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[EN[ In this work, a new mathematical algorithm for sparse and orthogonal constrained biplots, called CenetBiplots, is proposed. Biplots provide a joint representation of observations and variables of a multidimensional matrix in the same reference system. In this subspace the relationships between them can be interpreted in terms of geometric elements. CenetBiplots projects a matrix onto a low-dimensional space generated simultaneously by sparse and orthogonal principal components. Sparsity is desired to select variables automatically, and orthogonality is necessary to keep the geometrical properties that ensure the biplots graphical interpretation. To this purpose, the present study focuses on two different objectives: 1) the extension of constrained singular value decomposition to incorporate an elastic net sparse constraint (CenetSVD), and 2) the implementation of CenetBiplots using CenetSVD. The usefulness of the proposed methodologies for analysing high-dimensional and low-dimensional matrices is shown. Our method is implemented in R software and available for download from https://github.com/ananieto/SparseCenetMA., Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. This work was not supported by any grant., Publicación en abierto financiada por el Consorcio de Bibliotecas Universitarias de Castilla y León (BUCLE), con cargo al Programa Operativo 2014ES16RFOP009 FEDER 2014-2020 DE CASTILLA Y LEÓN, Actuación:20007-CL - Apoyo Consorcio BUCLE

The pervasive soil-borne pathogen Sclerotium rolfsii (Sacc.) is responsible for collar rot (CR) of chickpea identified as one of the major production constraints for its cultivation worldwide. Presence of wider host range and absence of stable resistance sources against the pathogen makes it more difficult to manage, and seeks urgency towards identification of new sources of resistance. Environment play vital role towards host–pathogen dynamics also impact disease management. This study was focused on deciphering genotype × environment interactions with the objective of delineating and validating durable resistant genotypes against CR, identifying a suitable testing location. Initially, from 81 genotypes, 25 promising genotypes were selected based on their disease reaction (

This study aimed to investigate the phenolic composition and antioxidant capacity of Inula viscosa L. aerial parts as influenced by their geographic origin and the type of extractant used. We established the extraction yield and phenolic composition of I. viscosa plants supplied from Mediterranean, Aegean, and Black Sea regions and evaluated their antioxidant capacity. Hierarchical clustering agglomerative (CA) and principal components analysis (PCA) was performed for further evaluation of similarities and differences among the I. viscosa extracts. Based on PCA and CA, the plants were specified in three distinct groups; one group presented higher bioactive composition and more potent antioxidative properties. The extractant type was one of the parameters affecting the clustering of the plants on the PCA biplot and CA dendrogram. Amongst the screened plants, Plant 1 was discriminated by its higher extraction efficiency, bioactive compounds, and antioxidant capacity compared to other plants. Ethanol was the most effective extractant studied when compared with ethyl acetate and hexane in terms of extraction yield, phenolic composition, and antioxidant capacity. Due to our findings, the phenolic composition was successfully used as a biochemical indicator to specify natural I. viscosa plants. The results highlighted that I. viscosa plant could be an excellent natural source of antioxidants to be evaluated in food and pharmaceutical industries.

Key message The morpho-agronomic and genetic studies recorded variations in vegetative and reproductive traits, and in molecular information through population structure and clustering approaches among South African Phaseolus vulgaris landraces. Abstract Phaseolus vulgaris L., commonly known as common beans, is widely used for its edible leaves, immature pods, and dry seeds. Studies on variation in morphology and genetics among P. vulgaris landraces are limited in South Africa. Therefore, the current study aimed to determine the morpho-agronomic and genetic variations among P. vulgaris landraces. Thirty-eight landraces from different agro-ecological origins, planted in a randomized complete block design, had their variation in vegetative and reproductive traits determined. These landraces were studied for their genetic diversity using simple sequence repeat (SSR) markers. The landraces were clustered in a biplot and dendrogram based on their seed coats, shape, similar morpho-agronomic traits, and their areas of origin. A total of 57 alleles were produced with a mean of 3.64 per SSR locus. The polymorphism information content ranged from 0.00 to 0.58. The population structure had the highest delta value K = 2, thus the 38 landraces were divided into two subpopulations based on the Bayesian approach. The population structure showed an overlap among the landraces as several from the Mesoamerican carried some seed traits or genes from the Andean gene pool, and showed a high level of admixtures. The principal coordinate analysis and the dendrogram had a similar clustering pattern as the population structure. This study revealed the potential markers with high diversity that can be used to determine genetically homogenous/heterogeneous landraces. Therefore, the use of PV-ctt001, PV-ag001, and PV-at003 could be beneficial in future breeding, conservation, and marker-assisted selection studies.

In multisite forest genetic experiments, the presence of genotype × environment interaction (GEI) is common. GEI may negatively affect the estimates of genetic variance and hamper selection decisions in tree breeding programs. Several measures exist to evaluate the stability of tested genotypes’ performance across environments with a choice of the method likely affecting breeders’ decisions. In this study, we evaluated variation in diameter and height growth performance in the progeny test established at 4 sites with 80 open-pollinated half-sib families of Scots pine. We found significant variation among examined progeny at age 10, reaching up to 31% for diameter and 20% for height depending on site, and significant GEI in both traits. We estimated contribution of each family to GEI using various methods and tools of GEI analysis—AMMI, GGE biplots, heterogeneity of regression coefficients (bi’s), the deviation mean squares from regression (s2di) and Kang’s yield-stability index (YSi). Despite the presence of the cross-over interaction, family ranks did not vary much among sites. The selections based on the phenotype, YSi and restricted bi corresponded well to each other leading to the expected response to selection up to 7.8% on diameter and 4.4% on height, whereas those based on the AMMI stability variance were different and lead to a slight loss in both traits. We discuss our results in the context of the usefulness of those measures of genotype stability for tree breeding programs and propose the procedure to follow for making selection decisions in forest experiments with GEI.

Under the climate change scenario, high-temperature stress declines crop yields. The present study was designed with the objectives to identify the stable heat-tolerant genotypes for grain yield under normal and heat stress conditions at three locations. The 80 mung bean genotypes and 3 check varieties were sown in three agro-ecological zones of Pakistan, namely, Chakwal, Piplan, and Bhakkar. The experiments were planted in two sowing dates, i.e., the normal sowing and late sowing by using an augmented randomized block design with 6 blocks at each location. The plot size for each genotype was 2.4 m2 at all the locations. All cultural and agronomic practices were carried out as per recommendations. Ten randomly selected plants were used to record the yield-related traits. An infrared gas analyzer (IRGA) was used to measure physiological traits like photosynthesis rate and stomatal conductance. To study the nature of relationship among traits, Pearson correlation analysis was done using SPSS software (v. 16.0). The GGE biplots were constructed to graphically represent the genotype and GE interaction of multi-environment data using the software plant breeding tools. Three views of the GGE biplot were generated to display the comparative performance, rank, and stability of each genotype in the tested environments. Correlation and principal component analysis (PCA) revealed a positive interaction of grain yield with pods plant−1, seed pod−1, 100 grain weight, and harvest index, while days to flowering and maturity had a negative association under normal and heat-stressed conditions. The GGE biplot analysis efficiently explained 85.1% of the total variation and demonstrated that among 8 vertex genotypes of polygon biplot, the G14 and G38 were heat tolerant as these genotypes outclassed others in all the heat-stressed environments. In contrast, the genotypes G51 and G74 produced maximum yield under normal conditions (E3 and E5). Among all the genotypes, genetic diversity was observed for grain yield and other morpho-physiological traits. Significant G × E interaction was observed. The genotypes G14, G38, and G51 were identified as stable and heat tolerant in most of the environments. These findings will be helpful for development of heat-tolerant mung bean breeding material in the future.

