19

Total chlorophyll (mg/g) 0.55–2.04 0.122 0.109 0.013 24.48 23.15 89.34 44.95

Leaf carotenoid (mg/kg) 230.23–669.56 10452.16 9441.26 1010.90 21.11 20.07 90.33 39.29

Seed carotenoid (mg/kg) 1.69–5.52 0.833 0.813 0.020 32.18 31.78 97.60 64.84

Seed protein (%) 12.55–21.02 6.73 6.68 0.052 15.98 15.92 99.23 32.69

s2p: phenotypic variance; s2g: genotypic variance; s2e: environmental variance; PCV: phenotypic coefficient of variation; GCV: genotypic coefficient of variation.

A. Bhargava et al. / Field Crops Research 101 (2007) 104–116110

the 16 traits studied, dry weight/plant, seed yield and

inflorescence length recorded high coefficient of variation

values. Broad sense heritability was high and exceeded 80% for

all the traits. Genetic gain as percent of mean was highest for seed

yield (140.19%), followed by dry weight/plant (133.62%) and

inflorescence length (102.08%). Seed protein showed lowest

genetic gain among quality traits (32.69%) while for morpho-

logical traits the lowest value was for days to flowering (15.65%).

3.2. Correlation studies

The genotypic and phenotypic correlation coefficients

between various traits are presented in Table 7. The genotypic

correlation values were slightly higher than their corresponding

phenotypic values, which might be due to the modified effect of

environment on character association at the genetic level. All

morphological traits except days to flowering, days to maturity

and inflorescence length exhibited significant positive associa-

tion with seed yield, the maximum value was recorded for

inflorescence/plant. Among the quality traits, total chlorophyll

showed maximum correlation with seed yield both at

phenotypic and genotypic levels (0.499** and 0.509**,

respectively). Traits like days to flowering, days to maturity,

plant height, leaf area, primary branches/plant, inflorescence/

plant and dry weight/plant showed positive association amongst

themselves, which were highly significant. The association of

leaf area with all the traits except harvest index and seed protein

was positive. Seed size was negatively correlated with all the

morphological traits except for leaf area, 1000 seed weight,

harvest index and seed yield. The association of leaf carotenoid

with total chlorophyll and seed carotenoid was positive and

highly significant. Leaf carotenoid also showed positive

correlation with all morphological traits except seed size. An

interesting observation relates to the negative association

exhibited by seed protein with 13 traits. Of these the

relationship with days to maturity, plant height, leaf area,

inflorescence length and dry weight/plant were significant,

while harvest index was the only trait exhibiting significant

positive association with seed protein. Both seed carotenoid and

seed protein were negatively correlated with seed yield, though

the values were non-significant (Table 7).

3.3. Path analysis

In the present study, path coefficient analysis has been

conducted taking harvest index and seed yield as dependent

variables. The direct and indirect effects of various traits on

seed yield are provided in Table 8. The path analysis revealed

that 1000 seed weight had highest positive direct relationship

with seed yield (1.057), followed by total chlorophyll (0.559)

and branches/plant (0.520). Some traits showing high negative

direct effect were leaf carotenoid (�0.749), seed size (�0.678)

and days to flowering (�0.377). Days to flowering exerted

negative indirect influence on seed yield via all the

morphological traits except seed size and harvest index.

Likewise, leaf area also negatively indirectly influenced seed

yield through most of the morphological traits except plant

height and harvest index. Among the quality traits, seed protein

showed negative indirect effect on seed yield through all the

traits barring harvest index and seed carotenoid, though the

values of indirect effects were small.

The direct and indirect effects of various characters on

harvest index are given in Table 9. Total chlorophyll exerted

strongest direct positive effect (0.722) on harvest index,

followed by seed yield (0.505) and seed protein (0.245). Seed

yield also indirectly and positively influenced harvest index

through all the traits except leaf and seed carotenoid. Highest

negative direct was exhibited by leaf carotenoid (�1.118), dry

weight/plant (�0.638) and days to maturity (�0.058). Seed

protein and dry weight/plant negatively indirectly influenced

harvest index through all the morphological traits while

inflorescence/plant and leaf carotenoid were the other traits

exercising negative influence on harvest index through majority

of other traits. Plant height and leaf area showed positive direct

Table 7

Genotypic and phenotypic correlation coefficients among 16 traits in Chenopodium

Traits Days to

flowering

Days to

maturity

Plant

height

(cm)

Leaf

area

(cm2)

Branches/

plant

Inflorescence

length (cm)

Inflorescence/

plant

Seed

size

(mm)

1000 seed

weight (gm)

Dry weight

/plant (g)

Harvest

index

Total

chlorophyll

(mg/g)

Leaf

carotenoid

(mg/kg)

Seed

caro-enoid

(mg/kg)

Seed

protein

(%)

Seed yield/plant (g) G 0.201 0.178 0.507** 0.433** 0.417** 0.154 0.613** 0.277* 0.491** 0.486** 0.267* 0.509** 0.506** �0.007 �0.018

P 0.199 0.177 0.504** 0.428** 0.413** 0.153 0.607** 0.267* 0.485** 0.480** 0.267* 0.499** 0.498** �0.006 �0.017

Days to flowering G 0.712** 0.492** 0.339** 0.474** 0.246 0.331** �0.062 0.119 0.389** �0.070 �0.146 0.100 0.129 �0.237

