Genotype X Environment Interaction

Oil content and fatty acid composition are important attributes desirable in oil crops. A 3-year (2002–2004) field evaluation of selected East African sesame accessions was conducted in Busia district in Kenya to assess the variability in the seed oil content, fatty acid composition and relationship between oil content and specific fatty acids. The correlations among different fatty acids and oil content were examined to create an understanding of their interrelations for future breeding. The oil content and the concentration of most of the fatty acids examined was significantly different among accessions. However, the concentration of palmitoleic, behenic and erucic acids was similar for all sesame accessions. The oil and fatty acid content varied significantly among the years. However, erucic acid content did not vary with years. Stearic, linolenic and arachidic acid contents were the least affected across the years. Oil content correlated negatively with palmitic and linoleic aci...

This assessing of genotype × environment interaction is one important step for accurate rice promising genotypes
evaluation in large multi-environment trials. In this study, ten rice promising genotypes and two Indonesian rice
varieties were grown in nsix environments during 2011 plant season to determine the grain yield stability and
adaptability. The experiment used randomized complete block design with three replications. Yield stability and
adaptability of yield performance were analyzed by using coefficient regression (bi), general mean of yield and
deviation of regression by Finlay-Wilkinson and Eberhart-Russell method and other parameters of stability and
AMMI model. From the current study, it is concluded that among rice promising genotypes that identified
superior performance genotypes i.e. IPB 107-F-5-1-1, IPB 115-F-3-2-1, IPB 116-F-44-1-1, IPB 116-F-46-1-1, IPB
117-F-4-1-1, and IPB 149-F-8-1-1 were stable for two or more stability parameters and combination with high
yield potential. Further analysis based on YSi only select four of the above genotypes i.e, IPB 115-F-3-2-1, IPB 116-
F-44-1-1, IPB 117-F-4-1-1, and IPB 149-F-8-1-1, that could be recommended to farmers based on their
performance of stability and high yield potential during selection. Based on AMMI biplot analysis, genotypes IPB
116-F-3-1-1, IPB 116-F-46-1-1, IPB 116-F-44-1-1and IPB 149-F-8-1-1 were more stable and have minimal
interaction with environment. Whereas, genotypes IPB 117-F-4-1-1 and IPB 107-F-5-1-1 was gave indication to
adapt at specific environmental condition.

Salinity limits the production capabilities of agricultural soils in large areas of the world. Both breeding and screening germplasm for salt tolerance encounter the following limitations: (a) different phenotypic responses of plants at different growth stages, (b) different physiological mechanisms, (c) complicated genotype × environment interactions, and (d) variability of the salt-affected field in its chemical and physical soil composition. Plant molecular and physiological traits provide the bases for efficient germplasm screening procedures through traditional breeding, molecular breeding, and transgenic approaches. However, the quantitative nature of salinity stress tolerance and the problems associated with developing appropriate and replicable testing environments make it difficult to distinguish salt-tolerant lines from sensitive lines. In order to develop more efficient screening procedures for germplasm evaluation and improvement of salt tolerance, implementation of a rapid and reliable screening procedure is essential. Field selection for salinity tolerance is a laborious task; therefore, plant breeders are seeking reliable ways to assess the salt tolerance of plant germplasm. Salt tolerance in several plant species may operate at the cellular level, and glycophytes are believed to have special cellular mechanisms for salt tolerance. Ion exclusion, ion sequestration, osmotic adjustment, macromolecule protection, and membrane transport system adaptation to saline environments are important strategies that may confer salt tolerance to plants. Cell and tissue culture techniques have been used to obtain salt tolerant plants employing two in vitro culture approaches. The first approach is selection of mutant cell lines from cultured cells and plant regeneration from such cells (somaclones). In vitro screening of plant germplasm for salt tolerance is the second approach, and a successful employment of this method in durum wheat is presented here. Doubled haploid lines derived from pollen culture of F1 hybrids of salt-tolerant parents are promising tools to further improve salt tolerance of plant cultivars. Enhancement of resistance against both hyper-osmotic stress and ion toxicity may also be achieved via molecular breeding of salt-tolerant plants using either molecular markers or genetic engineering.

