Harnessing Sorghum Landraces to Breed High-Yielding, Grain Mold-Tolerant Cultivars With High Protein for Drought-Prone Environments

Intermittent drought and an incidence of grain mold disease are the two major constraints affecting sorghum production and productivity. The study aimed at developing drought-tolerant sorghum varieties possessing a high protein content and tolerance to grain mold with stable performance using additive main effects and multiplicative interaction (AMMI) and genotype and genotype × environment interaction (GGE) biplot methods. Systematic hybridization among the 11 superior landraces resulted in subsequent pedigree-based breeding and selection from 2010 to 2015 evolved 19 promising varieties of grains such as white, yellow, and brown pericarp grains. These grain varieties were evaluated for their adaptability and stability for yield in 13 rainfed environments and for possessing tolerance to grain mold in three hot spot environments. A variety of yellow pericarp sorghum PYPS 2 (3,698 kg/ha; 14.52% protein; 10.70 mg/100 g Fe) possessing tolerance to grain mold was identified as a stable variety by using both AMMI and GGE analyses. Four mega-environments were identified for grain yield and fodder yield. Sorghum varieties PYPS 2, PYPS 4, PYPS 8, and PYPS 11 were highly stable in E2 with a low grain mold incidence. Besides meeting the nutritional demand of smallholder farmers under dryland conditions, these varieties are suitable for enhancing sorghum productivity under the present climate change scenario.

Download Full-text

The Impacts of Flowering Time and Tillering on Grain Yield of Sorghum Hybrids across Diverse Environments

10.20944/preprints201909.0198.v1 ◽

2019 ◽

Author(s):

Xuemin Wang ◽

Colleen Hunt ◽

Alan Cruickshank ◽

Emma Mace ◽

Graeme Hammer ◽

...

Keyword(s):

Grain Yield ◽

Flowering Time ◽

Genetic Background ◽

Linear Models ◽

Genetic Correlations ◽

Environment Interaction ◽

Canopy Development ◽

Factors Affecting ◽

Sorghum Production ◽

Relationship Of

Sorghum in Australia is grown in water-limited environments of varying extent, generating substantial genotype × environment interaction (GEI). Much of the yield variation and GEI results from variations in flowering time and tillering through their effects on canopy development. The confounding effects of flowering and tillering complicate the interpretation of breeding trials. In this study, we evaluated the impacts of both flowering time (DTF) and tillering capacity (FTN) on yield of 1741 unique test hybrids derived from three common female testers in 21 yield testing trials (48 tester/trial combinations) across the major sorghum production regions in Australia in three seasons. Contributions of DTF and FTN to genetic variation in grain yield were significant in 14 and 12 tester/trial combinations, respectively. The proportion of genetic variance in grain yield explained by DTF and FTN ranged from 0.2% to 61.0% and from 1.4% to 56.9%, respectively, depending on trials and genetic background of female testers. The relationship of DTF or FTN with grain yield of hybrids was frequently positive, but varied across the genetic background of testers. Accounting for the effects of DTF and FTN using linear models did not substantially increase the between trial genetic correlations for grain yield. The results suggested that other factors affecting canopy development dynamics and grain yield might contribute GEI and/or the linear approach to account for DTF and FTN on grain yield did not capture the complex non-linear interactions.

Download Full-text

Production Efficiency of Sorghum: The Case of Smallholder Farmers in Kafta-Humera District Tigray Ethiopia

South Asian Journal of Social Studies and Economics ◽

10.9734/sajsse/2021/v11i230282 ◽

2021 ◽

pp. 46-61

Author(s):

Tewoderos Meleaku ◽

Degye Goshu ◽

Bosena Tegegne

Keyword(s):