P 0.702** 0.488** 0.332* 0.467** 0.244 0.325* �0.056 0.114 0.384** �0.069 �0.138 0.103 0.128 �0.236

Days to maturity G 0.611** 0.310* 0.596** 0.522** 0.481** �0.356** �0.226 0.542** �0.381** �0.042 0.309* 0.369** �0.296*

P 0.608** 0.305* 0.590** 0.520** 0.478** �0.343* �0.224 0.536** �0.378** �0.043 0.300* 0.367** �0.293*

Plant height (cm) G 0.503** 0.849** 0.484** 0.719** �0.104 0.035 0.825** �0.410** 0.356** 0.669** 0.298* �0.382**

P 0.498** 0.843** 0.483** 0.714** �0.102 0.036 0.821** �0.409** 0.348** 0.657** 0.295* �0.380**

Leaf area (cm2) G 0.304* 0.169 0.422** 0.254* 0.504** 0.402** �0.022 0.533** 0.618** 0.142 �0.379**

P 0.301* 0.166 0.414** 0.241 0.498** 0.395** �0.022 0.526** 0.604** 0.137 �0.375**

Branches/plant G 0.606** 0.644** �0.165 �0.143 0.663** �0.367** 0.096 0.515** 0.442** �0.223

P 0.600** 0.640** �0.161 �0.143 0.655** �0.362** 0.101 0.507** 0.435** �0.221

Inflorescence length (cm) G 0.203 �0.199 �0.264* 0.272* �0.248 �0.047 0.304* 0.388** �0.266*

P 0.205 �0.190 �0.261* 0.273* �0.247 �0.046 0.299* 0.386** �0.265*

Inflorescence/plant G �0.003 0.158 0.706** � 0.237 0.591** 0.718** 0.242 �0.159

P 0.002 0.155 0.699** � 0.234 0.580** 0.703** 0.238 �0.157

Seed size G (mm) G 0.849** �0.086 0.423** 0.131 �0.044 �0.169 �0.012

P 0.817** �0.079 0.408** 0.127 �0.039 �0.164 �0.011

1000 seed weight (g) G 0.037 0.426** 0.396** 0.205 �0.231 �0.115

P 0.041 0.420** 0.386** 0.199 �0.229 �0.114

Dry weight/plant (g) G �0.516** 0.299* 0.501** �0.015 �0.433**

P �0.513** 0.302* 0.498** �0.017 �0.429**

Harvest index P G �0.018 �0.271* �0.171 0.500**

P �0.017 �0.264* �0.169 0.498**

Total chlorophyll (mg/g) G 0.865** 0.242 �0.076

P 0.862** 0.236 �0.075

Leaf carotenoid (mg/kg) G 0.508** �0.228

P 0.496** �0.225

Seed carotenoid (mg/kg) G 0.066

P 0.067

G: genotypic correlation coefficient; P: phenotypic correlation coefficient. *P = 0.05, **P = 0.01.

A.

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(20

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1

Table 8

Path coefficient analysis showing direct (in bold) and indirect effects of 15 traits over seed yield in Chenopodium

Traits Days to

flowering

Days to

maturity

Plant

height

(cm)

Leaf

area

(cm2)

Branches/

plant

Inflorescence

length (cm)

Inflorescence/

plant

Seed

size

(mm)

1000 seed

weight (g)

Dry weight/

plant (g)

Harvest

index

T l

ch rophyll

(m /g)

Leaf

carotenoid

(mg/kg)

Seed

carotenoid

(mg/kg)

Seed

protein

(%)

Genotypic

Correlation

Days to flowering �0.377 0.089 0.020 �0.037 0.242 0.049 0.042 0.042 0.126 0.187 �0.031 � 082 �0.075 0.017 �0.010 0.201

Days to maturity �0.254 0.125 0.009 �0.034 0.305 0.104 0.061 0.241 �0.248 0.260 �0.170 � 023 �0.232 0.048 �0.012 0.178

Plant height (cm) �0.176 0.076 0.031 0.086 0.434 0.097 0.091 0.071 0.037 0.396 �0.183 198 �0.501 0.038 �0.016 0.507**

Leaf area (cm2) �0.121 0.039 �0.001 �0.109 0.157 0.034 0.053 �0.172 0.533 0.193 �0.010 298 �0.463 0.018 �0.016 0.433**

Branches/plant �0.169 0.074 �0.008 �0.033 0.520 0.121 0.082 0.111 �0.151 0.319 �0.164 054 �0.385 0.057 �0.009 0.417**

Inflorescence length (cm) �0.088 0.065 0.032 �0.050 0.310 0.200 0.026 0.135 �0.279 0.131 �0.111 � 026 �0.228 0.050 �0.011 0.155

Inflorescence/plant �0.128 0.060 0.010 �0.046 0.330 0.041 0.127 0.002 0.167 0.339 �0.106 330 �0.538 0.031 �0.006 0.613**

Seed size (mm) 0.022 �0.044 0.023 �0.028 �0.084 �0.040 �0.001 �0.678 0.875 �0.041 0.189 073 0.033 �0.022 �0.001 0.277*

1000 seed weight (g) �0.043 �0.028 �0.006 �0.055 �0.073 �0.053 0.020 �0.570 1.057 0.018 0.191 221 �0.153 �0.030 �0.005 0.491**