Black Australorp (BA) exotic breed of chicken has been introduced to crossbreed with local chickens (LC) in Malawi since 1960. Localised survey studies and reviews have concluded that the crossbreeding programme has had no impact on improving local chicken productivity. The programme, however, continues and farmers like the exotic breed due to 'exotic is good' mentality. As an incentive to work with indigenous (local) chickens on farmer households and for farmers to see the impact for themselves, a current study was conducted to compare production characteristics of BA and LC when left to free-range on village flocks. BA (n=125) were distributed at random to farmers (maximum of three per farmer) in the villages at nine (9) weeks of age. On those farmers, LC chicks (n = 124) of the same age but hatched and mothered by a local hen were used to compare growth performance. The remaining 64 BA were kept intensive and fed commercial ration. Live weights were collected on all birds...

The performance of quantitative traits in sugarcane (Saccharum
spp. complex) often varies across diverse environments because of
significant genotype-by-environment interaction (GEI). Our objective
was to assess performance stability of 20 advanced sugarcane
genotypes across six environments, including two crop seasons
in Punjab. Data were obtained on cane yield (t/ha), sucrose %
juice, and commercial cane sugar % at harvest and subjected to
GGE [genotype (G) plus genotype-environment (GE)] biplot analysis,
which revealed high positive correlations between spring and
autumn crop seasons at all locations for all measured traits. This
implied that genotypes could be evaluated in either crop season,
which should reduce testing cost and time. Test environment
Faridkot (FDK) spring, being both discriminating and representative,
was an ideal test environment for selecting generally adapted
genotypes for cane yield. Similarly, Ludhiana (LDH) autumn was
an ideal test environment for selecting generally adapted genotypes
for quality traits. Co 0238 and CoPb 08214, having high meanperformance and stability across environments for cane yield and
quality traits, were identified as ideal genotypes. These genotypes
can be exploited commercially for the entire state of Punjab. The
GGE biplot helped identify a specifically adapted genotype, CoH
119, which was the best performer in Gurdaspur (GDSP) in both
crop seasons.

Production objectives and breeding practices of smallholder households participating in dairy goat breeding projects were analysed in relation to their ability to bring about sustainable genetic improvement in the dairy goat flocks in Kenya. A stratified survey involving 311 goat keepers in 4 project sites was used. This employed both qualitative and quantitative research methods to get a holistic view of dairy goats, and take into account the full array of contributions of dairy goats to the smallholder households. Milk production and sales of breeding stock were high priority functions for the objective to create a financial buffer. The breeding objective traits that farmers perceived as being of primary importance were milk yield, growth rate, body size, fertility and disease tolerance. There were logical trade-offs in the choice of these traits by farmers. Female dairy goats were mainly culled due to old age, poor fertility, small body size and poor health. Farmers did not place a large significance on unsatisfactory milk performance when culling female goats, mainly due to the very small production size and the high demand existing for breeding animals. Factors affecting milk yield and flock size presented satisfied a P < 0.1 significance level. The performance levels of dairy goats were mainly influenced by breeding strategies and the resource availability at the farm level. The optimisation of genotype x environment interactions remains the biggest challenge given the objectives set by the farmer.

Addiction Madness was thought out very well and will discuss about how the Western world has become a disability nation, why is x-raying so important especially pregnant women, will discuss what degenerative disease is, how I got myself of of disability, why it is important to know your blood type and factor, the courage of Dr. Alice Stewart who studied and her findings that x-ray radiation exposure can be passed on an unborn fetus causing the baby to be born with an autoimmune disease, when is exposure to radiation to much, will speak briefly upon the dawn of the x-rays or as I call in my paper x-beams, the history DES, will discuss my findings upon prescribed pain medication and abuse of them in the United States and other findings which will follow in the table of contents.

