Genotype x Environment (GxE) interaction studies in hybrids and elite cultivars of pigeonpea

Uttam Chand Research Scholar (M.Sc.) Pigeonpea Breeding ICRISAT, Patancheru

Contents…….

I. Introduction

II. Materials and methods

III. Results and discussion

IV. Conclusions

INTRODUCTION

Origin : India (van der Maesen 1980, 1991)

Hybrids available at commercial level like

ICPH 2671, ICPH 2740 etc.

Protein content : 18-24 %

Often cross pollinated crop (25-70%)

Genome size : 858 Mbp

Chromosome no. : 2n=22

Mostly use as “Dal”

Second most

important pulse crop of India

Area = 4.04 Million hectare Production = 2.65 Million tonnes (IIPR, 2013)

Productivity Global - 813 kg/ha India - 657 kg/ha

Area, production and productivity (India)

Source: IIPR, 2013

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

Area (m ha) Production (m t) Productivity(t/ha)

Importance of GxE interaction

Wide adaption and consistent performance of released varieties/hybrids

To identify the stable genotype in diverse environments

Yield stability of performance across varied environments

The phenotypic response to change in environment is not the same for all the genotypes leading to GxE interaction

Objectives

To determine the environmental influence on yield and yield characters of pigeonpea hybrids

To determine the flexibility in genotypes to the environment for stability of yield characters

To identify the hybrids and cultivars for stability of desirable yield and yield contributing characters

To identify the stable pigeonpea hybrid which can be used for cultivation over a wide range of environments

Experimental materials

Source : ICRISAT, Patancheru

CMS line (A4 cytoplasm)

ICPA 2043, ICPA 2047, ICPA 2048, ICPA 2078 and ICPA 2092

Fertility restorer line

ICPL 87119, ICPL 20093, ICPL 20096, ICPL 20098, ICPL 20108 and ICPL 20126

Experimental materials

Genotypes Pedigree Standard Maturity days

ICPH 3933 ICPA 2078 × ICPL 87119 180-190

ICPH 2671 ICPA 2043 × ICPL 87119 165-175

ICPH 2740 ICPA 2047 × ICPL 87119 180-185

ICPH 3477 ICPA 2047 × ICPL 20098 175-185

ICPH 4490 ICPA 2047 × ICPL 20126 165-175

ICPH 3494 ICPA 2048 × ICPL 20093 170-180

ICPH 2751 ICPA 2048 × ICPL 87119 165-180

ICPH 3491 ICPA 2048 × ICPL 20096 175-190

ICPH 3762 ICPA 2092 × ICPL 20108 171-184

ICPH 3461 ICPA 2092 × ICPL 87119 165-180

Maruti (check) Selection from ICP 7626 165-175

Asha (check) ICP 1-6W3×W1×x C11 175-180

Source : ICRISAT, Patancheru

Details of Three Environments

Particulars Environments

Location ICRISAT,

Patancheru B.A.U., Ranchi R.A.K. ,Sehore

Latitude 17o 53'N 23o17'N 23°12’ N

Longitude 78o 27'E 85o 19'E 77° 05’ E

Altitude 545.0 m 625.0 m 498.77m

Soil type Medium black Sandy soil Vertisol

Climatic zone Moderate

rainfall zone sub-tropical sub-tropical

Date of sowing 29/06/2012 11/07/2012 16/08/2012

Date of harvesting 4/01/2013 12/02/2013 4/02/2013

Observations recorded

Days to 50% flowering Days to 75% maturity Plant height (cm) Number of primary branches/plant Number of secondary branches/plant Number of pods/plant Number of seeds/pod Grain yield/plant (g) 100 seeds weight (g) Grain yield/plot (g) Grain yield (kg/ha)

Experimental details

Genotypes : 12

Locations : 03

Design : RCBD

Replication : 02

Row length (m) : 04

Row to row spacing (cm) : 75

Plant to plant spacing (cm): 50

No. of rows per plot : 06

Genotypes were grown in RCBD with two replications at three different locations.

Data were collected from five randomly

selected plants for different characters.

Data collection

Data obtained from the multi-location trials were analyzed using GenStat software.