The subjectivity of index selection and unpredictable environmental variabilities cause ambiguities in multiple-trait selection across environments. In the present study, we tested and validated a recently proposed multivariate approach for genotypic selection based on multiple trait evaluations. A genotype by yield*trait (GY*T) biplot approach originally proposed was validated in this study to assess the comparative efficiency of GY*T approach over genotype by trait (GT) approach in genotypic selection on multiple traits in common bean. The analysis is based on six trials spread over four years from 2015–2018 at two locations. Based on the GY*T analysis, the biplot could improve the variation accounted for by PCI and PC2 from 71.37 to 92.81%. The genotypes WB-341, WB-1634 and WB-451 were identified as high yielding and possessed higher seed yield on account of higher values of pods per plant and seeds per pod indicating that these possess the ideal trait combination of yield, pod number and seeds per pod. The genotype WB-222 had the ideal trait combination of yield, pods per plant and plant height. Similarly the genotype WB-185 had the ideal trait combination of yield and 100-seed weight but was poor for pods per plant. The genotype WB-83 had an opposite trait profile to WB-185 especially for 100-seed weight, but was good for pods per plant, even though both had comparable yield levels. Based on the results of present study and few earlier studies, we conclude that GY*T approach based on multi-trait data is comparatively more efficient than GT biplot.

Assessing the effectiveness of different molecular markers is essential for identification of appropriate ones for crop improvement and conservation, hence, inter-simple sequence repeat (ISSR) and start codon targeted (SCoT) markers were used for this study. Sixty-six accessions with different genomes obtained from International Transit Center, Belgium, were used for DNA extraction, amplification with ISSR and SCoT markers and agarose gel electrophoresis. The reproducible bands were scored for analyses. We identified high allelic richness of 299 (ISSR) and 326 (SCoT). Polymorphic information contents (ISSR: 0.9225; SCoT: 0.9421) were high but SCoT exhibited higher level of informativeness. The two markers demonstrated high percentage polymorphic loci (ISSR: 91.21–100%; SCoT: 96.97–100%). Other genetic indicators including effective number of alleles, Nei’s genetic diversity, and Shannon information index were higher in SCoT and further elucidated the usefulness of the markers. Intraspecific genetic diversity, interspecific genetic diversity, coefficient of gene differentiation and level of gene flow revealed extensive gene flow and larger variability within the accessions. Both ISSR and SCoT grouped the accessions via dendrogram, biplot and structure analyses. Though the two marker systems varied in their informativeness, they demonstrated high effectiveness in resolving genetic diversity (GD) of the different accessions, with higher efficiency in SCoT markers. Due to higher GD indices exhibited by SCoT, AS is the most genetically endowed one. Our study showed that SCoT markers are more informative than ISSR for GD exploration, assessment and cluster resolution of Musa species, thereby revealing the potential of SCoT markers for improved breeding and conservation.

Environmental pollution arising from crude oil exploratory activities has adversely impacted both the living and non-living components of the ecosystem. An insight into the impact of such activities with focus on Goi Creek in Ogoniland was provided in this study. We generated reliable data for physicochemical, heavy metal, and total hydrocarbon levels in the creek via a total of 40 samples collected across 4 stations designated within the creek in a duration of 10 months. With the exception of temperature, total dissolve solid, dissolved oxygen, chloride, sulfate, nitrate, zinc, and vanadium, the levels of other regulated parameters in the samples were not compatible with the national and international guidelines and standards for surface water quality including Federal Ministry of Environment Guidelines and standards for water quality in Nigeria and Environmental Protection Agency National recommended water quality criteria, respectively. The principal components (PCs) 1 and 2 of principal component analysis biplot revealed that the concentrations of the physicochemical parameters showed a mixed distribution among the stations; however, the heavy metals were more localized to station 4. Moreover, the dataset was subjected to water quality index (WQI), contamination index (Cd), heavy metal evaluation index (HEI), trace element toxicity index (TETI), and environmental water quality index (EWQI) to determine the extent of contamination. The result showed poor WQI, high contamination for Cd, and low-to-medium contamination for HEI. Although, there were variations among the stations on the contamination level, uniform remediation method should be adopted due to the similarity of the contaminants in all the stations.

Despite much effort, little exotic germplasm has been introduced in temperate maize breeding programs. Tropical and subtropical maize germplasm from CIMMYT is the most genetically diverse in the world and should be useful in widening the genetic base of temperate maize germplasm. Extracting the most suitable material from exotic germplasm is a tough challenge for plant breeding programs. This study aimed to determine the optimal number of testers to screen a maize line derived from tropical and subtropical CIMMYT germplasm. For this purpose, four temperate maize testers (MO17, B73, K47/3, and K18) and nine lines from CIMMYT were crossed. The 36 crosses along with two hybrid checks were assessed in a randomized complete block design with three replications at four maize growing regions in Iran. The GGE biplot procedure and methodology proposed by Fan et al. (2010) were used to analyze the results indicating a possibility of direct use of 2, 3, 4, and 9 CIMMYT lines to improve grain yield in temperate environments. Temperate maize testers B73 and K47/3, which belong to the Reid Yellow Dent heterotic group, were very efficient in selecting superior tropical and subtropical CIMMYT germplasm, whereas testers MO17 and K18 from the Lancaster Sure Crop heterotic group were fairly good and weak, respectively. Actually just one temperate tester could select most, if not all, of the top exotic tropical and subtropical lines, and a second tester would provide backup.

Due to environmental diversity, genotype performance for yield and stability is essential for crop improvement. The GGE biplot, and 11 parametric and non-parametric stability models were employed to evaluate 23 wheat (Triticum aestivum L.) genotypes, tested in randomized complete block trials across two contrasting fields (sandy and loamy) and four seasons. The sandy field yielded half compared to the loamy field, reflecting relatively low- and high-input environments, respectively. Analysis of variance showed significant differences between genotypes for grain yield and crossover genotype ranking across environments; the loamy field was more representative of an overall genotype performance. The stability models resulted in diverse genotype classification and were distinguished into two separate groups. The first group comprised measures that consider both G and GE focusing on the agronomic aspect of stability and high-yielding ability. The second group included tools that consider only GE focusing on the static aspect of stability and characterized most of the high-performing genotypes as undesirable. The GGE biplot highlighted genotypes that were characterized as either desirable or undesirable following most models in both groups. Therefore, the GGE biplot presented an effective statistical tool for assessing wheat genotypes in terms of general and specific adaptation without overlooking yielding ability. It is suggested the preference of favorable experimental conditions and application of the GGE model to identify genotypes that are more promising for stable performance across wide agroecosystems.

In the present study, fifty genotypes were evaluated over 5 years. The analysis of variance revealed significant interaction (P

To study the impact of terminal moisture stress, thirty-one genotypes of mungbean were screened under irrigated and moisture stress at pod filling stage during summer 2013–2014 in randomized block design. Mean performance revealed RMG 492 and GVIT-203 as best genotypes under irrigated and moisture stress, respectively. Individual and combined ANOVA revealed significant difference among the genotypes. The genotype-trait (GT) biplot analysis was done using multiple traits for irrigated and moisture stress separately. The polygon view of GT biplot revealed that AKM 9904, IPM-02-19, LGG 528, PUSA VISHAL and RMG 492 in irrigated condition; RMG 492 and GVIT-203 in moisture stress as best genotypes. The genotypes VG-6197A, IPM-02-19, COGG 974, ML 145 and PUSA 9531 under irrigated condition; EC-396117, RMG 492 and VG-6197A under moisture-stress condition are close to ideal genotypes. The harvest index (HI) was identified as the best and stable trait for all genotypes under both irrigated and moisture-stress conditions. The relationship among characters showed that seed yield per plant is positively associated with HI and relative water content under both irrigation regimes. The seed yield per plant and specific leaf area are more discriminative under both conditions, whereas SCMR and chlorophyll content are more representatives under irrigated and moisture stress, respectively. The genotypes RMG 492 and VG-6197A identified in this study could be used in different breeding programs and traits SCMR and harvest index portrayed in this study can be used for screening of moisture-stress tolerance in different selection processes.