Dry weight/plant (g) �0.139 0.068 0.019 �0.044 0.320 0.054 0.089 0.058 0.039 0.481 �0.231 167 �0.375 �0.002 �0.018 0.486**

Harvest index 0.025 �0.047 0.040 0.002 �0.188 �0.049 �0.030 �0.286 0.450 �0.248 0.408 � 010 0.203 �0.022 0.021 0.267**

Total chlorophyll (mg/g) 0.052 �0.005 0.001 �0.058 0.048 �0.009 0.075 �0.089 0.419 0.144 �0.008 559 �0.647 0.031 �0.003 0.509**

Leaf carotenoid (mg/kg) �0.036 0.039 0.022 0.068 0.263 0.061 0.091 0.030 0.216 0.241 �0.121 461 �0.749 0.066 �0.009 0.506**

Seed carotenoid (mg/kg) �0.046 0.046 0.007 �0.016 0.219 0.077 0.031 0.115 �0.244 �0.007 �0.076 135 �0.380 0.129 0.003 �0.007

Seed protein (%) 0.085 �0.037 0.010 0.041 �0.114 �0.053 �0.020 0.008 �0.121 �0.208 0.214 � 043 0.170 0.009 0.042 �0.018

*P = 0.05; **P = 0.01.

Table 9

Path coefficient analysis showing direct (in bold) and indirect effects of 15 traits over harvest index in Chenopodium

Traits Days to

flowering

Days to

maturity

Plant

height

(cm)

Leaf

area

(cm2)

Branches/

plant

Inflorescence

length (cm)

Inflorescence/

plant

Seed size

(mm)

1000 seed

weight (gm)

Dry weight/

plant (g)

Total

chlorophy

(mg/g)

Leaf

carotenoid

(mg/kg)

Seed

carotenoid

(mg/kg)

Seed

protein

(%)

Seed

Yield

(t/ha)

Genotypic

Correlation

Days to flowering 0.169 �0.041 0.074 0.073 0.046 0.026 �0.004 �0.003 0.005 �0.248 �0.106 �0.112 0.008 �0.058 0.102 �0.070

Days to maturity 0.120 �0.058 0.092 0.067 0.058 0.056 �0.006 �0.019 �0.009 �0.346 �0.030 �0.346 0.022 �0.072 0.090 �0.381**

Plant height (cm) 0.083 �0.035 0.151 0.108 0.083 0.052 �0.010 �0.006 0.001 �0.526 0.255 �0.747 0.018 �0.093 0.256 �0.410**

Leaf area (cm2) 0.057 �0.018 0.076 0.215 0.030 0.018 �0.006 0.013 0.020 �0.256 0.385 �0.691 0.009 �0.093 0.219 �0.022

Branches/plant 0.080 �0.035 0.128 0.066 0.098 0.065 �0.009 �0.009 �0.006 �0.423 0.069 �0.575 0.027 �0.055 0.211 �0.367**

Inflorescence length (cm) 0.042 �0.030 0.073 0.036 0.059 0.107 �0.003 �0.010 �0.010 �0.174 �0.034 �0.340 0.023 �0.065 0.078 �0.248

Inflorescence/plant 0.056 �0.028 0.108 0.091 0.063 0.022 �0.013 �0.001 0.006 �0.450 0.426 �0.802 0.015 �0.039 0.309 �0.237

Seed size (mm) �0.010 0.021 �0.016 0.054 �0.016 �0.021 0.003 0.049 0.033 0.055 0.095 0.049 �0.010 �0.003 0.140 0.423**

1000 seed weight (g) 0.020 0.013 0.005 0.108 �0.014 �0.028 �0.002 0.045 0.039 �0.023 0.286 �0.229 �0.014 �0.028 0.248 0.426**

Dry weight/plant (g) 0.066 �0.031 0.124 0.086 0.065 0.029 �0.009 �0.004 0.001 �0.638 0.216 �0.560 �0.001 �0.106 0.246 �0.516**

Harvest index �0.025 0.002 0.053 0.114 0.009 �0.005 �0.007 0.007 0.015 �0.191 0.722 �0.966 0.015 �0.019 0.257 �0.018

Total chlorophyll (mg/g) 0.017 �0.018 0.101 0.133 0.050 0.032 �0.010 �0.002 0.008 �0.319 0.624 �1.118 0.031 �0.056 0.256 �0.271*

Leaf carotenoid (mg/kg) 0.022 �0.021 0.045 0.031 0.043 0.041 �0.003 �0.009 �0.009 0.010 0.175 �0.568 0.061 0.016 �0.004 �0.171

Seed carotenoid (mg/kg) �0.040 0.017 �0.058 �0.081 �0.022 �0.028 0.002 �0.001 �0.004 0.276 �0.055 0.254 0.004 0.245 �0.009 0.500**

Seed protein (%) 0.034 �0.010 0.076 0.093 0.041 0.016 �0.008 0.015 0.019 �0.310 0.367 �0.566 �0.001 �0.004 0.505 0.267*

*P = 0.05; **P = 0.01.

A.

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0.

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0.

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0.

0.

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0.

0.

ll

A. Bhargava et al. / Field Crops Research 101 (2007) 104–116 113

path and indirectly and positively influenced harvest index

through most of the traits.