Data analysis

Stability analysis

Regression method (Eberhart and Russell, 1966)

GGE Biplot method

(Yan et al., 2000)

Eberhart and Russel Model

The total variance is first divided into two components- genotypes and E+GxE.

The second component (E+GxE) is further sub-divided into three components viz. a) environments linear, b) g x e (linear) and c) pooled deviations .

The SS due to pooled deviation are further divided in to SS due to individual genotypes.

The Model consist of three parameters mean yield over locations or seasons, b) regression coefficient and c) deviation from regression.

Mean = high

Regression coefficient of unity (b=1),

Minimum deviation from the regression line (S2d=0).

Parameters for stable genotype

GGE biplot method

The GGE-biplot methodology consists of two concepts: biplot and GGE It is the graphical representation of the both genotypes mean as well as environments performance

More efficient stability method compare to regression method

It is latest and very effective tool for the stability analysis

Steps in GGE biplot analysis

I. Centering the data

II. Partitioning the singular value into genotype and environment scores for each of the principal components (PC1 and PC2).

III. Plotting the PC1 scores against the PC2 scores to generate a biplot

IV.Large PC1 score represents high yielding ability and small PC2 score represents high stability

Results

and

Discussion

Pooled analysis of variance (ANOVA)

Source of

variation

df Days to

50%

flowering

Days

to 75%

maturity

Plant

height

(cm)

Primary

branches

/plant

Secondary

branches

/plant

Genotype 11 8.62** 3.39** 480.71** 13.69** 12.46**

Environment 2 1.41* 18144.3* 2201.8** 30.80** 493.79**

G × E 22 1.75* 2.28* 322.74** 3.53* 7.14*

Error 33 1.21 1.00 83.24 2.56 2.61

Cont.. *, ** Significant at P≤ 0.05 and P≤0.01, respectively

Source of

variation

df Pods

/plant

Seeds/

pod

Grain

yield /

plant (g)

100

seed

weight

(g)

Grain yield

(kg/ha)

Genotype 11 15.05** 0.11** 774.82** 8.62** 327560.0**

Environment 2 353.09** 0.41** 384.54** 5.58** 763360.0**

G × E 22 5.09** 0.09** 45.34** 1.62 86227.0**

Error 33 1.00 0.02 9.21 0.15 23928.0

*, ** Significant at P≤ 0.05 and P≤0.01, respectively

Analysis of variance (ANOVA) by regression method

Source of variation

df Days to 50%

flowering

Days to 75%

maturity

Plant height (cm)

Primary branches

/plant

Secondary branches

/plant

Genotype 11 37.86** 1.69 425.36** 31.23** 27.35**

Environ.+

(G× E) 24 6.8 757.05 239.66 15.05 23.84

Environment

(linear) 1 14.22 18144.3** 2201.8** 176.45** 493.79**

G×E (linear) 11 25.58* 1.10 412.53** 28.36** 34.36**

Pooled

deviation 12 5.41* 1.10 99.44** 6.69* 4.46*

Pooled error 33 2.34 0.5 4.61 2.16 1.30

Cont.… *, ** Significant at P≤ 0.05 and P≤0.01, respectively

Source of variation

df Pods / plant

Seeds /pod

Grain yield

/plant (g)

100 seed weight

(g)

Grain yield

(kg/ha)

Genotype 11 17.69** 0.15* 387.41** 1.51** 163779.7**

Environ.+

(G × E) 24 7.57 0.06 36.80 0.34 71327.4

Environment

(linear) 1 353.0** 0.48** 384.53** 0.01 76335.1

G×E(linear) 11 15.36** 0.20* 175.20* 0.26 97589.0*

Pooled

deviation 12 3.23** 0.04* 26.70* 0.28 26251.5*

Pooled error 33 0.50 0.01 11.37 0.15 11963.9

*, ** Significant at P≤ 0.05 and P≤0.01, respectively

Stability parameters

Genotypes Days to 50% flowering Days to 75% maturity Plant Height (cm)

