Advances in Agriculture
Volume 2019 (2019), Article ID 1398612, 6 pages
https://doi.org/10.1155/2019/1398612

Research Article

Field Pea (Pisum sativum L.) Variety Development for Moisture Deficit Areas of Eastern Amhara, Ethiopia

Yirga Kindie,¹ Aemiro Bezabih,² Wubeshet Beshir,¹ Zinabu Nigusie,¹ Zelalem Asemamaw,¹ Antenh Adem,³ Birke Tebabele,¹ Genet Kebede,¹ Tesfay Alemayehu,¹ and Fentaw Assres¹

¹Sekota Dryland Agricultural Research Center, P.O. Box 62, Sekota, Ethiopia
²Debre Birhan Agricultural Research Center, P.O. Box 112, Debre Birhan, Ethiopia
³Adet Agricultural Research Center, P.O. Box 8, Bahir Dar, Ethiopia

Correspondence should be addressed to Yirga Kindie; ykindie2007@gmail.com

Received 13 October 2018; Revised 10 February 2019; Accepted 6 March 2019; Published 24 March 2019

Academic Editor: Ayman Suleiman

Copyright © 2019 Yirga Kindie et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract.

Twelve field pea genotypes were evaluated in seven environments in Eastern Amhara in main production season (2010-2012). The objective of this trial was to identify stable and high yielding field pea genotype for production in Eastern Amhara. The trial was conducted using randomized complete block design with three replications. Combined analysis of variance for grain yield revealed that genotypes, environments, and genotype by environment interaction effect were highly significant (P ≤ 0.01). The environments, GEI, and genotypes were accounted for 77.47%, 13.83%, and 4.37%, of the total sum squares, respectively, indicating that field pea grain yield was significantly affected by the changes in the environment, followed by GEI and genotypic effect. The candidate genotype, EH-03-002, showed 14.42% and 44.87% yield advantage over the standard and local checks, respectively. Considering the seven environments data and field performance evaluation during the variety verification trial, the National Variety Releasing Committee has approved the official release of EH-03-002 with the vernacular name of “Yewaginesh” for moisture deficit areas of Wag Lasta and similar agroecologies.

1. Introduction

Field pea (Pisum sativum L.) is one self-pollinated diploid (2n=14) annual of the most important annual cool season pulse crop and is valued as high protein food [1]. It is widely grown in the cooler temperate zones and in the highlands of tropical regions of the world. The crop is cultivated in a wide range of soil types from light sandy loams to heavy clays but it does not tolerate to saline and waterlogged soil conditions [2]. The soil pH optimum is 5.5-6.5. Field pea is one of the most important pulse crops in Ethiopia which is produced for a long time in high- and mid-altitude areas by smallholder farmers. It covers an area of about 25147.69 hectares with an annual production volume of 21406364 kg [3]. Field pea is nutritious food staff when fully matures and they are valuable food legume, often being ground into flour and used extensively in the manufacture of soups. Fresh green peas are almost universally accepted as a nutritious vegetable [4].

Nutritionally, field peas contain all the essential amino acids and are rich in high-quality vegetable protein [5]. Therefore, this crop can substitute high protein containing animal meat products in the developing countries including Ethiopia. The crop has an important role in the highlands of Ethiopia by playing a significant role in soil fertility improvement occupying a unique position in cereal-based cropping systems [6]; the crop is considered environmentally friendly and economical feasible from soil improvement point of view. Despite its importance, the average national productivity (0.85 tha⁻¹) is very low [3]. It is below the potential as compared to the research findings that ranged from 0.82 tha⁻¹ to 4.6 tha⁻¹ in Ethiopia [7] and the higher yield reported about 7 tha⁻¹ to 8 tha⁻¹ in Europe (England and France) [8]. The major yield-limiting constraints in field pea production in Ethiopia are aphids, low yielding local varieties, lodging, diseases (ascochyta blight, powdery mildew), and pod shattering [9] (Yayis et al., 2014). Ethiopian field pea landraces showed lack of resistance gene for two major field pea insect pests, namely, pea aphid and pea weevil (Melaku et al., 2003). Kemal (2002) identified options for the control of field pea pests such as the use of mixed cropping, time of planting and fertilizer application, cultural control, and biological control. On the other hand, several studies revealed that there is valuable genetic variability in field pea collections for yield and yield-related traits [9, 10] which is a good opportunity for Ethiopian field pea researchers to exploit the genetic potential of the crop by integrating conventional with molecular techniques. In general, we believe that the current field pea research should be assisted by more efficient molecular tools to develop varieties that are resistant or tolerant to field pea insect pest.