Tribolium castaneum is known, to be the most cosmopolitan of pests. Its ubiquitous character has drawn attention to its morphological adaptability. The objective of this study was to characterize the morphology of T. castaneum populations in West African countries. Millet and rice are collected from each sampled West African country. After emergence during mass rearing, 30 male adults were randomly selected from each country and from each cereal and made up the individuals of that population on that cereal. On each adult, 19 variables were measured of which 16 were used (the other three are invariable). The significance of the rank differences of each variable between West African populations is determined by the Kruskal-Wallis and Wilcoxon-Mann-Whitney tests. PCAs were used to determine PCs and these were used to perform DAs. the West African Morphogroups were determined by the HAC. Following the logarithmic transformation of the data, the biplots showed a difference in form between these populations. Log-transformed revealed significant mean differences between pairs of populations on each cereal. The HAC revealed the existence of three morphogroups. Morphogroup_2, which groups more individuals on each of the developmental supports, is the subregional morphogroup of West Africa. The distribution of other morphologies was based on the West African countries sampled. The morphology of each population is characterized by the proportions of its individuals that specifically reproduce each of the three morphologies that exist in the West African subregion.

Profitable canola production depends upon an adequate supply of nitrogen (N) and sulfur (S) fertilizer. However, agricultural soils in eastern Canada seldom receive S fertilizer and rely on inherent S supply from biogeochemical and anthropogenic sources, which could be a yield-limiting factor for canola. The objective of this study was to document N × S fertilizer interactions to develop site-specific best management practices for canola production in eastern Canada. Factorial field experiments were conducted for four consecutive cropping seasons at five locations across eastern Canada. The N × S and N × S × environment interactions on seed yields and yield-related traits were visualized with the graphical analytical genotype and genotype-by-environment biplot tool. The highest seed yield was achieved with 150 kg N ha−1 together with 20–40 kg S ha−1 in 15 of the 19 test site-years. Seed yield was closely related to harvest index and number of seeds pod−1. Fertilizing canola with 20 kg S ha−1 enhanced the nitrogen use efficiency (NUE) of canola receiving 75 kg N ha−1, but the benefit of S fertilizer on NUE was negligible when N fertilizer rates increased to 150 kg N ha−1. Since canola yield response to fertilizer inputs varied from one site to another, due to the variation in environmental and soil conditions, we conclude that N × S fertilizer recommendations for canola production need to be developed on a site-specific basis in eastern Canada.

Garden pea is an important off-season vegetable in the hills of North Western Himalayas that provides high remuneration to growers. Lack of high yielding wider adaptive varieties restricts its productivity. To identify high yielding stable genotypes across environments, 48 lines were evaluated in Alpha Lattice design over seven diverse environments spreading in five locations from sub-tropical to dry temperate conditions of Himachal Pradesh during winter 2016–2017 (5 environments) and one location each during summer 2017 and winter 2017–2018. The highest mean pod yield over environments was produced by SP-3 (83.35 g) which was 20% higher over check Pb-89 while SP-6 (79.45 g) and SP-22 (76.90 g) got second and third rank with significant increase of 15 and 11% for pod yield over the check, respectively. The joint regression analysis depicted significant G × E (linear) interaction for pods/plant and pod yield/plant. Of the seven genotypes depicting stability for pod yield, SP-6 showed stability (bi = 1 and S2di = 0) for all the traits whereas SP-22 showed the same for seeds/pod and shelling percentage. G + GE biplot described Dhaulakuan as the most representative and discriminating environment for pod yield. In the mean vs. stability GGE biplot, SP-6, SP-22 and SP-17 were highly stable while SP-3 possessed medium stability. ‘Which won where’ polygon view represented SP-3, SP-6 and SP-22 as most stable for yield and pod attributes across environments, constellated into majority of the environments and can be released for commercial cultivation.

The evaluation of genetic diversity in a gene pool contributes to the effective selection of genotypes and truncates the breeding time. In the present study, 96 durum wheat genotypes were evaluated for (1) genotypic diversity using two DNA marker systems: CAAT box-derived polymorphism (CBDP) and inter-simple sequence repeats (ISSR) markers and (2) phenotypic diversity using several drought-adaptive traits under rainfed conditions for two cropping seasons. Our results revealed that the ISSR primers produced 99 bands across the genotypes, the average of which was 6 fragments per primer, whereas CBDP primers generated 70 polymorphic bands, with an average of 5.3 fragments per primer. The values of marker index (MI) and polymorphism information content (PIC) indicated that CBDP markers were more efficient than ISSR markers for detection of genetic diversity in durum wheat. The average of PIC values for the CBDP and ISSR markers were 0.40 and 0.23, respectively. Based on the values of Shannon index (I) ICARDA population had a higher than CIMMYT population and the heterozygosis values confirmed these results. Dendrogram was created with a neighbor-joining clustering method. The studied genotypes were divided into five and seven groups based on data from the CBDP and ISSR markers, respectively, which was supported by principal coordinate analyses. The results of genotype by trait biplot analysis showed different patterns of interaction accessions and traits across years. High level of diversity among the studied accessions based on each studies trait was observed.

Among the tropical tuber crops, cassava (Manihot esculenta Crantz) deserves special attention as regards to its higher biological efficiency in terms of dry matter production which incidentally implies to the higher amount of nutrient extraction from the soil resulting in better response to the application of manures and fertilizers. Among the major nutrients, Potassium (K) is considered as the key nutrient for cassava owing to its influence both in tuber yield and tuber quality. The above facts as well as the availability of sufficient cassava genotypes in the germplasm collection of ICAR-CTCRI made us to initiate research work to screen cassava germplasm including the pre breeding lines. The objective being to identify K efficient genotypes which can yield well under limited availability of K so that the external application of K can be reduced. This paper describes the wide variation noticed during the pre evaluation of 83 elite genotypes which was done as a prelude in the screening and identification of K efficient genotypes. The characters studied were tuber yield, tuber characters, plant dry matter percentage, plant K content, tuber quality (starch, cyanogenic glucosides) attributes, physiological efficiency and plant biometric characters. The variation among the genotypes for the above traits was assessed by making some yardstick for classification which in turn helped in determining the percent distribution of genotypes in each category. The variation among the genotypes were further affirmed through principal component analysis, wherein the first five components explained more than 77% of variability and the cluster analysis performed grouped these genotypes into five clusters. The biplot showed the traits which are closely linked to the genotypes. The dendrogram constructed indicated similar genotypes to that of the clusters to the extent of more than 50% revealing the association of members with similar traits in clusters and dendrograms. The study helped in establishing the drastic variation among the genotypes along with identification of six genotypes viz., Aniyoor, 7 Sahya (2), 7 III E3-5, W-19, CR 43-8, 6-6 for further detailed experimentation to identify K efficient genotypes.

Inadequate information is available on trait relations and profiles of sorghum genotypes, yet this information is vital for precise decisions to be undertaken in breeding programs. Here, 17 sorghum experimental lines were evaluated together with three checks at five locations, representing the major sorghum production environments in Zimbabwe. Across site analysis of variance (ANOVA) showed significant genotypic effects on grain yield (GYD) as well as the other traits, including panicle length (PL) and stem diameter (SD). Distance-based clustering indicated the possibility of indirectly selecting for GYD using; SD, exertion (EXSTN), panicle length (PL), panicle width (PW) and number of leaves (NL). In addition, the vector view of the genotype-by-trait (GT) biplot also revealed strong correlations between GYD and, PW, SD and FYD, as well as the other physiological traits including, days to male flowering (DMA) and days to physiological maturity (DPM). Genotypes superior for a combination of traits were, G6, G7, G11, G18 and G20, which were strong for GYD, PL and PW, as well as, G5 which was strong for sugar content (SC), number of leaves (NL) and SD. Genotypes 15, 16 and 17, were specifically strong for GYD whereas, genotypes 4 and 9 were strong for FYD. Overall, results revealed the key traits which can be considered singularly or in combination, when selecting suitable sorghum genotypes, either for feed or food purposes, under arid and semi-arid conditions. This information is vital for decision making in sorghum breeding programs.