Mean Bi S2di mean bi S2di mean Bi S2di

ICPH 3933 117 0.88 -0.23 181.66 1.00 0.12 192.61 1.55 -0.55

ICPH 2671 120 0.98 0.03 185.50 0.97 -0.42 190.80 1.41 2.38

ICPH 2740 122 0.75 4.73 183.83 1.03 -0.49 193.18 1.31 -1.26

ICPH 3477 118 5.21* 2.23 187.33 1.00 -0.35 211.06 0.98 -1.29

ICPH 4490 123 -1.50 4.73 189.66 0.97 2.53* 206.26 1.51 -1.30

ICPH 3494 122 0.87 0.07 192.83 0.96 4.76** 200.70 -0.65 -0.99

ICPH 2751 120 0.37 2.23 187.16 1.02 -0.49 192.73 -0.45 -0.04

ICPH 3491 119 1.87 -6.23 186.33 1.01 -0.48 201.28 1.55 0.68

ICPH 3762 117 1.62 3.47 184.66 1.04 -0.28 197.65 1.17 -1.29

ICPH 3461 124 -1.87* 5.77 188.66 1.01 1.91 202.10 -0.31 26.69*

Maruti 117 1.52 -2.35 180.16 0.96 -0.33 186.36 2.54* 3.65

Asha 121 0.37 0.25 185.66 0.96 -0.43 178.41 1.33 10.39*

Mean 120 1.00 - 186.12 0.99 - 196.09 1.00 -

S.E.(m) ± 2.13 0.19 - 4.95 0.12 - 7.05 0.73 -

*, ** Significant at P≤ 0.05 and P≤0.01, respectively

Stability parameters

Genotypes

Primary branches /plant

Secondary branches/ plant Pods per plant

mean bi S2di mean bi S2di mean Bi S2di

ICPH 3933 21.40 1.85* -4.62 90.53 0.88 -0.55 255.38 0.90 -0.18

ICPH 2671 28.79 1.02 0.75 130.20 1.43 2.31 404.86 1.33 1.89

ICPH 2740 25.30 1.64 -8.62 106.56 1.01 -1.26 303.80 0.70 12.53**

ICPH 3477 24.00 1.36 3.88 95.66 0.93 -1.29 258.26 1.31 4.92**

ICPH 4490 22.80 0.97 1.10 97.21 0.93 -1.30 264.71 0.99 2.49

ICPH 3494 25.23 0.33 2.15 96.66 0.88 -0.09 223.61 0.95 -0.48

ICPH 2751 22.70 0.37 1.96 92.43 0.70 -0.04 281.28 1.22 -0.50

ICPH 3491 21.16 0.63 6.60 96.56 1.02 0.68 224.16 0.95 -0.21

ICPH 3762 24.28 1.30 2.60 90.28 0.80 -1.29 300.61 1.12 -0.05

ICPH 3461 25.81 0.32 -16.03* 112.56 1.48 26.69** 299.40 1.09 0.63

Maruti 18.04 0.96 7.92 91.90 0.85 3.65 230.80 0.62 -0.47

Asha 20.57 2.57 0.53 101.10 1.05 10.39** 224.43 0.77 0.10

Mean 23.34 0.99 - 100.14 1.00 - 272.61 0.99 -

S.E.(m) ± 1.35 0.28 - 5.26 0.32 - 17.15 0.35 -

Stability parameters

Genotypes Seeds/pod Grain yield/plant(g) Grain yield (kg/ha)