There are still many unanswered questions which may be answered by further research which I will be doing at a later date and writing books upon my findings and how I got myself off of prescribed medications and am now using God's healing foods along with alkaline pH water which Alkaline water helps balance the body's pH, which tends to be acidic because of our high acid food diet, stress and exposure to environmental toxins such as smog. Alkalize your body pH from acidic to alkaline pH, because cancer and many other illnesses cannot live in alkaline environments.

Also my findings are showing that our environment has a lot to do with what happens to our bodies and have research Dr. Alice Stewart and according to Gayle Greene (author) in 1943 who wrote: "The Woman Who Knew Too Much: Alice Stewart and the secrets of radiation" review by Choice Review, "Claiming radiation to be unsafe any dose."  Dr. Stewart's findings found exposure to low-level dose radiation was more serious than most scientists will admit.

Aim: To estimate the nature and magnitude of GEI interaction for oil content in sesame varieties and to identify stable and promising varieties for general and specific adaptations across the areas of the Awash valleys in Ethiopia. Study Design: Entries were planted in a randomized complete block design (RCBD) replicated thrice in each location and year. Original Research Article Abate et al.; AJEA, 9(2): 1-12, 2015; Article no.AJEA.18482 2 Place and Duration of Study: The study was conducted at Assaita, Melkassa and Werer representing the Lower, Upper and Middle Awash valleys of Ethiopia respectively, during the 2010/11 main cropping season and 2011/12 off season. Methodology: Morphological data taken from each environment were analyzed for combined analysis of variance, Additive Main Effects and Multiplicative Interaction (AMMI), Biplot analysis, AMMI Stability Value (ASV), and regression analysis. Finally, ranking of genotypes was done based on the overall results of all stability indices. Results: Combined analysis of variance showed highly significant (P<0.01) difference between the varieties, environments and GEI, suggesting differential response of varieties across testing environments and the need for stability analysis. Proportion of variance captured by environments was 1.43%, genotypes 91.5% and GEI 7.1% of the total variation, indicating less effect of environments on oil content as compared to the effect of genotypes. Stability analysis by AMMI and Joint-regression model were used to further shed light on the GEI of oil content. Two IPCA of AMMI were significant (P<0.01) and captured the largest portion of variation of the total GEI, which indicated that the AMMI model was the best for the data set. The Joint regression analysis indicated that the linear regression (bi) did not deviate from unity for all varieties, suggesting that performance of the cultivars could not be predicted in a linear manner. Conclusion: The influence of environment is less prominent in the manifestation of oil content along the areas of Awash valleys. Season two is the best environment for growing the present set of genotypes for oil content. Variety Adi was identified as the most stable variety across environments for oil content. This variety can be recommended for varied environments of the Awash valleys to exploit its yield potential. The rest high yielder varieties, Serkamo, Tate and Argene can be adapted only under favorable environmental conditions.

The study was aimed to evaluate the adaptability and stability of the soybean genotypes based on the seed yield and the other observed characteristics in the sites cultivated second crop soybean of Turkey which have Mediterranean climate conditions using the GGE biplot analysis method. The experiments were performed under irrigated conditions in 2014, 2015 and 2016 in four different locations (Adana, Antalya, Izmir and Sanliurfa) of Turkey. Fourteen soybean genotypes consisting of 10 advanced soybean lines and four standard varieties were analyzed by a randomized complete block design with 4 replications. The combined analysis of variance revealed significant (P<0.01) effects for all sources of variation (environment, genotype, and G×E interaction) for the seed yield and yield components. Genotype and environment accounted for about 2.59% and 51.04% of the total variation for seed yield, respectively, while the GE interaction explained 20.84% of the total variation. According to the GGE principle, five mega-environments were formed in the present study. Results of the research revealed that genotypes G8 (KANA), G9 (KASM 02), G11 (ARISOY), G3 (BATEM 306), G1 (BATEM 207) and G12 (ATAEM 7) were found as stable. According to GGE Biplot analysis for all traits and genotypes, G4 (BATEM 317) had the largest values for plant height, first pod height, days to 50% flowering, days to maturity and seed yield.