Climate variability and associated droughts are major environmental factors limiting crop productivity worldwide. Identification and better understanding of factors influencing genotype × environment (GE) interaction in drought-prone environments will allow breeders and producers to improve crop productivity. The objectives of this study were to identify genotypic and climatic factors responsible for GE interactions in durum wheat yield trials under highland cold and moderate cold rainfed areas of Iran. Field experiments were carried out using 20 durum wheat genotypes, differing in growth habit, in three highland rainfed research stations for three cropping seasons (2015–2018). Environments were characterized by climatic co-variables measured during the three seasons. Genotypes were described by co-variables related to phenology, agronomy and disease resistance. Possible factors influencing GE interaction were examined by factorial regression (FR), partial least squares (PLS) regression and the additive main effects and multiplicative interaction (AMMI) models. The results indicated that both AMMI IPCA1 and IPCA2 scores had positive and negative values, resulting in crossover GE interaction and leading to inconsistent yield performance of genotypes across environments. The AMMI, PLS and FR identified similar genotypic and climatic variables that explained a large proportion of the GE interaction for grain yield. Based on the results, the climatic variables of average temperature, rainfall, relative humidity, minimum and maximum temperature, and genotypic variables of heading date, plant height and 1000-kernel weight were among the most important factors responsible for differential genotype adaptation. The PLS biplot showed that the genotypic responses to environmental covariates depended strongly on the growth habit type. This information can contribute toward the identification and biological understanding of adaptive characteristics relevant for durum wheat breeding in highland cold rainfed conditions of Iran and facilitate cultivar recommendation at eco-regional level. In conclusion, the AMMI, PLS and FR complement each other and the PLS biplot offered further interpretations of the GE interaction including differential genotype adaptation.

The variable cowpea productivity across different environments demands evaluating the performance of genotypes in a breeding program prior to their release. The aim of this study was to assess yield stability of eight cowpea advanced breeding lines selected from participatory varietal selection in multilocational trials, and to identify mega-environments for cowpea production in Ghana. The genotypes were evaluated across five environments in 2016 and 2017 in randomized complete block design with three replications. The GEA-R version 4.0 software was used for genotype main effect plus genotype by environment interaction (GGE) biplot analyses. Analysis of variance (PROC GLM of SAS using a RANDOM statement with the TEST option) detected significant variations for location, year, genotype, environment, and their interactions. The results showed that the yield performances of the cowpea genotypes were highly influenced by genotype × environment interaction effects. The principal component 1 (PC1) and PC2 were significant components which accounted for 46.75% and 22.84% of GGE sum of squares, respectively. We showed for the first time, two mega-environments for cowpea production and testing in the major cowpea production agro-ecologies in Ghana. The genotypes SARI-6-2-6 and IT07K-303-1 were adapted to Damongo, Nyankpala, and Tumu, whereas SARI-2-50-80 was adapted to Yendi and Manga. The best ranking location was Damongo followed by Tumu, and Nyankpala. The high-yielding genotypes, IT86D-610, IT10K-837-1, IT07K-303-1, and SARI-2-50-80 had significant higher grain yields than the check (Bawutawuta) and were recommended for release as cultivars (or as breeding lines) to boost cowpea production in Ghana.

Twenty-three winter wheat (Triticum aestivum L.) varieties were tested in randomized complete blocks for four seasons in two fields (sandy and loamy soil), of the Mendel University in Brno, Czech Republic. Objectives were to find genotypes combining high grain with protein yield and cover the protein content standards. Stability was assessed on the coefficient of variation (CV) of grain yield and plant height (plot-to-plot variability), the level a variety lagged behind the maximum yield attained within a block (yield-gap index), and the GGE biplot analysis. Sandy and loamy fields simulated low- and high-input agroecosystems, respectively. The sandy field averaged 5.47 t/ha grain yield and 15.25% grain protein content, while the respective values for the loamy field were 10.4 t/ha and 13.17%. In the loamy field, nine varieties failed to meet the protein content benchmark of 13% for the breadmaking industry. The CV of plant height rather than of grain yield was a good criterion to show the effects of crop variation on yield and stability. The yield-gap index constituted a good measure of general adaptability to fluctuating conditions. Some varieties showed specific adaptation to sandy or loamy soil. On basis of CV of plant height, yield-gap index and GGE biplot, there were also varieties with general adaptability. Genotypes were found to have high protein content irrespective of grain yield, so selection of varieties with good yielding performance and protein concentration appears to be a sound pursuit.

Drought is a serious global problem of agriculture. For this, an investigation was carried out with 25 wheat genotypes composed of cultivars and advanced lines to screen drought-tolerant bread wheat genotypes using multivariate analysis. The experiment was conducted in a split plot design with three replications and two treatments control and drought. The analysis of variance revealed significant differences among the genotypes and treatments for all the characters studied, viz. plant height, flag leaf collar height, flag leaf length, flag leaf breadth, chlorophyll a, chlorophyll b, proline content, number of tillers per plant, root fresh weight, shoot fresh weight and root–shoot ratio. High heritability was observed for all the traits except flag leaf length, flag leaf breadth and number of tillers per plant. Based on the genetic distances, all the 25 genotypes were grouped into three different clusters. In control conditions, cluster number I contained most tolerant genotypes and under drought conditions, cluster number III contained most drought-tolerant genotypes. In biplot, the genotypes SATYN-24, BARI Gom-24 and SATYN-2 contributed positively and correlated with number of tillers per plant, shoot fresh weight, flag leaf breadth, proline content and plant height under drought conditions. The drought susceptibility index (DSI) indicated that the genotypes BARI Gom-24 and SATYN-9 exhibited a highly drought-tolerant genotype in the present investigation. These genotypes might carry genes for drought tolerance and may be useful for further drought tolerance breeding.

Flax (Linum usitassimum L.) of family Linaceae is one of the most important crops, which has been widely used from ancient times. The aim of the study was to examine seed morphological characteristics and fatty acids differences among 13 populations of flax (11 from Iran, one from Turkey and one from USA). We studied six morphological variables of seeds in 50 replications. The methyl esters of seeds fatty acids were analyzed using GC. We detected that the flax seeds shape and color were stable among the populations, whereas ANOVA proved significant variations for all the quantitative seed morphological features. Moreover, we found the main fatty acids of the seed oil remained consistent over the ecological and geographical ranges of the populations, except for Khorasan and Turkey populations differed from the rest by their second main fatty acid. We registered that the amounts of main fatty acids differed among the populations and ANOVA test proved significant differences for most of the identified fatty acids. In addition, significant relationships were registered between some fatty acids. The populations were clustered in UPGMA tree and PCO plot into three distinct groups. CA joined plot and PCA biplot demonstrated that each group had specific type and amount of fatty acid. Therefore, we defined three chemotypes: petroselinic acid, linoleic and linolenic acids, and oleic acid. Although, studied ecological factors influenced some fatty acids amounts, populations from different phytogeographical regions clustered closely as chemotypes. This revealed that populations of each chemotype have been originated from the same diversity center, and some secondary diversity centers exist for flax in the world.