mean bi S2di mean bi S2di mean bi S2di

ICPH 3933 3.50 -0.43 -0.01 62.78 1.52 -3.62 1561.16 1.46 113660.1**

ICPH 2671 3.62 0.99 0.00 72.80 0.97 -10.44 1634.90 0.95 -9242.7

ICPH 2740 3.63 1.12 0.04 64.30 1.30 34.94 1674.08 1.22 -2249.0

ICPH 3477 3.55 0.33 0.14* 60.00 1.25 -2.31 1396.93 -0.25 -10256.6

ICPH 4490 3.54 0.60 -0.00 65.48 2.27* 68.89* 1629.46 0.91 6453.2

ICPH 3494 3.83 0.98 0.08* 49.29 0.86 0.90 1215.61 0.81 63648.0*

ICPH 2751 3.53 0.98 -0.00 63.77 0.01 0.45 1289.53 -0.08* -5078.3

ICPH 3491 3.93 0.99 -0.01 47.69 0.53 17.11 1328.55 1.36 -11955.9

ICPH 3762 3.50 0.93 -0.00 62.58 0.61 -70.52 1509.90 1.54 25249.1

ICPH 3461 3.58 1.57* 0.00 65.39 0.53 114.0* 1486.20 0.03 -11208.8

Maruti 3.66 3.57 0.01 37.17 0.72 -8.79 953.75 1.03 11372.2

Asha 3.47 -0.20 0.07* 39.11 0.57 -8.85 1050.66 0.08 1059.7

Mean 3.64 0.95 - 57.53 0.92 - 1394.23 1.00 -

S.E.(m) ± 0.40 0.14 - 5.65 0.91 - 114.56 0.64 -

*, ** Significant at P≤ 0.05 and P≤0.01, respectively

GGE biplot figures

Days to 50% flowering Days to maturity

GGE biplot figures

Plant height Primary branches/plant

GGE biplot figures

Secondary branches/plant Pods/plant

GGE biplot figures

Seeds/pod Grain yield/plant (g)

0

500

1000

1500

2000

Patancheru G

rain

yie

ld (

kg/h

a)

0

500

1000

1500

2000

2500 Ranchi

Gra

in y

ield

(kg

/ha)

0

500

1000

1500

2000Sehore

0.0

500.0

1000.0

1500.0

2000.0

Gra

in y

ield

(kg

/ha)

Pooled

Gra

in y

ield

(kg

/ha)

Standard heterosis over the checks

0.0

200.0

400.0

600.0

800.0

1000.0

1200.0

1400.0

1600.0

1800.0

Gra

in y

ield

(kg

/ha)

Standard heterosis over the checks

Genotypes

Stable Hybrids Traits Stable genotypes

Grain yield (kg/ha) ICPH 2671, ICPH 2740, ICPH 3762, ICPH 4490, ICPH 3491

Days to 50% flowering ICPH 2671, ICPH 3933, ICPH 3494,

Days to maturity ICPH 2671, ICPH 3933, ICPH 3762, ICPH 2740, ICPH 3477, ICPH 2751, ICPH 3491, ICPH 3461, Maruti and Asha

Plant height (cm) ICPH 2671, ICPH 3933, ICPH 2740, ICPH 3762 ICPH 3477, ICPH 4490, ICPH 3491,

Primary branches/plant ICPH 2671, ICPH 4490

Secondary

branches /plant ICPH 2740, ICPH 3477, ICPH 4490, ICPH 3494, ICPH 3491

Pods/plant ICPH 2671, ICPH 3933, ICPH 3762, ICPH 2751, ICPH 3461

Seeds/pod ICPH 2671, ICPH 2751, ICPH 3491, ICPH 3762

Grain yield /plant (g) ICPH 2671, ICPH 3933, ICPH 3762, ICPH 2740, ICPH 3477

Conclusions

In Ranchi, most of the hybrids showed high

yield compared to other two locations

Patancheru location was suitable for

early maturity than the other locations

Cont.…

Stable hybrids Yield traits

ICPH 2671 (8) grain yield (kg/ha), days to 50% flowering, days to 75% maturity, plant height, primary branches, pods/plant, seeds / pod, grain yield/plant

ICPH 2740, ICPH 3933 and ICPH 3762 (5)

grain yield (kg/ha), days to 75% maturity, plant height, pods/plant, grain yield/plant

Acknowledgements

Dr. K.B. Saxena & team, Pigeonpea Breeding, ICRISAT, Patancheru.

Dr. A. N. Tikle, R.A.K. College of Agriculture,

Sehore, R.V.S.K.V.V., Gwalior, (Madhya Pradesh). Dr. Abhishek Rathore & team, Biometrics,

department, ICRISAT, Patancheru. Dr. Rosana Mula & team, LSU, ICRISAT, Patancheru. Housing & Food serving Committee, ICRISAT,

Patancheru.

ICRISAT is a member of the CGIAR Consortium

Everything else can wait but not agriculture Thank you !