Rice as the major staple food of the world although is high in calories but deficient in essential micronutrients. This deficiency can be tackled by biofortification of rice grains with enhanced micronutrient content. Field experiments were carried out across three locations involving 17 genotypes, with the objective of assessing the genotype × environment interaction for native soil micronutrient assimilation in rice kernels and the influence of intrinsic soil variables on micronutrient content in rice grains. Contents of Fe, Zn, Cu and Mn in the milled kernels were found to vary significantly among genotypes and locations. There was significant genotype-by- environment interaction (GEI) for all the nutrients. Further, it was found that soil pH and soil available P had significant influence towards grain Fe content. Soil Zn availability and the electrical conductivity of the soil solution were found closely associated with grain Zn content. The two factors that regulated Cu and Mn content of rice grains were soil organic carbon content and soil Cu availability. The factorial regression (FR) approach to assess the role of significant intrinsic soil factor (s) on enrichment of specific micronutrient in the milled rice kernels showed differential genotype responses that ultimately determined grain micronutrient accumulation in each genotype. These determinants enabled prediction of genotypes suited to different environments. In certain cases, further examination of environmental co-factors is advocated to bring out a comprehensive picture of the micronutrient assimilation in milled rice grains.

Rhode Island Red (RIR) and Fayoumi chickens were evaluated on-station in a college farm and on-farm in village farms, whereas local chickens were only tested under on-farm condition. Traits recorded are egg production and egg quality, body weight and feed efficiency at 4, 8 and 12 months of age. Significant age effect was found for most traits except for shell thickness, albumen height and egg length. Also, significant breed by management system interactions were found for all traits measured in both systems. Fayoumi chickens were higher in egg production in both management systems. Moreover, they were higher than RIR in feed efficiency. RIR were higher in most egg quality traits and had higher weight gain. Local chickens performed below the two exotic breeds in most of the traits, but had higher weight gain than Fayoumi. Chickens kept on-farm had poorer performance than those kept on-station in all traits except for yolk colour.

This is an updated chapter that was originally published in the first edition of “Quantitative Genetics, Genomics and Plant Breeding.” Much new information has been added in the updated chapter published in the second edition of “Quantitative Genetics, Genomics and Plant Breeding.”

There is growing external pressure to abolish the farrowing crate, however alternative farrowing systems need to equal or surpass the performance (ie piglet survival) of more restrictive systems. In order to achieve consistent improvement in piglet survival genetic selection ...

Genotype X environment (GE) interactions limit the effectiveness of selection when selection is based only on mean yields. This study evaluated three methods of partitioning GE interaction into stability-variance components assignable to each cul-tivar in sugarcane (Saccharum spp.) cultivar evaluation tests. An unbiased stability-variance parameter (~) developed by Shukla and an ecovalence stability index (w) developed by Wricke were calculated separately for plant-cane and ratoon crops for Brix (%), grams of sugar per kilogram of cane, and tons per hectare of cane and of sugar for 11 cultivars. A cultivar X location component of variance (~c~) proposed by Plaisted and Peterson was also calculated. Within each crop, ~t and w had identical cultivar rankings (r, = 1.00"*) (**, Significant at the 0.01 level.) for each of the four traits studied. We propose that w sum of squares for each cultivar be expressed as w mean square and the latter be tested for significance in the same manner as ~. Those cultivars with a significant mean square were judged to be unstable. Shukla's method allowed use of a covariate of fertility and cultural practices at different locations to remove hetero-geneity variance (nonadditivity) from the GE interaction, and partitioning of the remainder of variance assignable to each cul-tivar (g~). Certain cultivars were judged stable after the covariate adjustment, indicating that the instability Was introduced by the linear effect of the covariate. Methodology for computing the ~cL component is cumbersome and would have little application when a large number of genotypes are evaluated. Repeatability of stability-variance parameters between crops (individual re-peatability) was relatively low for the four traits studied.