An important objective of wheat improvement programmes is to breed varieties for high yield in optimum conditions and for minimum yield reduction under stress-prone conditions such as heat and drought. Analyses of yield and its components in multiple years allow a comprehensive and comparative understanding of genetic yield potential and stress-tolerance mechanisms in the study germplasm. The present study was carried out to evaluate performance of elite varieties and landraces of spring durum wheat under different water regimes, determine the repeatability of the examined traits, and identify superior genotypes for their potential use in breeding for drought tolerance. A total of 97 accessions of spring durum wheat (T. durum Desf.) were evaluated under rain-fed and well-watered conditions in the nursery of the Centre for Agricultural Research at Martonvásár, Hungary (2011–2013). The experiments were laid out in an unbalanced, incomplete alpha lattice block design. The trait with the lowest broad-sense repeatability was seed length (0.075), while high h2 values were observed for heading date (0.89), thousand-grain weight (0.85) and the protein content (0.85). Grain yield showed moderate level of repeatability (0.53) across the three years. The principal component analysis revealed that grain yield (t/ha) is positively associated with the fertile tiller number, chlorophyll content values at early waxy ripeness stages and plant height. Based on biplot analysis, ‘DP-133′, ‘DP-017′ and ‘DP-061′ proved to be the best durum cultivars in terms of yield whereas genotypes ‘DP-011′, ‘DP-185′, 'DP-126′ and 'DP-136′ preceded them with their good yield stability.

The present study was conducted to assess the physiological and biochemical responses in the leaves of ten chickpea accessions trifurcated into moderately tolerant, intermittent and moderately sensitive on the basis of their yield losses via drought susceptibility index. Moderately sensitive accessions recorded higher decline in number of leaves and dehydrogenase activity and increased membrane permeability index (MPI) under receding moisture conditions. However, moderately tolerant genotypes, viz. GL 29078 and ICC 4958, maintained number of leaves and optimal dehydrogenase activity and lower MPI in leaves at reproductive stages by enhanced enzymatic activity of superoxide dismutase, catalase and ascorbate peroxidase that upregulated their antioxidative defense system at 75% moisture reduction levels. Furthermore, the tolerance capacity was maintained in moderately tolerant genotypes (IPCK-2009-165 and ICC 4958) due to increased proline level that acted as a positive loading variable component in principal component biplot analysis and lowered malondialdehyde content levels in leaves at receding moisture levels. Assessment of leaf tissue-specific response under lysimetric screening and its final correlation with yield adds to paramount importance and uniqueness to the current study.

Bread wheat (Triticum aestivum L.) cultivars adapted to specific environments and resistant to prevalent pathogens are preferred for obtaining high yield. This study aimed to identify wheat genotypes with superior grain yield (GY) and yield associated traits from 168 genotypes of International Maize and Wheat Improvement Center’s 13th Stem Rust Resistance Screening Nursery evaluated over two seasons during 2019 and 2020 under high disease pressure of both stem rust (SR) and yellow rust (YR) in a 21 × 8 α-lattice design with 3 replications in Kenya. Effects due to seasons were significant for YRAud, SRAud, 1000-kernel weight (TKW), days to heading (DH), plant height (PH) and number of spikelets spike−1 (SS), while genotypes and genotypes × season interaction effects were significant for all traits except number of kernels spike−1. Respectively, heritability values of 0.95, 0.93, 0.87, 0.86, 0.77 and 0.75 were observed for area under disease progress curve for SR (SRAud), YR (YRAud), TKW, DH, biomass (BM) and GY. Path analysis showed positive direct effects on GY via PH, SS, BM, and TKW. Biplot analysis identified 16 genotypes with superior desirable traits GY, BM and harvest index. The SR contributed the highest reduction in GY and TKW while YR contributed the most reduction in BM. These identified genotypes with superior GY combined with adequate resistance to both SR and YR are potentially valuable resources for improvement of locally adapted wheat cultivars.

Multi-environment trials have a fundamental role in the selection of the best genotypes across different environments before its commercial release. This study was carried out to identify high-yielding stable sunflower hybrids using the graphical method of the GGE biplot. For this purpose, 11 new hybrids along with four hybrid cultivars were evaluated in a randomized complete block design with four replications across 8 environments (combination of years and locations) during the 2018–2020 growing seasons. The mean oil yield of the environments varied from 833 kg ha−1 in E4 to 1565 kg ha−1 in E5 and the oil yield of hybrids ranged from 1085 kg ha−1 in hybrid H9 to 1565 kg ha−1 in hybrid H8. The results indicated that genotype (G), environment (E) and genotype × environment (G × E) effects were significant for oil yield. The G, E, and G × E interaction effects accounted for 64.83, 11.86, and 23.31% of the total variation, respectively. Results of biplot analysis showed that the first and second principal components accounted for 45.9% and 20.4%, respectively, and in total 66.3% of oil yield variance. GGE biplot analysis indicated two major mega-environments of sunflower testing locations in Iran. Based on the hypothetical ideal genotype biplot, the hybrids H3 and H5 were better than the other hybrids in terms of oil yield and stability, which had the highest general adaptation to all of the environments. Based on the ideal genotype from the most desirable to the most undesirable the hybrids were ranked as follows: H5 > H3 > H8 > H14 > H6 > H2 > H13 > H12 > H10 > H11 > H1 > H7 > H4 > H15 > H9. Furthermore, ranking of the environments based on the ideal environment introduced Sari as the best environment. Therefore, Sari can be used as a suitable test location for selecting superior sunflower hybrids in Iran.

Crop cultivar performance is a result of combined effects of genotype, environment and genotype × environment (G × E) interaction. To effectively generate reliable estimates of crop yield the magnitude and patterns of G × E in regional yield trials should be specified. This research aimed to (1) investigate existing possible mega-environments (ME) and suitability of test locations for winter wheat zoning, and (2) determine the role of climatic factors in clustering patterns of G × E. Winter wheat yield data from a three-year nationwide yield trial consisting of 24 genotypes grown in 24 test environments supplemented with 37 climatic factors were subjected to empirical and analytical analyses. Standard deviation-scaled genotype main effect and G × E interaction (SD-GGE) biplot methodology, factorial regression and partial least square regression were applied to both analyses. The combined ANOVA showed that the environmental effect was the main source of variation (83%), and the magnitude of G × E interaction was sixfold greater than genotype alone. The SD-GGE biplot confirmed non-repeatable patterns for grouping of test locations across years, indicating significant (P

The development of lines with high performance and stability for synthesis of superior hybrids is the most expensive and time-consuming phase in maize hybrid breeding. Several times, due to available resources, only a part of possible hybrid combinations is tested. Therefore, the breeder needs methods that allow the evaluation of genotypes untested in the field. This work was carried out with the objective of proposing a prediction model of general and specific (SCA) combining ability, and interactions with environments, associated with the use of credible regions in biplots obtained through Additive Main Effects and Multiplicative Interaction Bayesian model. Two analyses were done, in which the first one was conducted with simulated data, and the second one with real data. Credible ellipses were constructed in biplot in order to evaluate the stability of interaction effects for GCA and SCA. For the analysis of simulated data, the predictions obtained had high correlation with the real values. For the effects of GCA and SCA, the predictions kept the standard of signals and rank. The model was efficient to provide credible intervals which covered the simulated values. For the analysis of real data, estimates of GCA and SCA for all genotypes evaluated do not differ from zero. The biplots for GCA × E and SCA × E interactions allowed evaluate the genotype stability in a more accurate way and the uncertainty about interaction estimates. The model is shown as a promising tool for helping the breeder to select and recommend genotypes.

Rice production is affected by emerging problems of climate change and over-utilization of resources. To obtain consistent yield across diverse environments, a variety should have adaptability and stability to fit into various growing conditions. G×E interaction and stability performance of 59 rice lines of different maturity durations were investigated for grain yield-related traits in three environments. This study was carried out to identify stable lines for varietal development as well as to identify parental lines with stable contributing traits for further breeding programs. AMMI and GGE analysis showed significant genotype, environment, and G×E interaction indicating the presence of variability among the genotypes and environments. The G×E interaction effect showed that the genotypes responded differently to the variation in environmental conditions or seasonal fluctuations and explained that most of the traits were contributed mainly by genotype, followed by environment and their interaction. As per AMMI biplot analysis, environment1 was identified as the best suited for potential expression of grain yield and related traits. Results of stability analysis revealed that early and mid-early genotypes NH776, NH4371, 27K, NH686, 258S, NH219, and Tellahamsa were identified as the best stable genotypes across all the three seasons for single plant grain yield and hence suitable for wider environments. These selected genotypes can be suggested for hybridization in further breeding programs to develop early genotypes with high yield. The stable early and mid-early lines with high yield potential will be tested in multi-location trials for commercial cultivation.