Production Efficiency ◽

New Technologies ◽

Smallholder Farmers ◽

Allocative Efficiency ◽

Sampling Technique ◽

Farm Income ◽

Stochastic Production Frontier ◽

Resource Base ◽

Factors Affecting ◽

Sorghum Production

Efficiency is an important factor for increasing productivity which leads to increase market output to achieve the goal of food security. In economics where resources are scarce and opportunities to use new technologies are limited, increasing efficiency remains the most reasonable means to raise productivity without necessarily developing new technologies or increasing the resource base. So, this study aimed to investigate level of production efficiency, factors affecting production inefficiency of sorghum small holder farmers in Kafta-humera district of Tigray Ethiopia. A two stage sampling technique was used to select 289 sample farmers who were interviewed using a semi- structured questionnaire to obtain data pertaining to sorghum production during the year 2016/2017.Stochastic production frontier model was used to identify production efficiency levels, where as Tobit models was used to estimate factors affecting production efficiency levels. Accordingly, the mean technical, allocative and economic efficiencies were 78.01%, 65.21% and 39.91% respectively. This implies that output can be increased by 21.99% or cost can be reduced by 34.79% with the existing level of technology and resources. Input variables such as land, labor, tractor plow power, chemicals, DAP and Urea fertilizers positively affects production of sorghum. The discrepancy ratio (γ) implied that about 91.91% of the variation in sorghum production was attributed to technical inefficiency effects. Tobit model revealed that age, education, non-farm income, credit, extension service and training positively and significantly affected technical efficiency while age square and total livestock holding had negatively and significantly affected. Additionally, age square, education and frequency of farm visit positively and significantly affected allocative efficiency, while age, non-farm income, credit and extension contact have a negative and significant affect. Economic efficiency was positively and significantly affected by age, education, non-farm income, credit, extension contact and frequencies of farm visit but negatively affected by age square. These indicate that there is a room to increase in production efficiency of sorghum in the study area. Therefore, government authorities and other concerned bodies should take into consideration the above mentioned demographic, socioeconomic and institutional factors to increase efficiency of sorghum.

Download Full-text

Yield Components Stability Assessment of Peas in Conventional and Low-Input Cultivation Systems

Agriculture ◽

10.3390/agriculture11090805 ◽

2021 ◽

Vol 11 (9) ◽

pp. 805

Author(s):

Vasileios Greveniotis ◽

Elisavet Bouloumpasi ◽

Stylianos Zotis ◽

Athanasios Korkovelos ◽

Constantinos G. Ipsilandis

Keyword(s):

Seed Yield ◽

Stability Index ◽

Farming Systems ◽

Farming System ◽

Genotype By Environment Interaction ◽

Environment Interaction ◽

Low Input ◽

Cultivation Systems ◽

Biplot Analysis ◽

Stable Performance

The primary purpose of this study was to explore yield stability of pea (Pisum sativum L.) cultivars based on stability index, with specific aim at studying cultivar behavior regarding yield of peas under both conventional and low-input cultivation systems. Five cultivars of peas were used in a strip-plot design. Correlations showed a significant positive relation between seed yield and some other traits. Indirect seed yield improvement may be implemented by improving pod length, which generally showed high stability indices in Greek mega-environment. Comparisons between conventional and low-input farming systems generally did not affect stability estimations, but revealed cultivars that exhibited stable performance, even in low-input farming systems. The additive main effects and multiplicative interaction (AMMI) biplot analysis, genotype by environment interaction (GGE) biplot analysis and analysis of variance (ANOVA) showed statistically significant differences between genotypes and environments, and also the farming system. This way, we have certain cultivars of peas to recommend for specific areas and farming system, in order to achieve the most stable performance. Vermio proved to be a stable cultivar for seed yield performance, in Giannitsa, Trikala and Kalambaka area, in low-inputs farming systems, while Olympos was the best in Florina area and low-input farming.

Download Full-text

Determinants Sorghum Market among Smallholder Farmers in Kafta Humera District Tigeray Ethiopia

South Asian Journal of Social Studies and Economics ◽

10.9734/sajsse/2020/v8i130200 ◽

2020 ◽

pp. 1-13

Author(s):

Tewoderos Meleaku ◽

Degye Goshu ◽

Bosena Tegegne

Keyword(s):

