Improving the efficiency of wheat breeding experiments using alpha lattice design over randomised complete block design

Kumar, Arun; Bharti, Baudh; Kumar, Jaydev; Bhatia, Dharminder; Singh, Gyanendra; Jaiswal, J. P.; Prasad, Rajendra

doi:10.1007/s42976-020-00014-3

Cited by 6 publications

(5 citation statements)

References 8 publications

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“…Although the use of two different experimental designs in Ecuador and Europe, estimations of highly heritable traits were fairly consistent across trials. An accurate estimation of genotype and environmental effects, generally considered more precise on large trials when using incomplete designs (Kumar et al, 2020), was here guaranteed for the plots with a RCB design through the use of spatial correction. In agreement with other studies, we observed high heritability values for flowering time (Harzic et al, 1996).…”

Section: Discussionmentioning

confidence: 99%

Diversity and Agronomic Performance of Lupinus mutabilis Germplasm in European and Andean Environments

et al. 2022

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The introduction of Lupinus mutabilis (Andean lupin) in Europe will provide a new source of protein and oil for plant-based diets and biomass for bio-based products, while contributing to the improvement of marginal soils. This study evaluates for the first time the phenotypic variability of a large panel of L. mutabilis accessions both in their native environment and over two cropping conditions in Europe (winter crop in the Mediterranean region and summer crop in North-Central Europe), paving the way for the selection of accessions adapted to specific environments. The panel of 225 accessions included both germplasm pools from the Andean region and breeding lines from Europe. Notably, we reported higher grain yield in Mediterranean winter-cropping conditions (18 g/plant) than in the native region (9 g/plant). Instead, North European summer-cropping conditions appear more suitable for biomass production (up to 2 kg/plant). The phenotypic evaluation of 16 agronomical traits revealed significant variation in the panel. Principal component analyses pointed out flowering time, yield, and architecture-related traits as the main factors explaining variation between accessions. The Peruvian material stands out among the top-yielding accessions in Europe, characterized by early lines with high grain yield (e.g., LIB065, LIB072, and LIB155). Bolivian and Ecuadorian materials appear more valuable for the selection of genotypes for Andean conditions and for biomass production in Europe. We also observed that flowering time in the different environments is influenced by temperature accumulation. Within the panel, it is possible to identify both early and late genotypes, characterized by different thermal thresholds (600°C–700°C and 1,000–1,200°C GDD, respectively). Indications on top-yielding and early/late accessions, heritability of morpho-physiological traits, and their associations with grain yield are reported and remain largely environmental specific, underlining the importance of selecting useful genetic resources for specific environments. Altogether, these results suggest that the studied panel holds the genetic potential for the adaptation of L. mutabilis to Europe and provide the basis for initiating a breeding program based on exploiting the variation described herein.

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Section: Discussionmentioning

confidence: 99%

Diversity and Agronomic Performance of Lupinus mutabilis Germplasm in European and Andean Environments

et al. 2022

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“…For statistical analysis, all data of two years (2019-2020 and 2020-2021) were combined and data are expressed as the mean. The properties examined in the study were analysed by SAS (1998) software according to the 6×6 Alpha Lattice Design (Patterson and Williams, 1976;Kumar et al, 2020). The mean comparison among cultivars was obtained by using the Tukey test.…”

Section: Discussionmentioning

confidence: 99%

GRAIN - BRAN QUALITY PARAMETERS and AGRONOMIC TRAITS of BREAD WHEAT CULTIVARS

ERBAŞ KÖSE,

MUT,

KARDEŞ

et al. 2023

Turkish Journal of Field Crops

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Wheat (Triticum avestivum L.) has a wide adaptation limit and it is used as an important source of essential nutrients for both humans and animals. Wheat bran is also a by-product of the milling of wheat grain. It has a unique nutritional composition due to the amount and quality of proteins, mineral content and B complex vitamins content and dietary fiber content. One of the aims of this study was to determine the grain yield, yield components and quality traits of 36 wheat cultivars between 2019-2020 and 2020-2021. The other aim was to determine the nutritional properties of the bran obtained from these cultivars. Plant height, spike length, number of spikelets per spike, number of grains per spike, grain yield, thousand grain weight, test weight, wet gluten and sedimentation value traits were determined only in the whole grain, while ash content, protein content, starch content, fat content, acid detergent fiber, neutral detergent fiber, potassium, phosphorus, and magnesium traits were determined both in the whole grain and in the bran. It is expected that the data obtained in this study will be reported in the literature, evaluated in terms of product quality and taken into account in breeding programs.

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“…The detailed information about the association panel is provided in Additional file 1 : Tables S1 and S2. The experiments were carried out at the Kheirabad Agricultural Research Station (36°31′51.7″N and 48°45′29.9″E) in Zanjan province during the 2017–2018 cropping season using two separate alpha lattice designs [ 31 ] with two replications for each. The plots were 1 m in length, 1 m in width, and 0.5 m apart.…”

Section: Methodsmentioning

confidence: 99%

A simple, cost-effective high-throughput image analysis pipeline improves genomic prediction accuracy for days to maturity in wheat

et al. 2020

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Background High-throughput phenotyping and genomic selection accelerate genetic gain in breeding programs by advances in phenotyping and genotyping methods. This study developed a simple, cost-effective high-throughput image analysis pipeline to quantify digital images taken in a panel of 286 Iran bread wheat accessions under terminal drought stress and well-watered conditions. The color proportion of green to yellow (tolerance ratio) and the color proportion of yellow to green (stress ratio) was assessed for each canopy using the pipeline. The estimated tolerance and stress ratios were used as covariates in the genomic prediction models to evaluate the effect of change in canopy color on the improvement of the genomic prediction accuracy of different agronomic traits in wheat. Results The reliability of the high-throughput image analysis pipeline was proved by three to four times of improvement in the accuracy of genomic predictions for days to maturity with the use of tolerance and stress ratios as covariates in the univariate genomic selection models. The higher prediction accuracies were attained for days to maturity when both tolerance and stress ratios were used as fixed effects in the univariate models. The results of this study indicated that the Bayesian ridge regression and ridge regression-best linear unbiased prediction methods were superior to other genomic prediction methods which were used in this study under terminal drought stress and well-watered conditions, respectively. Conclusions This study provided a robust, quick, and cost-effective machine learning-enabled image-phenotyping pipeline to improve the genomic prediction accuracy for days to maturity in wheat. The results encouraged the integration of phenomics and genomics in breeding programs.

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Improving the efficiency of wheat breeding experiments using alpha lattice design over randomised complete block design

Cited by 6 publications

References 8 publications

Diversity and Agronomic Performance of Lupinus mutabilis Germplasm in European and Andean Environments

Diversity and Agronomic Performance of Lupinus mutabilis Germplasm in European and Andean Environments

GRAIN - BRAN QUALITY PARAMETERS and AGRONOMIC TRAITS of BREAD WHEAT CULTIVARS

A simple, cost-effective high-throughput image analysis pipeline improves genomic prediction accuracy for days to maturity in wheat

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