4. Discussion

Quinoa is considered a crop adapted to diverse habitats with

tremendous potential for diversification of agricultural

systems in mountainous regions of the developing world such

as the Himalayas and the central mountain region of Africa

(Jacobsen, 2001; Jacobsen and Risi, 2001). Quinoa has

generated increased interest among farmers, agro-industries

and researchers in its native region as well as in North America

and Europe. Demand for quinoa has increased considerably

during recent years but the supply of quinoa from South

American countries is insufficient which necessitates its

introduction outside the Andean region. Some new sites have

been identified in the American and European Test of quinoa,

organized by the FAO. Field trials in Italy and Greece have

shown promising results with reported grain yield of 2280 and

3960 kg/ha, respectively (Mujica et al., 2001). Our results

show that quinoa could serve as an alternative winter crop for

the North Indian Plains and other subtropical regions having

similar agro-climatic and edaphic conditions. A thorough

assessment of yield potential of all the germplasm lines under

study for two consecutive years clearly shows that 41% of the

lines were high yielding. This reflects greater adaptability of

some quinoa lines to North Indian agro climatic conditions,

especially of the Chilean and U.S. ones. It was noticed that

variability was not related to geographical origin. This is

exemplified by the Bolivian lines, two of which (C. quinoa PI

614938 and PI 478408) were the lowest yielding and also

recorded low values for most of the traits. However, high seed

yield along with above average mean performance for most

morphological traits were observed in two other Bolivian lines

namely, C. quinoa PI 478414 and C. quinoa Ames 21909. This

extreme variation in seed yield witnessed in C. quinoa PI

478408 and C. quinoa PI 478414, which were collected from

the same location (La Paz, Bolivia), could be due to genetic

factors and points towards wide genetic variation present in the

lines having the same origin. Such differences also exist in C.

quinoa PI 510536 and C. quinoa PI 510537 whose origin are

the same but yield varies by more than six times. One

interesting observation was that some lines collected from high

elevations (C. quinoa PI 478414, C. quinoa PI 596498, C.

quinoa PI 478410 and C. quinoa Ames 21909) gave

considerably good seed yield at 120 m altitude of the

experimental site. The present results further support earlier

reports (Jacobsen, 2003) that quinoa is adapted to areas ranging

from sea level to high altitudes. In our study, the US and

Chilean lines, and one line each from Argentina (PI 614881)

and Bolivia (PI 478414) seem to be adaptable and more suited

to subtropical North Indian conditions as they gave consis-

tently high yield, while both lines of C. berlandieri subsp.

nuttalliae of Mexican origin were poor in terms of yield.

Jacobsen and Stolen (1993) and Jacobsen (2003) reported that

Chilean lines have low sensitivity to photoperiod, thus

conferring greater stability to them. Our study confirms that

the Chilean lines are more suited for diversification of quinoa

in newer areas. These results indicate ample scope for quinoa

in furthering agricultural diversification in countries having

monsoon climate like India that have markedly cold winters

and hot summers.

The 29 accessions evaluated had an average pre-flowering

growth period of about 82 days and took around 48 days for

grain maturity. The total growth period in North Indian

conditions is less than that reported in South America (110–190

days) (Jacobsen and Stolen, 1993) and is similar to that reported

in northern Europe (Jacobsen, 1998). The total growth period of

quinoa at the experimental site is quite low in comparison to the

generally recommended <150 days growing period of quinoa

(Jacobsen, 2003). The non-significant correlation with grain

yield and low direct and indirect effects shown by days to

flowering and days to maturity suggests that these two

components are influencing yield to a lesser extent and are

of not much significance in North Indian conditions. Days to

maturity was negatively, though non-significantly related with

total chlorophyll content which was possibly due to gradual rise

in temperature and drop in humidity as the season progressed,

which leads to degradation of leaf pigments and the enzyme

RuBisCo (Garcia del Moral et al., 1995; Fernandez-Figares

et al., 2000; Bhargava et al., 2006b). The low yielding

accessions generally had below average values for most of the

morphological traits and vice versa. This is also corroborated

by correlation analysis where all the morphological traits

showed positive association with seed yield that was significant

for most of the traits. Thus, different morphological traits seem

to positively influence yield to a great extent.

An interesting observation was made with regard to

association between days to maturity and seed size, which

was negative and highly significant, thereby indicating a

negative impact of maturity period on seed size. Our results are

similar to that obtained by Bertero et al. (1999) who reported

that temperature and photoperiod after anthesis affects seed

diameter to a considerable extent in quinoa. Short photoperiod

and cool temperatures after anthesis promote seed diameter,

while long photoperiods and high temperature after anthesis

negatively affect leaf size (Bertero et al., 1999). Our findings

support their results as flowering at the experimental location

occurred at the beginning of February, the same time when

winter ends. Later on, there is a constant rise in temperature and

day length, which progresses till June when the maximum

temperatures reach about 45 8C. In our experiment, the control

conditions of Bertero et al. (1999) were created naturally as

after anthesis the temperature and photoperiod increased which

had a negative impact on seed size. Thus, in North India, sowing

of quinoa should be done at the onset of winter so that by the

time summer approaches, seed formation and development is

complete. A strong positive association existed between seed

size and 1000 seed weight, which is on expected lines, as a large

seed would naturally have more weight than a smaller one.