In Ethiopia, in order to increase field pea productivity, more than 30 improved varieties have been developed and released by national and regional Agricultural Research Center of the country. Most of them are targeted to favourable and wide environments but they are not suited for diverse and challenging environments. In general genotype by environment (GxE) interaction affects the efficiency of crop improvement programs that may lead to complicates recommendation of varieties across divers’ environments. Therefore, information on the structure and nature of GxE interaction is particularly useful to breeders (Bridges, 1989; Yayis et al., 2014). However, there is limited information on the extent of GEI in Eastern Amhara in general and in Waghimra in particular. Hence, this trial was initiated with the following objectives:

(1)To determine and understand the effect of genotype, environment, and their interaction on grain yield of field pea.(2)To identify and release stable and high yielding field pea genotype for Wag Lasta and similar agroecologies of the country.

2. Materials and Methods

2.1. Genotypes, Testing Sites, and Experimental Design

Twelve field pea genotypes advanced from observation nursery and preliminary variety trials, together with local check and standard check (Agrit), were evaluated during the main cropping season for four convictive years (2010 to 2012) in two sites and each site and year were treated as a single environment. The trial was conducted using a randomized complete block design with 3 replications throughout the testing sites. Description of the testing sites is presented in Table 1. The trial was conducted on the plot size of 4m0.8m with four rows per plot throughout all trial sites and 1.5m between replication, 1m between plot, 20cm between rows, and 5cm between plant distances were maintained. A variety verification trial was conducted at both Lalibela and Aybera on the trial station and in seven farmers’ field during 2016/17 main production season.

Table 1: Description of the test environment.

Location
Years
Environment Code
Altitude
Annual rain fall
Soil Type

(m.a.s.l)

Aybera
2010, 2011, 2012 & 2013
E1, E2, E3 & E4
1850
789
vertisol and red sandy soil

Lalibela
2010, 2011 & 2012
E5, E6 & E7
2400
940
Black (vertisol) soil

2.2. Data Collection

Data on grain yield and yield-related traits were collected on plot and plant basis from each plot, respectively. Date of flowering and maturity were taken when each plot attained 50% flowering and 90% of the pod’s physiological maturity, respectively, and days were calculated beginning from the date of sowing. Data for plant height (cm), number of pods per plant, and number of seeds per pod were collected on the basis of five sample plants which were randomly taken from each plot and the average of five sample plants was used for analysis. Hundred seed weight (g) and grain yield (g) of each plot were measured on clean, dried seed and the measured grain yield value (g) has converted to kilogram per hectare for analysis. All agronomic practices were done as per the recommendation for field pea.

2.3. Data Analysis and Analysis of Variances

Data from individual environments and combined over seven locations were analyzed by using SAS (2009) software. The analysis of variance for grain yield and yield-related traits for each environment and over seven environments was analyzed by using randomized complete block design. The combined analysis of variance across the environment was done in order to determine the differences between genotypes across environments, among environments and their interaction. Bartlett’s test was used to assess the homogeneity of error variances prior to doing combine analysis over environments. Mean comparison using Duncan's Multiple Range Test (DMRT) was performed to explain the significant differences among means of genotypes and environments.

The combined analysis of variance across environments was done in order to determine differences between field pea genotypes across the environment, among the environment, and also to determine their interaction effect by using the following statistical model:

where is observed mean of the genotype (Gi) at the environments (Ej), μ is the general mean, , , and represent the effects of the genotype, environment, and genotype by environment interaction, respectively, R (E) is the effect of replications within environments, and is the average random error associated with the plot that receives the genotype in the environment.