Smallholder Farmers ◽

New Technology ◽

Sampling Technique ◽

Economic Benefits ◽

Farm Size ◽

Tobit Regression ◽

Output Market ◽

Ethiopian Government ◽

Sorghum Production ◽

Current Price

Markets are important for economic growth and development of a given country to ensure sustainable supply of food. Failure of market leads to failure of adoption of new technology which is necessary for increasing productivity. Sorghum has been considered as a strategic crop by the Ethiopian government aiming at enhancing food security and essential source of income for farmers as whole economic benefits to the country. Smallholder’s farmers producing about 95 percent of the national agricultural production increasing market participation among smallholder farmers have a big opportunity to boost their living standards. The objective of this study was analyzing factors determining smallholder sorghum farmer decision to participate in output market and level of marketed output smallholder farmers in Kafta-Humera district of Tigeray Ethiopia. A two stage sampling technique was used to select 289 sample farmers who were interviewed using a semi- structured questionnaire to obtain data pertaining to sorghum production during the year 2016/2017. Descriptive and Tobit regression analyses were used to determine the key factors that influence household participation in the market in terms of volumes of product sales. The study identified that quantity of sorghum supplied to the market was positively affected by credit, extension contact, training, sorghum farm size, current price of sorghum and education, while family size and lagged price of sesame negatively affected. These indicate that there is a room to increase in supply and intensity of sorghum in the study area. Therefore, government authorities and other concerned bodies should take into consideration the mentioned demographic, socioeconomic and institutional factors to increase supply of sorghum to the market in study area.

Download Full-text

Analysis of Genotype by Environment Interaction on Cocoa Hybrids (Theobroma cacao L.) Resistance to Phytophthora Pod Rot

Pelita Perkebunan (a Coffee and Cocoa Research Journal) ◽

10.22302/iccri.jur.pelitaperkebunan.v32i3.234 ◽

2016 ◽

Vol 32 (3) ◽

pp. 162-170

Author(s):

Agung Wahyu Soesilo ◽

Indah Anita Sari ◽

Bayu Setyawan

Keyword(s):

Block Design ◽

Genotype By Environment Interaction ◽

Environment Interaction ◽

Gge Biplot ◽

Genotype By Environment ◽

Experimental Station ◽

Stability Performance ◽

Stable Performance ◽

Wet Climate ◽

The Stability

Phenomenon of genotype by environment interaction was able to influence the stability performance of cocoa resistance to Phytophthora pod rot (PPR). This research had an objective to evaluate the effect of genotype by environment interaction on resistance of cocoa hybrids to PPR. The tested hybrids were F1 crosses between selected clones of TSH 858, Sulawesi 1, Sulawesi 2, NIC 7, ICS 13, KEE 2 and KW 165. There were 14 tested hybrids and an open pollinated hybrid of ICS 60 x Sca 12 was used as control in multilocation trials at four different agroclimatic locations, namely Jatirono Estate ((highland-wet climate), Kalitelepak Estate (lowland-wet climate), Kaliwining Experimental Station (low land-dry climate) and Sumber Asin Experimental Station (highland-dry climate). Trials were established in the randomized complete block design with four replications. Resistance to PPR were evaluated based on the percentage of infected pod for the years during wet climate of 2010 in Jatirono, Kalitelepak and Kaliwining followed in dry climate of 2011–2015 in Kaliwining and Sumber Asin. Variance of data were analyzed for detecting the effect of genotype by environment interaction (GxE) then visualized with a graph of genotype main effect and genotype by environment interaction (a graph of GGE) biplot. There was consistently no interaction effect between hybrid and location to PPR incidence which was affected by single factor of hybrid, year, location and interaction between year and location. The effect of year indicated yearly change of weather was more important to PPR incidence than location difference. A graph of GGE biplot indicated a stable performance of the tested hybrids among locations.

Download Full-text

GGE biplot analysis of genotype × environment interaction and identification of mega-environment for baby corn hybrids evaluation in India

Indian Journal of Genetics and Plant Breeding (The) ◽

10.31742/ijgpb.79.4.3 ◽

2020 ◽

Vol 79 (04) ◽

Author(s):

Mukesh Choudhary ◽

Bhupender Kumar ◽

Pardeep Kumar ◽

S. K. Guleria ◽

N. K. Singh ◽

...