Highly significant correlations between seed diameter and seed

weight have also been determined earlier in quinoa by Ochoa

and Peralta (1988), Cayoja (1996) and Rojas et al. (2003). Most

of the accessions having above average seed size also had very

A. Bhargava et al. / Field Crops Research 101 (2007) 104–116114

high 1000 seed weight which support the results obtained

through correlation.

Among other morphological variables, significant association

among branches/plant, inflorescence length and inflorescence/

plant indicates that plants with good branching habit tend to

develop large number of long inflorescences. Inflorescence

length also correlated positively with plant height indicating that

lines with greater plant height also developed longer panicles, a

fact also reported by Rojas et al. (2003) and Ochoa and Peralta

(1988).

Biomass accumulation and partitioning to reproductive

structures are key determinants of crop yield (Andrade et al.,

1999). Reproductive partitioning is the proportion of total

biomass allocated to reproductive tissues (Hay, 1995; Sinclair,

1998). The productive capacity of any crop plant depends, not

only on its photosynthetic efficiency, but also on the effective

translocation of assimilates to the seeds, which is measured by

the harvest index. This partitioning between vegetative and

reproductive parts can be modified by agronomic practices such

as sowing density, fertilization, irrigation and choice of sowing

date. In the present study, harvest index presented tremendous

variability and ranged from 0.26 to 1.43, the highest value being

approximately six times the lowest value. However, this range

is quite narrow as compared to the report of Rojas et al. (2003)

who reported harvest index in quinoa in the range of 0.06–0.87,

a difference of almost 15 times. The harvest index values in the

present study are a bit high which might be due to the fact that

the plants were cut about 6 cm above the ground and the dry

weight excluded the weight of secondary branches and leaves.

The inclusion of the above mentioned plant parts in dry weight

would in most probability lower the harvest index below 1.00.

However, still the harvest index values are pretty high and point

towards high efficiency of reproductive partitioning in quinoa.

Donald (1963) has reported that early sowing, when combined

with good conditions and a long growing season leads to severe

inter-plant competition and low harvest index. However, our

results show no inverse relationship between harvest index and

long growing season. Therefore, the variations of sowing date

and good growing conditions vis-a-vis harvest index in quinoa

needs detailed examination. In the present study, days to

flowering showed positive association with dry weight/plant but

none with harvest index. Days to maturity showed strong

positive association with dry weight/plant and negative

correlation with harvest index, while both dry weight/plant

and harvest index were negatively correlated between

themselves. Thus, it seems that in the late maturing lines, as

season progressed the dry weight increased but there was much

less partitioning of the assimilated product to reproductive parts

in comparison to the vegetative parts.

The present study gave some interesting results with

reference to quality traits. A large amount of variation was

found with respect to quality traits studied. Earlier, Prakash

et al. (1993) have reported significant differences within

quinoa germplasm and suggested their use in breeding of

nutritionally superior lines. Carotenoids play an important role

in human nutrition as the whole vitamin A comes through diet

and many carotenoids have been identified as precursors to

vitamin A while others have been shown to function as

antioxidants (de Pee and West, 1996; Rock, 1997; Pavia and

Russel, 1999). The leaf carotenoid content was higher than that

reported for spinach, amaranth and Chenopodium album

(Gupta and Wagle, 1988; Prakash and Pal, 1991; Shukla et al.,

2003; Bhargava et al., 2006b, in press). The overall mean for

seed carotenoid content was lower in comparison to earlier

reports (Koziol, 1992). The total seed protein content

corroborates earlier reports by Koziol (1992), Wright et al.

(2002) and Repo-Carrasco et al. (2003). The protein content in

quinoa is quite high in comparison to commonly used cereals

and compares favourably with other underutilized crops like

Amaranthus (Bressani et al., 1987; Shukla et al., 2004, 2005),

Fagopyrum (Steadman et al., 2001) and even some under-

utilized legumes like Cassia floribunda (Vadivel and Janard-

hanan, 2001). The high seed protein in quinoa indicates its

potential as a low cost protein source to eliminate protein

malnutrition in developing countries where low incomes

restricts the use of meat and pulses by the bulk of the

population. There is an urgent need for obtaining high quality

protein concentrates to solve the problem of chronic

malnutrition affecting urban and rural populations in the

developing countries. The embryo, after separation from the

seed, can be utilized in food for malnutrited children and for

pregnant and breast-feeding women. C. quinoa PI 510537 was

nutritionally superior, having high protein and carotenoid

content coupled with high seed yield. Three germplasm lines of

C. quinoa namely CHEN 67/78, CHEN 71/78 and PI 478414

had high carotenoid (both leaf and seed) and protein content

but had low seed yield and thus could be used as donor parents

for quality improvement.

Although top three high yielding accessions had an above

average protein, but this relationship does not hold good for other

high yielding accessions, which had low protein, therefore,

showing insignificant correlation between yield and protein

content, which is contrary to the generally accepted view that

increase in protein content is made at the expense of yield (Jenner

et al., 1991; Pleijel et al., 1999). The non-significant correlation

between seed yield and seed quality traits and low values of direct

path are beneficial since it would not hinder attempts to breed

lines with both greater grain yield and high seed protein and

carotenoid. The seed quality traits in quinoa are reported to be

negatively influenced by cold stress and humid autumn weather

in high altitude and/or high latitude locations (Jacobsen, 2003).