ANOVA from Additive Main Effect and Multiplicative Interaction (AMMI) [11] was computed for grain yield by using Gen Stat software ( edition) that exhibited significant mean squares for genotype and genotype by environment interaction.

3. Results and Discussion

3.1. Analysis of Variance and Mean Performance of 12 Field Pea Genotypes

Analysis of variance for each environment showed a highly significant (p ≤ 0.01) variation for grain yield and yield-related traits among the tested field pea genotypes (Table 2). This indicated the presence of performance variation among the tested field pea genotypes for grain yield and yield-related traits across the testing environments. Likewise, Mulusew et al. [12] and Tamene et al. [7] in field pea and Mulusew et al. [13] in faba bean had reported significant variation for grain yield and most of the yield-related traits among the tested genotypes across testing environments.

Table 2: Mean grain yield (Kg ha⁻¹) of twelve field pea genotypes over seven environments (i.e., across two locations and four years).

Genotypes
Gen. Code
Environment Code
Gen. mean

E1
E2
E3
E4
E5
E6
E7

IFPI12712
G1
1941
1081
2273
2882
2115
1459
1351
1872

EH-03-001
G2
1483
976
2565
3125
1999
1475
825
1778

COLL-24/002-1
G3
2263
877
2703
3347
1966
950
1365
1924

EH-03-002
G4
2045
1183
2527
3361
2446
2082
2400
2292

EH-03-010
G5
1408
867
2597
3484
2757
1487
1220
1974

COLL-217/99-5
G6
1971
741
2329
2696
2633
1260
1263
1842

EH-99-009-8
G7
1317
621
2527
3120
2307
1443
1885
1889

IPF-4021
G8
1894
869
2267
2448
2409
1178
2230
1899

EH-03-018
G9
1751
791
2161
2830
1967
1778
1650
1847

EH-99-020-3
G10
1995
823
2446
2629
2545
1455
1243
1877

Agrit (ch)
G11
1487
1140
2580
3017
2218
1377
2202
2003

Local (ch)
G12
2037
623
1923
2855
2135
385
1120
1582

Env. Mean

1799
883
2408
2983
2291
1361
1563
1898

CV%

11.6
8.8
8.0
6.0
6.4
12.5
11.7
9.7

Duncan 5%

= significant at 1% probability level, = significant at 5% probability level, CV = coefficient of variation (%), Env. mean= environmental mean, Gen. Code = genotype code, and Gen. mean = genotypic mean.

As indicated in Table 2, the average environmental grain yield across genotypes varied from the lowest 621 kg ha⁻¹ at E2 (Aybera in 2011) to the highest at 3484 kg ha⁻¹ in E4 (Aybera in 2012). The highest yielding environment (E4) had 57.16% yield advantage over the environmental gran mean. Environments, E3 and E5, were the second and the third highest yielding environments with mean grain yield of 2408 and 2291 kg ha⁻¹, respectively.

The mean grain yield of field pea genotypes across seven environments ranged from 1582 kg ha⁻¹ for the local check to 2292 kg ha⁻¹ for G4 (EH-03-002) (Table 2). Moreover, performances of genotypes were not consistent across seven environments. For instance, at E2 (Aybera 2011) genotype EH-03-002, at E3 (Aybera in 2012) genotype COLL-24/002-1, at E4 (Aybera in 2013) genotype EH-03-010, and at E6 (Lalibela 2011) genotype EH-03-002 were the top ranking genotypes with the mean grain yield of 1183 kg ha⁻¹, 2703 kg ha⁻¹, 3484 kg ha⁻¹, and 2082 kg ha⁻¹, respectively. Thus, such inconsistent yield ranking from the environment to environment indicated the presence of possible cross over GEI as described by Ermiyas [14] and Matova and Gasura [15].