Keyword(s):

Total Variation ◽

Value Added ◽

Corn Yield ◽

Environment Interaction ◽

Gge Biplot ◽

Corn Hybrids ◽

Biplot Analysis ◽

Genotype Environment Interaction ◽

Green Fodder ◽

Fodder Yield

Baby corn has emerged as one of the most important sources to augment the farmer’s income in peri-urban areas. It has diverse uses as vegetables, snacks, value-added products and assured supply of green fodder for livestock. The multilocation varietal trials mainly emphasize on the identification of new superior cultivars over commercial checks, while genotype×environment interaction (GEI) is ignored. In the current study, 13 baby corn hybrids were evaluated for green ear yield, baby corn yield and green fodder yield over eight locations (environments) in kharif seasons of 2015 and 2016 using GGE biplot analysis. The results revealed a higher proportion of the variation in the data is attributable to the environment (72.4-87.0%), while genotype contributed only 2.5-7.3% of the total variation. GEI contributed 10.5-24.1% of the total variation. Superior stable hybrids for green ear yield, baby corn yield and green fodder yield could be identified using a biplot graphical approach effectively. ‘Which won where’ plot for each of the traits partitioned testing locations into three mega-environments with different winning genotypes for different traits in respective mega-environments. Thus it can be concluded that similar inferences can be drawn from one or two representatives of each mega-environment instead of using several locations. Hence, the presence of extensive crossover GEI in baby corn multi-location trials clearly suggests the need to emphasize on smaller zonation of testing locations and location-specific breeding. Particularly in baby corn, this is the first study on GGE biplot analysis to identify mega-environments for effective evaluation of baby corn trials.

Download Full-text

Genotype x environment interaction for grain yield of maize (Zea mays L.) inbreds under salinity stress

Bangladesh Journal of Agricultural Research ◽

10.3329/bjar.v39i2.20431 ◽

2014 ◽

Vol 39 (2) ◽

pp. 293-301 ◽

Cited By ~ 1

Author(s):

A Bisawas ◽

U Sarker ◽

BR Banik ◽

MM Rohman ◽

MZA Talukder

Keyword(s):

Zea Mays ◽

Grain Yield ◽

Salinity Stress ◽

Zea Mays L ◽

Phenotypic Traits ◽

Environment Interaction ◽

Ecological Stress ◽

Plot Analysis ◽

Normal Environment ◽

Stable Performance

An experiment was conducted on Maize (Zea mays L.) to investigate the genotype × environment interaction for gain yield of maize inbreds under salinity stress. The objective of this study was to evaluate G × E interactions and yield stability in multi-environmental trials across wide ecological stress environments. Prescreened thirteen maize inbred lines collected from CYMMT, India were evaluated for phenotypic traits at different salinity conditions (8dS, 12dS and 16dS) with normal environment. The environmental mean and genotypic mean ranged from 10.3 to 49.7 g and 10.9 to 52.8 g, respectively. The regression coefficient (bi) values of these genotypes ranged from 0.44 to 1.66. Among the genotypes P43, CZ29 and CZ33 produced higher grain yield and highly responsive under different salinity level. On the other hand considering the Pi, bi, S2di and AMMI bi-plot analysis the genotypes E32, P29 and P35 showed almost stable performance across the different salinity conditions. DOI: http://dx.doi.org/10.3329/bjar.v39i2.20431 Bangladesh J. Agril. Res. 39(2): 293-301, June 2014

Download Full-text

Factor analysis to investigate genotype and genotype × environment interaction effects on pro-vitamin A content and yield in maize synthetics

Euphytica ◽

10.1007/s10681-019-2505-3 ◽

2019 ◽

Vol 215 (11) ◽

Cited By ~ 1

Author(s):

Wende Mengesha ◽

Abebe Menkir ◽

Silvestro Meseka ◽

Bunmi Bossey ◽

Agbona Afolabi ◽

...

Keyword(s):

Factor Analysis ◽

Vitamin A ◽

Public Health Problem ◽

Preschool Age ◽

Sub Saharan Africa ◽

Provitamin A ◽

Major Public Health Problem ◽

Environment Interaction ◽

Maize Varieties ◽

Stable Performance

Abstract Vitamin A Deficiency (VAD) is a major public health problem in Sub-Saharan Africa affecting 33 million preschool-age children. Enrichment of maize varieties with provitamin A could provide sustainable and affordable solution to VAD. This study was conducted to understand the extent of GEI effects on both grain yield and provitamin A content in 21 maize synthetics and identify synthetics combining stable performance with high level provitamin A content across diverse environments in West Africa. Combined analysis of variance found significant (p < 0.01) GEI effects that prompted further investigation of the GEI magnitude using mixed model with factor analysis. Factors 1 and 2 explained 71% of the total variability. G5, G4, G12, G18, G2 and G14 were broadly adapted to a range of environments and considered the most stable and high yielding. G8, G1, and G10 were specifically adapted to a group of environments. Whereas, G21, G19 and G17 were found to be the worst and unstable genotypes. G4 combined stable performance with high provitamin A content, whereas G20 and G18 were stable but had low provitamin A contents. Three genotypes, G4, G12 and G14 were found to combine stability with high provitamin A contents. These genotypes can be recommended for production in the low-land tropics of West and Central Africa with similar environments.