Our results show that at low elevations and low latitude, seed

quality traits show no association with duration of growth. This

would enable cultivation of quinoa in the tropics and at lower

elevations without in any deteriorating the quality of the grain.

Protein content is also negatively and indirectly affected by yield

through most of the traits, morphological as well as quality. Seed

carotenoid seems to be correlated with seed coat colour as six out

of the seven dark coloured accessions had high seed carotenoid.

Such an association between coat colour and carotenoid content

has also been reported in transgenic rice (Datta et al., 2003).

Variability plays an important role in any crop-breeding

program and determines the limit of selection for yield

improvement. The relative amount of genotypic variation is

A. Bhargava et al. / Field Crops Research 101 (2007) 104–116 115

best expressed as the genotypic coefficient of variation (GCV),

since this variable takes into account the mean value as well as

the unit of measurement into consideration. The high GCV for

seed yield supports the view that reproductive characters in

general are more variable than vegetative ones (Sachs and

Coulman, 1983). The heritability values for most of the traits

were high suggesting that these traits are under genotypic

control. Such high heritability values for various traits have also

been reported in vegetable chenopods (C. album) (Bhargava

et al., 2003b, 2006b). However, estimation of heritability is of

little significance in coherent selection breeding programs

unless accompanied by sufficient genetic gain (Johnson et al.,

1955b). Due to large differences in the phenotypic variation

between different traits, genetic advance is not directly related

to heritability values. In the present study, moderate to high

genetic gain values for most of the traits indicate that

improvement could be made in the aforesaid characters. The

genetic advance for some traits were high because of extreme

variation in the material investigated, and smaller values for

genetic advance are expected in further selection cycles in a

more improved material. Among the various traits, 1000 seed

weight, branches/plant, dry weight and total chlorophyll

influenced seed yield to a considerable extent by exhibiting

strong positive correlation with seed yield coupled with high

positive path and indirect influence through most of the traits.

This indicates scope for improvement in seed yield by proper

selection pressure. These traits also showed moderate to high

coefficient of variation, heritability and genetic gain values that

amply demonstrate the utility of these traits in selection

programmes in quinoa. Seed yield and seed protein were the

only traits exhibiting high positive direct path and significant

positive association with harvest index, indicating a true

relationship among these traits. Leaf carotenoid and dry

weight/plant had negative direct effect on harvest index, showed

negative significant correlation and indirectly influenced harvest

index through majority of the traits, indicating actual relationship

and suggesting that selection of plants having less dry weight and

low leaf carotenoid would likely bring improvement in harvest

index. Total chlorophyll had high positive direct effect but

exhibited non-significant negative correlation with harvest index

due to presence of strong indirect effect via leaf carotenoid. Thus,

the ideotype to increase harvest index in quinoa should have high

seed yield and low dry weight/plant. The study of path analysis

also indicated that there were no common causal factors that

directly influenced both seed yield and harvest index.

Acknowledgements

The authors are thankful to the Director N.B.R.I, Lucknow

for providing the facilities and constant encouragement to carry

out the present investigation. Atul Bhargava acknowledges

C.S.I.R., New Delhi for providing financial assistance.

Appendix A. Supplementary data

Supplementary data associated with this article can be

found, in the online version, at doi:10.1016/j.fcr.2006.10.001.

References

Aggarwal, P.K., Joshi, P.K., Ingram, J.S.I., Gupta, R.K., 2004. Adapting food

systems of the Indo-Gangetic plains to global environmental change: key

information needs to improve policy formulation. Environ. Sci. Pol. 7, 487–

498.

Aguilar, P.C., Jacobsen, S.E., 2003. Cultivation of quinoa on the Peruvian

altiplano. Food Rev. Int. 19, 31–41.

Andrade, F.H., Vega, C.R.C., Uhart, S.A., Cirilo, A.G., Cantarero, M., Valenti-

nuz, O., 1999. Kernel number determination in maize. Crop Sci. 39, 453–459.

Bertero, H.D., King, R.W., Hall, A.J., 1999. Photoperiod-sensitive development

phases in quinoa (Chenopodium quinoa Willd.). Field Crops Res. 60, 231–

243.

Bertero, H.D., Vega de la, A.J., Correa, G., Jacobsen, S.E., Mujica, A., 2004.

Genotype and genotype-by-environment interaction effects for grain yield

and grain size of quinoa (Chenopodium quinoa Willd.) as revealed by

pattern analysis of international multi-environment trials. Field Crops Res.

89, 299–318.

Bhargava, A., Shukla, S., Katiyar, R.S., Ohri, D., 2003a. Selection parameters

for genetic improvement in Chenopodium grain on sodic soil. J. Appl.

Hortic. 5, 45–48.

Bhargava, A., Shukla, S., Ohri, D., 2003b. Genetic variability and heritability of

selected traits during different cuttings of vegetable Chenopodium. Ind. J.

Genet. Pl. Breed. 63, 359–360.

Bhargava, A., Shukla, S., Ohri, D., 2006a. Chenopodium quinoa—an Indian

perspective. Ind. Crops Prod. 23, 73–87.

Bhargava, A., Shukla, S., Dixit, B.S., Bannerji, R., Ohri, D., 2006b. Variability

and genotype x cutting interactions for different nutritional components in

C. album L. Hortic. Sci. 33, 29–38.

Bhargava, A., Shukla, S., Ohri, D., in press. Evaluation of foliage yield and leaf

quality traits in Chenopodium spp. in multiyear trials. Euphytica.