3.2. Combined Analysis of Variance and Mean Performance of Genotypes over Seven Environments

The combined analysis of variance for grain yield and yield-related traits of twelve field pea genotypes tested in seven environments had performed on the original (untransformed) data (Table 3). The analysis showed that field pea grain yield was significantly (p ≤ 0.01) affected by environment, genotype, and genotype by environment interaction. The significance of GEI indicated that the relative performances of the genotypes were not consistent across the test environments and the environments had different effects on the yield potential of the genotypes. This, in turn, suggested the need to conduct further analysis on genotype by environment interaction to understand the nature of the interaction. These results agreed with previous findings of Tamene et al. [7] which reported that genotypes, environments, and GxE interaction were significantly different for grain yield of field pea. Likewise, other authors also documented a significant GxE interaction for grain yield in field pea [12] and in faba bean [13]. Similarly, analysis of variance indicated a significant effect of genotypes for all collected yield-related traits and significant environmental effect for days to flowering, number of pods per plant, number of seeds per pod, and hundred seeds weight while tested genotypes showed significant variation in days to flowering, number of seeds per pod, and hundred seed weight due to the G X E interaction effect.

Table 3: Combined means of grain yield and yield-related traits of 12 field pea genotypes grown at seven environments.

Genotypes
DF
DM
PP
SP
PH
HSW
GY

IFPI12712
50
93
7
5
127
16
1872

EH-03-001
53
95
8
5
131
17
1778

COLL-24/002-1
53
93
7
6
111
13
1924

EH-03-002
53
93
7
6
135
18
2292

EH-03-010
53
94
7
6
120
16
1974

COLL-217/99-5
54
95
8
5
126
16
1842

EH-99-009-8
55
98
8
5
126
18
1889

IPF-4021
53
96
7
5
133
18
1899

EH-03-018
53
95
8
6
131
17
1847

EH-99-020-3
53
94
7
5
124
15
1877

Agrit (ch)
50
92
8
5
129
21
2003

Local (ch)
53
95
7
6
130
12
1582

Mean
53
95
7
5
127
16
1898

Cv %
4.22
2.66
23.98
13.48
11.44
7.28
9.66

Genotype

Environment

Ns

Ns

GXE interaction

Ns
Ns

Ns

Ns, , and = nonsignificant, significant at p < 0.05, and significant at p < 0.01, respectively, DF = days to flowering, DM = days to maturity, PP = pods/plant, SP = seeds/pod, HSW = 100 seed weight (g), GY = grain yield (kg/ha), and CV = coefficient of variation (%).

Among the tested genotypes, EH-03-002 was the highest yielder genotype with the mean grain yield of 2292 kg/ha followed by standard check Agrit (2003 kg ha⁻¹) and genotype, EH-03-010 (1974 kg ha⁻¹), respectively, whereas the lowest mean grain yield (1582 kg ha-1) was registered from a local check (Table 2). As indicated in the same Table 3, five genotypes scored highest grain yield over the grand mean (i.e., 1898 kg ha-1) but only one candidate genotype scored mean grain yield above the standard check Agrit. The candidate genotype, G4 (EH-03-002), was statistically high yielder (2292 kg ha⁻¹) than the other genotypes and showed 14.42% and 44.87% yield advantage over the standard check: Agrit (2003 kg ha⁻¹) and local check (1582 kg ha⁻¹), respectively. This genotype has been verified in 2017 and visited by the national variety releasing technical committee. Accordingly, genotype EH-03-002 has been officially released for its high yielding, deep white grain colour, and high adaptability in the moisture deficit areas of Wag Lasta.

3.3. Additive Main Effects and Multiplicative Interaction Analysis for Grain Yield

The additive main effects and multiplicative interaction (AMMI) analysis for grain yield showed highly significant (p ≤ 0.01) effect of environment, genotype, and genotype by environment interaction. The effects of environment, genotype, and genotype by environment interaction accounted for 77.47%, 13.83%, and 4.38% of the total sum of squares, respectively (Table 4). A large sum of squares for environments indicated that the environment was diverse, with large differences among environmental means causing most of the variation in grain yield. This also designated the reliability of the multienvironment experiments. The variation in soil type, soil fertility, and moisture availability might be the main reasons for the presence of variation among environment. In line to this Ermiyas [14] has reported the highest contribution (51.6%) of environmental effect for total variance of soybean grain yield. Similarly, Massaine et al. [16] in cowpea and Tadesse et al. [17] in common bean noticed the highest variation explained by the environmental effect.