Increased temperature caused by climate change is exerting negative impacts on productivity of cotton crop. Therefore, breeding cultivars tolerant of high temperature are need of the time. Realizing the situation, 154 accessions of upland cotton were sown under alpha lattice design in three replications in two sowing dates. The first sowing date was planned to coincide the flowering stage with maximum annual temperature (± 48 °C) of the region. The data were recorded at appearance of first flower for physiological traits like viability of pollen grains and cell membrane thermostability. Enzymatic and non-enzymatic antioxidants, i.e., peroxidase activity and proline contents were also quantified along with hydrogen peroxide. K-means cluster and biplot analysis revealed the differential response of genotypes. FH-Lalzar, IUB-13, GH-Mubarak and Shahkar exhibited higher values for antioxidants and physiological traits. The yield and fibre quality of these genotypes were also superior as compared to others. It was suggested that diversity in germplasm for aforementioned traits can be utilized in further breeding programs.

The GGE biplot tool has potential for determining combining ability effects, identifying distinct heterotic groups and efficient testers in a line × tester study. However, its use for such analysis has not been adequately explored. The objectives of this study were to (i) assess combining ability of extra-early maturing lines (80–85 days to physiological maturity) and testers for grain yield (ii) classify lines into heterotic groups and (iii) identify most efficient testers using GGE biplot. Sixty-three lines crossed to four testers were evaluated under Strga-infested, drought and nonstress environments for 2 years in Nigeria. Results of GGE biplot analyses of combining ability and heterotic patterns of yield of lines, grouping and identification of testers were close to those of the conventional line × tester method. Testers TZEEI 13, TZEEI 21 and TZEEI 29 were highly efficient in grouping lines under stress environments while testers TZEEI 21 and TZEEI 29 were best under nonstress environments. The GGE biplot identified tester TZEEI 13, TZEEI 21 and TZEEI 29 as most efficient across stress environments and TZEEI 21 and TZEEI 29 across nonstress environments.

Genotype selection based on multiple traits in multi-years is frequently influenced by unpredictable rainfed conditions. The main objective of the study was to apply the new methodology of genotype by yield*trait (GYT) biplot for genotype selection and trait profiles in durum wheat genotypes based on multi-traits and multi-year data under rainfed conditions of Iran. A superiority index was applied based on GYT table for ranking of genotypes by the mean of all traits. The GYT biplot ranked the genotypes based on their levels in combining yield with other key traits. Grain yield was combined with target traits and showed the strengths and weaknesses of each genotype. Based on GYT-biplots the relationships among the studied traits were not repeatable across years, but they facilitated visual genotype comparisons and selection. The breeding lines G13, G10 and G15 ranked as the best in combination of the morph-physiological traits i.e., SPAD-reading, early heading, flag-leaf length and number of grain per spike with grain yield under rainfed conditions. The results indicate that there is a potential for simultaneous improvement of some characteristics of durum wheat under rainfed conditions. The GYT biplot was a useful tool for exploring the combination of yield with traits and trait profiles of the durum genotypes to obtain high genetic gains in the durum breeding programs.

A study of combining ability for improving bread wheat yield and yield components was carried out via genotype plus genotype × environment (GGE) biplot. Six bread wheat genotypes were used to obtain F1 in a diallel cross matings at the Gachsaran Field Station, Dryland Agricultural Research Institute during 2012–2013 cropping seasons. Analysis of variance indicated significant effects of genotypes, general combining ability (GCA) and specific combining ability (SCA) for all of the studied traits. The highest values of plant height (108.15 cm), peduncle length (33.95 cm) and grain yield (265.5 g m−1) were obtained in g6 (DAMARA-6 ICW99-0427-8AP-0AP-0AP-3AP-0AP). GGE biplot analysis showed that g4 (Kouhdasht) and g6 (DAMARA-6 ICW99-0427-8AP-0AP-0AP-3AP-0AP) were as the best general combiners for days to maturity, plant height and grain yield, whereas g1 (Karim) had the highest GCA effects for spike length and thousand grain weight, and g3 (Aflak) showed the highest GCA effects in terms of peduncle length. Meanwhile, g6 showed large SCA effects for thousand grain weight and grain yield, while g4 had high SCA effects for spike length. g5 (PASTOR/2*SITTA//PBW343*2/KUKUNACMSS04Y00333S-099Y-099ZTM-099Y-099 M-3WGY-0B) had large SCA effects for peduncle length. Because of significant effects of mid-parent heterosis for grain yield, g4 × g6 was considered as the best possible cross for improvement of this trait. Based on the results of present study, GGE biplot indicated good potential for identifying suitable parents and heterotic crosses and the best hybrids according to diallel mating design.

A total of twenty-five grass pea (Lathyrus sativus L.) genotypes of released varieties, advanced lines, mutants and local collections were explored in this study. These genotypes were cultivated for two succeeding years in three different locations namely red lateritic zone (Shekhampur), gangetic alluvial zone (Kalyani) and saline zone of Sundarban region of west Bengal (Kakdwip) to evaluate the performance on the basis of yield and quality traits. The stability of the genotypes was established by AMMI and Biplot analysis. It was found that the neurotoxin content of grass pea, β-L-oxalyl-2,3diaminopropionic acid (β-ODAP), did not show any difference under various environmental conditions and the gangetic alluvial zone was proved to be the ideal test location for grass pea genotypes. The BK-37-2 advanced line was found to be the most stable genotype in respect of yield under all the tested environments and can be used in future breeding programmes.

Sixteen pongamia families were evaluated in a field experiment for eight consecutive years in dryland conditions to identify stable, high-yielding families. The trial was conducted in a randomized complete block design with three replications. Each family, consisting of nine trees per replication, was planted at a spacing of 3 m × 3 m. Yield stability was analyzed using (1) Eberhart and Russel’s regression coefficient (βi) and deviation from regression ($$S_{\text{d}}^{2}$$), (2) Wrike’s ecovalence ($$W_{i}$$); (3) Shukla stability variance ($$\sigma_{i}^{2}$$); and (4) Piepho and Lotito’s stability index ($$L_{i}$$). Families were also analyzed for adaptability and stability using AMMI and GGE biplots graphical methods. The study revealed significant variances due to family and family × year interaction for pod and seed yield. Families performed differently and ranked differently across years. The performance of families was influenced by both genetic factor and environmental conditions in different years. Among families tested, TNMP20, Acc14, TNMP14 and Acc30 were high yielders for pods, and Acc14, Acc30, TNMP6, RAK19 and TNMP14 were high for seed yield. According to the Eberhart and Russell model, Acc30, TNMP14 and TNMP3 were stable across years. In the graphical view of family × year interaction based on AMMI methods, TNMP3, TNMP4 and TNMP14 had greater stability with moderate seed yield, and Acc14 and Acc30 had moderate stability with high seed yield. On the other hand, GGE biplots revealed Acc14, Acc30 and TNMP14 as high yielders with moderate stability. AMMI and GGE biplots were able to capture nonlinear parts of the family × year interaction that were not be captured by the Eberhart and Russel model while also identifying stable families. Based on different methodologies, Acc14, Acc30 and TNMP14 were identified as high yielding and stable families for promoting pongamia cultivation as a biofuel crop for semi-arid regions.