Bressani, R., Gonzales, J.M., Zuniga, J., Brauner, M., Elias, L.G., 1987. Yield,

selected composition and nutritive value of 14 selections of amaranth grain

representing four species. J. Sci. Food Agric. 38, 347–356.

Cayoja, M.R., 1996. Caracterizacion de variables continuas y discretas del

grano de quinua (Chenopodium quinoa Willd.) del germoplasma de la

Estacion Experimental Patacamaya Thesis Fac. Agron., Oruro, Bolivia

Univ. Tecnica.

Datta, K., Baisakh, N., Oliva, N., Torrizo, L., Abrigo, E., Tan, J., Rai, M.,

Rehana, S., Al-Babili, S., Beyer, P., Potrykus, I., Datta, S.K., 2003.

Bioengineered ‘golden’ indica rice cultivars with b-carotene metabolism

in the endosperm with hygromycin and mannose selection systems. Plant

Biotech. J. 1, 81–90.

de Pee, S., West, C.E., 1996. Dietary carotenoids and their role in combating

Vitamin A deficiency: a review of the literature. Eur. J. Clin. Nutr. 50, 538–

553.

Dewey, D.R., Lu, K.H., 1959. A correlation and path coefficient analysis of

components of crested wheat grass seed production. Agron. J. 51, 515–518.

Donald, C.M., 1963. Competition among crop and pasture plants. Adv. Agron.

15, 1–118.

Fernandez-Figares, I., Marinetto, J., Royo, C., Ramos, J.M., Garcia del Moral,

L.F., 2000. Amino-acid composition and protein and carbohydrate accu-

mulation in the grain of triticale grown under terminal water stress

simulated by a senescing agent. J. Cereal Sci. 32, 249–258.

Garcia del Moral, L.F., Boujenna, A., Yanez, J.A., Ramos, J.M., 1995. Forage

production, grain yield and protein content in dual-purpose triticale grown

for both grain and forage. Agron. J. 87, 902–908.

Garcia del Moral, L.F., Rharrabti, Y., Villegas, D., Royo, C., 2003. Evaluation of

grain yield and its components in durum wheat under Mediterranean

conditions: an ontogenic approach. Agron. J. 95, 266–274.

Gupta, K., Wagle, D.S., 1988. Nutritional and antinutritional factors of green

leafy vegetables. J. Agric. Food Chem. 36, 472–474.

Hay, R.K.M., 1995. Harvest index: a review of its use in plant breeding and crop

physiology. Ann. Appl. Biol. 126, 197–216.

Jacobsen, S.E., 1998. Developmental stability of quinoa under European

conditions. Ind. Crops Prod. 7, 169–174.

Jacobsen, S.E., 2001. El potencial de la quinua para Europa. In: Jacobsen, S.E.,

Portillo, Z. (Eds.), Memorias, Primer taller Internacional sobre Quinua-

A. Bhargava et al. / Field Crops Research 101 (2007) 104–116116

Recursos Geneticos y Sistemas de Produccion. Lima, Peru, UNALM, May

10–14, 1999, pp. 355–366.

Jacobsen, S.E., 2003. The worldwide potential of quinoa (Chenopodium quinoa

Willd.). Food Rev. Int. 19, 167–177.

Jacobsen, S.E., Risi, J., 2001. Distribucion geografica de la quinua fuera de los

paises Andinos. In: Mujica, A., Jacobsen, S.E., Izquierdo, J., Marathee, J.P.

(Eds.), Quinua (Chenopodium quinoa Willd.)—Ancestral Cultivo Andino,

Alimento del presente y futuro. FAO, UNA-Puno, CIP, Santiago, Chile, pp.

56–70.

Jacobsen, S.E., Stolen, O., 1993. Quinoa- morphology, phenology and prospects

for its production as a new crop in Europe. Eur. J. Agron. 2, 19–29.

Jacobsen, S.E., Mujica, A., Jensen, C.R., 2003. The resistance of quinoa

(Chenopodium quinoa Willd.) to adverse abiotic factors. Food Rev. Int.

19, 99–109.

Jenner, C.F., Uglade, T.D., Aspinall, D., 1991. The physiology of starch and

protein deposition in the endosperm of wheat. Aust. J. Pl. Physiol. 18, 211–

226.

Jensen, A., 1978. Chlorophylls and carotenoids. In: Hellebust, J.A., Craigie,

J.S. (Eds.), Handbook of Physiological Methods: Physiological and Bio-

chemical Methods. Cambridge University Press, Cambridge, pp. 5–70.

Jensen, C.R., Jacobsen, S.E., Andersen, M.N., Nunez, N., Andersen, S.D.,

Rasmussen, L., Mogensen, V.O., 2000. Leaf gas exchange and water

relation characteristics of field quinoa (Chenopodium quinoa Willd.) during

soil drying. Eur. J. Agron. 13, 11–25.

Johnson, H.W., Robinson, H.F., Comstock, R.E., 1955a. Genotypic and phe-

notypic correlation in soybean and their implication in selection. Agron. J.

47, 477–485.

Johnson, H.W., Robinson, H.F., Comstock, R.E., 1955b. Estimates of genetic

and environmental variability in soybean. Agron. J. 47, 314–318.