Download Full-text

Evaluation of the performance of sorghum genotypes using GGE biplot

Canadian Journal of Plant Science ◽

10.4141/cjps-2015-119 ◽

2015 ◽

Vol 95 (6) ◽

pp. 1205-1214 ◽

Cited By ~ 8

Author(s):

Edmore Gasura ◽

Peter S. Setimela ◽

Caleb M. Souta

Keyword(s):

Grain Yield ◽

Agronomic Traits ◽

Abiotic Factors ◽

Research Station ◽

Environment Interaction ◽

Gge Biplot ◽

Ecological Zones ◽

Genotype Environment Interaction ◽

Sorghum Production ◽

Sorghum Genotypes

Gasura, E., Setimela, P. S. and Souta, C. M. 2015. Evaluation of the performance of sorghum genotypes using GGE biplot. Can. J. Plant Sci. 95: 1205–1214. In spite of sorghum's drought tolerance, it is largely affected by genotype×environment interaction (GE), making it difficult and expensive to select and recommend new sorghum genotypes for different environments. The objectives of this study were to examine the nature of GE for sorghum grain yield, to identify superior sorghum genotypes for sorghum production environments and determine ideal testing locations for future breeding activities in Zimbabwe. The grain yield of 20 sorghum genotypes from Seed Co. Pvt. Ltd. were evaluated for 2 yr (2011/2012 and 2012/2013 cropping seasons) at five locations in different agro-ecological zones of Zimbabwe. Combined analyses of variance showed significant differences for genotypes (P<0.01), environments (P<0.001) and genotype×location (P<0.01). Genotype×environment variance component was seven times greater than that of genotypes. Genotype×environment interaction was attributed to the variability in the predictable biotic and abiotic factors associated with the different locations. The genotype main effect plus GE biplot showed that the experimental sorghum genotypes W07, W09, W05, G06 and OP46 were high yielding and stable, and possessed other desirable agronomic traits. The most discriminating and representative location was Rattray Arnold Research Station.

Download Full-text

Factors That Influence Technical Efficiency of Sorghum Production: A Case of Small Holder Sorghum Producers in Lower Eastern Kenya

Advances in Agriculture ◽

10.1155/2015/861919 ◽

2015 ◽

Vol 2015 ◽

pp. 1-11 ◽

Cited By ~ 3

Author(s):

Evaline Chepng’etich ◽

Sospeter Onchoke Nyamwaro ◽

Eric Kiprotich Bett ◽

Kwena Kizito

Keyword(s):

Technical Efficiency ◽

Formal Education ◽

Smallholder Farmers ◽

Negative Influence ◽

Agronomic Practices ◽

Drought Tolerant ◽

Sorghum Production ◽

On Farm ◽

Small Holder ◽

Arid And Semiarid

Majority of the rural households in Kenya depend on agriculture as a source of food and livelihood. Agricultural productivity has been declining due to many factors resulting in increased food insecurity in the country. Consequently, there is a renewed interest in promoting drought-tolerant crops such as sorghum which thrives in the arid and semiarid lands of the developing world. However, performance of sorghum production among the smallholder farmers has still remained low. This study was thus carried out to identify factors that influence technical efficiency of sorghum production among smallholder farmers in Machakos and Makindu districts of the lower eastern Kenya. Collected data on farm and farmer characteristics were analysed by use of descriptive statistics and Tobit model. Result highlights show that technical efficiency was influenced positively by formal education level of the household, experience in sorghum farming, membership in farmers associations, use of hired labour, production advice, and use of manure. Surprisingly household size, meant to enhance labour, had a negative influence. To increase technical efficiency, efforts should focus on improving information flows on agronomic practices. Farmers should also be encouraged to form and actively participate in various farmers associations, which enhance learning and pooling of labour resources, hence improving technical efficiency.

Download Full-text