Geochemical pattern recognition and anomaly mapping are always involved in the fields of environmental and exploration geochemistry. Principal component analysis (PCA) and factor analysis (FA) are most commonly used to reveal underlying geochemical associations for the purpose of spatial distribution pattern analysis. However, the methods of PCA and FA cannot eliminate correlations between different principal components/factors, meaning that geochemical associations revealed by PCA or FA could be simultaneously influenced by two or more principal components/factors, as can be observed from biplot analysis. Such problem provides a challenge for interpretation of geochemical/geological processes. In the present study, we demonstrated a simple method, termed compositional balance analysis (CoBA), to interpret critical geochemical/geological processes. Comparative studies between CoBA and compositional factor analysis, as well as data- and knowledge-driven CoBA, were considered to discuss the advantage and practicability of the CoBA in geochemical pattern recognition and anomaly mapping based on a case study in the Nanling belt, South China. The results indicate that the CoBA has greater efficiency in enhancing weak or concealed geochemical anomalies and suppressing spurious geochemical anomalies relative to multivariate dimensionality reduction analysis; especially, knowledge-driven CoBA provides more robust interpretation of geochemical/geological processes relative to data-driven CoBA.

Bael is a medicinal cum fruit tree with multipurpose utility and propagated mostly through seeds. It is mostly found in India, Sri Lanka, Myanmar, Bangladesh, Thailand and China. Focus on collection of bael variability has increased in recent times with an aim towards their utilization as fresh or made into ‘Sharbat’, one of the most popular drinks in the Indian. Its lots of evidence have showed immense potential of nutritional and medicinal properties used in various ethnic societies. The present investigation was carried out to exploit genetic variability in bael fruits. Seventy-five genotypes were characterized for sixteen fruit traits viz. fruit weight, fruit length, fruit width, skin weight, no. of seed, seed weight, pulp weight, skin per cent, seed per cent, pulp per cent, skin thickness, fruit volume, TSS, acidity, reducing sugar and total sugars during 2015. Observations of growing seedling trees showed rich genetic variations regarding their fruit characteristics. The fruit characteristics, viz., fruit weight ranged from (315.20–1608.65 g), fruit length (81.39–173.43 mm), fruit width (89.76–136.35 mm), skin weight (88.62–358.07 g), number of seed (37.67–195.40), seed weight (7.48–54.33 g), pulp weight (201.17–1243.87 g), skin % (9.59–42.83%), seed % (0.97–7.97%), pulp % (53.72–89.33%), skin thickness (1.43–4.10 mm), volume of fruit (285.00–1555.00 cc), TSS (24.40–47.80°Brix), acidity (0.15–0.40%), reducing sugar (0.37–11.90 mg/100 g) and total sugars (7.14–20.83 mg/100 g) among the different genotypes. On the basis of overall assessment, one genotype, ICAR-RCER BS 6/1 was found to be the most promising. Based on fruit properties, principal component analysis (PCA) was performed to qualitatively and quantitatively discriminate the germplasm difference. Eight principal components, which contribute 94.80% of the total variability, were selected for analysis. Biplot between PC1 and PC2 showed that genotypes namely ICAR-RCER BS 6/1, 18/2, 25/5, 21/1, 17/3, 26/1, 18/5, 1/11, 8/1 and 14/4 were very different from each other.

Heat events during the reproductive stages of rice plants induce great yield losses. Cultivating heat-tolerant varieties is a promising strategy for guaranteeing grain security under global warming scenarios. Most heat-tolerant rice genotypes were identified under heat during the flowering stage, but it is unclear whether these currently screened heat-tolerant rice genotypes maintain stable high grain yields when heat stress occurs during the other reproductive stages. In the present study, two notable heat-tolerant rice cultivars, Nagina22 and Shanyou63, and one typical heat-sensitive cultivar, Liangyoupeijiu, were evaluated for their yield response and yield stability under heat treatments during the panicle initiation, flowering, and grain filling stages during 2010–2014. Our results revealed that rice cultivars respond differently to heat stress during different reproductive stages. Nagina22 was the most tolerant to heat stress during the flowering and grain filling stages but was susceptible during panicle initiation; Shanyou63 was the most tolerant to heat stress during panicle initiation and grain filling and was moderately tolerant to heat stress during the flowering stages. Genotype and genotype-by-environment interaction biplot yield analysis revealed that Shanyou63 exhibited the highest stability in high grain yield, followed by Nagina22, and Liangyoupeijiu exhibited stable low grain yield when experiencing heat stress across the three reproductive stages. Our results indicate that the heat tolerance of different rice cultivars depends on the reproductive stage during which heat stress occurs, and the effects manifest as reductions in grain yields and seed setting rates. Future efforts to develop heat-tolerant varieties should strive to breed varieties that are comprehensively tolerant to heat stress during any reproductive stage to cope with the unpredictable occurrence of future heat events.

Papaya is one of the most important fruit crops worldwide and its production depends on the availability of varieties that meet the consumer market demands. This study aimed to evaluate papaya inbred lines and select the best lines for fruit quality. A population of 97 lines of F5 generation, that was conducted via Single Seed Descent method from the F2 generation and derived from the crossing between Sekati and JS-12 genotypes of the heterotic group Formosa, were evaluated for nine morphoagronomic traits related to fruit quality. The data set was submitted to GT biplot and Pearson’s correlation analyzes using the R software. According to the results, the lines 96, 61, 39, 1 and 88 were indicated as favorable allele sources for the traits of average fruit weight, pulp volume, fruit firmness, pulp yield, and soluble solids, respectively. Lines 107, 19, 61 and 63 were indicated as ideotypes for per se use. Effectively, the application of the multivariate graphical approach GT biplot provides a practical and efficient new way to identify superior genotypes in papaya breeding programs.

Tan spot, caused by Pyrenophora tritici-repentis, is a major foliar disease of wheat in Kazakhstan. This study evaluated 103 winter wheat genotypes for tan spot resistance and high-productivity traits in the field in two years. Entries were also characterized using the molecular marker Xfcp623, indicative of Tsn1 gene conferring sensitivity to Ptr ToxA. The proportion of entries insensitive to Ptr ToxA was relatively high (71%). Forty-eight entries with the lowest tan spot severity in the field were confirmed to be insensitivity to Ptr ToxA in the molecular screening. Entries which were resistant under field conditions had similar level of seedling resistance. Principal component analysis biplots showed, that all spike productivity traits were highly correlated. Days to heading (DH) and tan spot severity, as well as the normalized difference vegetation index and DH were strongly correlated. Thousand kernels weight (TKW) and plant height were highly correlated and both were negatively correlated with DH and tan spot severity, indicating that taller cultivars tended to be more resistant. The Xfcp623 negative entries had lower disease severity (by about 40%), flowered up to 2 days later than entries with Tsn1 and had significantly more spikelets per spike, number of grains per spike, TKW and grain weight/spike. The results of the study will be important for increasing the efficiency of breeding based on the elimination of the genotypes with dominant allele Tsn1. Of the 103 entries evaluated, 28 can be directly used in breeding programs to improve tan spot resistance and productivity of winter wheat.

Common bacterial blight (CBB) of mungbean (Vigna radiata [L.] Wilczek var. radiata) is a major limitation to mungbean production in semi-arid areas of the world where mungbean is a major crop. Deployment of resistant varieties is a significant sustainable strategy for controlling CBB in marginal production systems. The objective of this study was to identify sources of resistance and the stability of mungbean landraces to CBB attack across drought-endemic environments. A total of 240 mungbean genotypes were evaluated for CBB resistance and performance of agronomic traits in an alpha lattice design at four locations for 2 years (2019, 2020). Data were subjected to residual maximum likelihood (REML) analysis to partition variance components attributed to main effects and interactions, respectively. REML analysis revealed significant main effects for genotype, environment (combination of cropping season and location) and genotype-by-environment interaction (p

The cowpea is produced in different environmental conditions in several regions of Brazil. It is crucial to select and develop cultivars that attend to the regional requirements with high productivity, adaptability, and stability, due to the interaction between the genotype and the environment. This research aimed to select strains of cowpea for the simultaneous presence of high genotypic productivity, adaptability, and stability in the North-eastern region of the state of Rio de Janeiro (Brazil) by the GGE-Biplot method. The study assessed 27 genotypes: 23 strains and four cultivars, in six environments of the North-eastern region of the state of Rio de Janeiro, during the years 2016, 2017, and 2018. The experimental design was a randomized block design with four repetitions. The GGE-Biplpot method assessed the genotypic adaptability and stability, by the use of the statistical software R. The interaction between the environment and the genotypes was complex, and the general average for the productivity of the grains was 1231.98 kg/ha. GGE-Biplot method was efficient in identifying the best strains to be suggested for the use in the North-eastern region of the state of Rio de Janeiro. The strains (9), (3), and (6) were classified as ideotypes due to their superior performance compared to the general average, and their stability. Their performance overcame the control cultivars BRS Tumucumaque, BRS Imponente, BRS-Itaim e CB-27.