Joshi, P.K., Tyagi, N.K., 1994. Salt affected and water logged soils in India: a

review. In: Svendsen, M., Gulati, A. (Eds.), Strategic Change in Indian

Irrigation. ICAR/IFPRI, New Delhi, India/Washington, DC, USA, pp. 237–

252.

Koziol, M.J., 1992. Chemical composition and nutritional value of quinoa

(Chenopodium quinoa Willd.). J. Food Comp. Anal. 5, 35–68.

Mastebroek, H.D., Limburg, H., 1996. Breeding for harvest security in Che-

nopodium quinoa. Proceedings of the COST-Workshop., 22-24/2 1996

European Commission EUR 17473/KVL, Copenhagen, KVL, pp. 79–86.

Mujica, A., Jacobsen, S.E., Izquierdo, J., Marathee, J.P., 2001. Resultados de la

Prueba Americana y Europes de la Quinua. FAO, UNA-Puno, CIP, p. 51.

Ochoa, J., Peralta, E., 1988. Evaluacion preliminar morfologica y agronomica

de 153 entradas de quinua en Santa Catalina, Pichincha. Actas del VI

Congreso Internacional sobre Cultivos Andinos. Quito, Ecuador, pp. 137–

142.

Pavia, S.A., Russel, R.M., 1999. Beta-carotene and other carotenoids as

antioxidants. J. Am. Coll. Nutr. 18, 426–433.

Peterson, G.L., 1977. A simplification of the protein assay method of Lowry

et al., which is more generally applicable. Anal. Biochem. 83, 346–356.

Pleijel, H., Mortensen, L., Fuhrer, J., Ojanpera, K., Danielsson, H., 1999. Grain

protein accumulation in relation to grain yield of spring wheat (Triticum

aestivum L.) grown in open-top chambers with different concentrations of

ozone, carbon dioxide and water availability. Agric. Ecosyst. Environ. 72,

265–270.

Prakash, D., Pal, M., 1991. Nutritional and anti-nutritional composition of

vegetable and grain amaranth leaves. J. Sci. Food Agric. 57, 573–583.

Prakash, D., Nath, P., Pal, M., 1993. Composition, variation of nutritional

contents in leaves, seed protein, fat and fatty acid profile of Chenopodium

species. J. Sci. Food Agric. 62, 203–205.

Repo-Carrasco, R., Espinoza, C., Jacobsen, S.E., 2003. Nutritional value and

use of the Andean crops Quinoa (Chenopodium quinoa) and Kaniwa

(Chenopodium pallidicaule). Food Rev. Int. 19, 179–189.

Risi, J., Galwey, N.W., 1989. The pattern of genetic diversity in the Andean

grain crop quinoa (Chenopodium quinoa Willd.). I. Association between

characteristics. Euphytica 41, 147–162.

Rock, C.L., 1997. Carotenoids: biology and treatment. Pharmacol. Ther. 75,

185–197.

Rojas, W., Barriga, P., Figueroa, H., 2003. Multivariate analysis of genetic

diversity of Bolivian quinoa germplasm. Food Rev. Int. 19, 9–23.

Sachs, A.P.W., Coulman, B.E., 1983. Variability in reed canarygrass collections

from eastern Canada. Crop Sci. 23, 1041–1044.

Shukla, S., Pandey, V., Pachauri, G., Dixit, B.S., Bannerji, R., Singh, S.P., 2003.

Nutritional contents of different foliage cuttings of vegetable amaranth. Pl.

Foods Human Nutr. 58, 1–8.

Shukla, S., Bhargava, A., Chatterjee, A., Singh, S.P., 2004. Estimates of genetic

parameters to determine variability for foliage yield and its different

quantitative and qualitative traits in vegetable amaranth (A. tricolor). J.

Genet. Breed. 58, 169–176.

Shukla, S., Bhargava, A., Chatterjee, A., Srivastava, A., Singh, S.P., 2005.

Estimates of genetic variability in vegetable amaranth (A. tricolor) over

different cuttings. Hortic. Sci. 32, 60–67.

Sinclair, T.R., 1998. Historical changes in harvest index and crop nitrogen

accumulation. Crop Sci. 38, 638–643.

Singh, R.K., Chaudhary, B.D., 1985. Biometrical Methods in Quantitative

Genetic Analysis. Kalyani Publishers, New Delhi.

Steadman, K.J., Burgoon, M.S., Lewis, B.A., Edwardson, S.E., Obendorf, R.L.,

2001. Buckwheat seed milling fractions: description, macronutrient com-

position and dietary fibre. J. Cereal Sci. 33, 271–278.

Vacher, J.J., 1998. Responses of two main Andean crops, quinoa (Chenopodium

quinoa Willd.) and papa amarga (Solanum juzepczukii Buk.) to drought on

the Bolivian Altiplano: significance of local adaptation. Agric. Ecosyst.

Environ. 68, 99–108.

Vadivel, V., Janardhanan, K., 2001. Nutritional and anti-nutritional attributes of

the under-utilized legume, Cassia floribunda Cav. Food Chem. 73, 209–215.

Wright, K.H., Pike, O.A., Fairbanks, D.J., Huber, C.S., 2002. Composition of

Atriplex hortensis, sweet and bitter Chenopodium quinoa seeds. J. Food Sci.

67, 1383–1385.