Table 4: Additive main effects and multiplicative interaction (AMMI) analysis of variance for grain yield (Kg ha⁻¹) of field pea genotypes across seven environments.

Source
Df
SS
MS
Sum of square Explained

% Total
%G X E
% Cumulative Interaction

Total
251
140958296
561587

Genotypes
11
6169770
560888
4.38

Environments
6
109198668
18199778
77.47

Block
14
914635
65331
0.65

Interactions
66
19493498
295356
13.83

IPCA1
16
7380110
461257
5.24
37.86
37.86

IPCA2
14
5451738
389410
3.87
27.97
65.83

IPCA3
12
2876239
239687
2.04
14.75
80.58

Residuals
24
3785411
157725

Error
154
5181726
33648

Grand Mean (kg/ha) =1897.60
CV(%) = 13.49

R-Square = 0.93

= highly significant at the 0.01 probability level, = significant at the 0.05 probability level, Df = degree of freedom, and IPCA: principal component axis for interaction.

AMMI analysis (Table 4) also showed that the first interaction principal component axis (IPCA1), the second interaction principal component axis (IPCA2), and the third interaction principal component axis (IPCA3) of the interaction explained 37.86%, 27.97%, and 14.75% of the interaction sum of squares, respectively. The mean squares for the IPCA1 and IPCA2 were Significant at P ≤ 0.01 and cumulatively contributed to 65.83% of the total GxE interaction. The third interaction principal component axis (IPCA 3) was also significant (p ≤ 0.05). For the validation of the variation explained by GEI, the first two multiplicative component axes are adequate because of notable reduction of dimensionality and graphical visualization for the stability patterns of genotypes [18]. According to Yan et al. [19] and Annicchiarico (2002), the AMMI model can be predicted by using the first two IPCAs. Numerous authors utilized the first two IPCAs for AMMI analysis in different crops: for faba bean [13], for field pea (Tamene et al., 2008), for finger millet [20], and for triticale [21]. Thus, the interaction of the 12 field pea genotypes with seven environments was best predicted by the first two principal components of genotypes and environments.

4. Conclusion and Recommendation

Genotype by environment interaction has a key effect on crop variety development by complicating the release of varieties across challenging environments. Analysis of variance for every seven locations and combined over seven locations showed significant differences among genotypes, environments, and genotypes x environments interaction (GEI) for grain yield and most of the yield-related traits. The significant genotypes x environments interaction effects indicated the inconsistent performance of genotypes across the tested environments. Among the tested genotypes, EH-03-002, Agrit, EH-03-010, COLL-24/002-1, and IPF-4021 had mean grain yield above the overall mean grain yield of genotypes. Only the candidate genotype EH-03-002 had mean grain yield above the standard check Agrit.

Additive main effects and multiplicative interactions (AMMI) model was used to partition the G x E interaction of grain yield of field pea. The results indicated that the environments, GEI, and genotypes were accounted for 77.47%, 13.83%, and 4.37%, of the total sum squares, respectively, indicating that field pea grain yield was significantly affected by the changes in the environment, followed by GEI and genotypic effect.

Considering the seven environments data and field performance evaluation during the variety verification trial, the national variety releasing committee has approved the official release of candidate genotype, EH-03-002, with the vernacular name of “Yewaginesh” for moisture deficit areas of Wag Lasta and similar agroecologies.

Data Availability

The data used to support the findings of this study are available from the corresponding author upon request.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

Acknowledgments

The authors would like to thank staff members of the Crop Technology Supply Research Directorate of Sekota Dry Land Agricultural Research Center for their unreserved effort in trial management and data collection. The site keepers, Mr. Kefeyalew Girmaye and Mr. Mekonent Tadu, are also acknowledged for their unreserved effort in trial management and strong following up. Finally, we wish to acknowledge the Amhara Regional State Government for financial support and the directors at ARARI and Sekota Dry Land Agricultural Research Center for helping and facilitating us to conduct this study and come to completion with fruitful result.

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