Genetic biofortification is a cost-effective strategy to address iron (Fe) and zinc (Zn) deficiencies prevalent worldwide. Being a rich and cheap protein source, chickpea, a food legume grown and consumed across the globe, is a good target for biofortification. Nineteen popular commercial cultivars of India were analysed for Fe and Zn content at four locations representing different agro-climatic zones to study the genotypic and genotype × environment interactions on Fe and Zn. Distribution of phytic acid (PA), an important anti-nutrient that chelates and reduces the mineral bioavailability, was also analysed. Influence of other agronomic traits like days to flowering, plant height and 100 seed weight on Fe and Zn content was also studied. All the traits showed significant G and G × E interactions; however, the magnitude of variance of GXE was lesser than that of G alone. Genotype + genotype-by-environment and genotype-by-trait biplots were used to assess the relations between different environments, genotypes and traits. Iron and zinc content showed positive correlation between them indicating a possibility of their co-selection in breeding. A negative correlation between Zn and PA was observed. However, there was very low variability for PA content in the cultivars under study, indicating that moderate PA is naturally selected in these cultivars during breeding. Despite significant GXE interactions, cultivars with high Fe (> 70 µg/g) and Zn content (> 40 µg/g) at three out of four test locations were identified. Such genotypes will be useful in breeding programs for enhancing mineral micronutrient content and understanding the molecular mechanisms governing their differential uptake.

The identification of stable and adaptable high yielding cowpeas (Vigna unguiculata (L.) Walp.) and highly discriminative environments will be useful for elite cultivar development in South Africa. Two statistical models, the Additive main effects multiplicative interaction (AMMI) and the genotype, genotype by environment biplot analysis have been used extensively to identify superior genotypes and ideal testing environments. Hence, the objective of this study was to identify elite cowpea lines and testing environments using the two models to inform future cultivar development strategies. Fifteen cowpea genotypes were evaluated for yield performance and stability across 3 different locations during 2016 and 2017 growing seasons in South Africa. Genotype main effects were significant for grain yield, while genotype × environment interaction effect was insignificant for grain yield. However, genotypic perfomance for grain yield was significantly affected by seasonal variability. The AMMI analysis of variance showed that genotypes (G), environments (E) and their interaction were significant for grain yield. The G and GE effects accounted for about 10% of the total variation in grain yield, while the environment accounted for 66%. The high yielding genotypes, Vigna Onb, TVU-5431 and Kisumu mix, were adapted to Mafikeng and Potchefstroom sites. Kisumu mix, followed by Vigna Onb, were the most stable genotypes, while Veg cowpea 1, Veg cowpea dacama cream and Veg cowpea 2 were the least stable genotypes across the three sites and seasons. The analysis also showed that Environment 4 (Potchefstroom) was the most ideal site for cowpea production among the test sites.

Experimental genotype selection in a forage crop cultivar development program is complex because the ultimate aim is increase performance and sustainability in animal production. The objectives of this study were (1) to identify traits with greater direct and indirect effects on yield of high nutritional value leaf mass (NLM) in Urochloa sp. hybrids and (2) to assess indirect gain from selection for these traits with greater effects through selection indexes and by genotype by yield*trait (GYT) biplot analysis using NLM as a basic variable. We evaluated 96 interspecific hybrids, from a gene pool among Urochloa ruziziensis, Urochloa brizantha and Urochloa decumbens species, in an experiment laid out in a randomized complete block design. A series of agronomic and nutritional value traits were measured. Path analysis and GYT were performed using NLM as the basic variable, and different strategies using selection indexes were adopted. The leaf dry matter and field green weight (FGW) traits exhibited greater direct effects on NLM. All selection strategies proved to be effective in obtaining gains in the NLM variable. GYT analysis and the selection index with weights corresponding to the relative direct effects to each trait on the NLM were the strategies that resulted in a greater correlated response for NLM. Indirect selection for NLM via FGW or the index with the FGW and regrowth capacity traits proved to be viable strategies for selection of Urochloa genotypes in the initial stages of the breeding cycles due to their practicality and lower requirement regarding traits to be measured.

To improve multi-environmental trial (MET) analysis, a compound method—which combines factor analytic (FA) model with additive main effect and multiplicative interaction (AMMI) and genotype main effect plus genotype-by-environment interaction (GGE) biplot—was conducted in this study. The diameter at breast height of 36 open-pollinated (OP) families of Pinus taeda at six sites in South China was used as a raw dataset. The best linear unbiased prediction (BLUP) data of all individual trees in each site was obtained by fitting the spatial effects with the FA method from raw data. The raw data and BLUP data were analyzed and compared by using the AMMI and GGE biplot. BLUP results showed that the six sites were heterogeneous and spatial variation could be effectively fitted by spatial analysis with the FA method. AMMI analysis identified that two datasets had highly significant effects on the site, family, and their interactions, while BLUP data had a smaller residual error, but higher variation explaining ability and more credible stability than raw data. GGE biplot results revealed that raw data and BLUP data had different results in mega-environment delineation, test-environment evaluation, and genotype evaluation. In addition, BLUP data results were more reasonable due to the stronger analytical ability of the first two principal components. Our study suggests that the compound method combing the FA method with the AMMI and GGE biplot could improve the analysis result of MET data in Pinus teada as it was more reliable than direct AMMI and GGE biplot analysis on raw data.

Monoculture and use of disease resistant varieties on large scale usually leads to selection of new pathogen races able to overcome the resistance. The use of variety mixtures can significantly improve the control of the disease and provides stable yield among different environments. The objective of this study was to assess genotype by environment interaction for grain yield in spring barley genotypes grown in two places different in terms of soil and meteorological conditions by the additive main effects and multiplicative interaction model. The study comprised 25 spring barley genotypes (five cultivars: Basza, Blask, Skarb, Rubinek and Antek, and 20, two- and three-component mixtures), analyzed in eight environments (compilations of two locations and four years) through field trials arranged in a randomized complete block design, with three replicates. Grain yield of the tested genotypes varied from 32.88 to 74.31 dt/ha throughout the eight environments, with an average of 54.69 dt/ha. In the variance ...

The aim of this study was to evaluate oat genotypes for grain yield and yield components in both 2014-2015 and 2015-2016 growing seasons using GGE biplot analysis. Experiments were laid out according to lattice design. Biomass at harvest, grain yield, number of grain per panicle, weight of grain per panicle, flag leaf width, flag leaf height, plant height, stem diameter, thousand kernel weight, time of panicle emergence, harvest index, panicle length, and spikelet per panicle were evaluated for 56 oat genotypes. GGE biplot graphics of the first and second years explained 54.4 and 55% of total variation, respectively. Grain yield, number of grains per panicle, and weight of grain per panicle were closely and positively associated in both growing seasons. Recently registered cultivar Sari and lines 26, 29, and 30 were found as promising genotypes for Canakkale conditions. Traits of genotype at different growing seasons can be visually studied using different genotype-by-trait (GT) biplots.