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Keywords = multi-environment yield trials

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15 pages, 2909 KiB  
Article
Adaptation and Grain Yield Stability Analysis of Winter Wheat Cultivars with and Without Fungicides Treatment from National Variety Trials in Sweden
by Admas Alemu, Pawan K. Singh and Aakash Chawade
Agriculture 2024, 14(12), 2229; https://doi.org/10.3390/agriculture14122229 - 5 Dec 2024
Viewed by 653
Abstract
The multi-environment evaluation of wheat genotypes for grain yield is an integral part of germplasm enhancement since it plays a pivotal role in sustainable production. A total of 178 winter wheat cultivars were evaluated across 20 environments in Sweden from 2016 to 2020, [...] Read more.
The multi-environment evaluation of wheat genotypes for grain yield is an integral part of germplasm enhancement since it plays a pivotal role in sustainable production. A total of 178 winter wheat cultivars were evaluated across 20 environments in Sweden from 2016 to 2020, with 52 to 59 cultivars tested per year as part of the Swedish National Trials (Sverigeförsöken). The genotypes were evaluated for grain yield performance with and without fungicide treatments. Additive main-effects and multiplicative interaction (AMMI) and genotype plus genotype-by-environment interaction (GGE) biplot methods were explored to estimate the genotype-by-environment interaction (GEI) for grain yield performance. ANOVA revealed a significant variation between treatments, genotypes in all years, and GEI in all years except 2018. The majority of the explained variance came from the environment, with a range of 61–88% across the five-year trial. The 20 sites were grouped into two to four mega-environments in the yearly studies. From the fungicide-treated trials, G 0512LT3, Informer, SG SU1563-15, LG Imposanto, and Pondus were identified as the most stable and high-yielding cultivars each year. From the fungicide-untreated trials, Informer, Ancher Greece, RGT Saki, and Pondus were the best-performing cultivars and could be good candidates for organic wheat cultivation. Full article
(This article belongs to the Section Crop Genetics, Genomics and Breeding)
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26 pages, 1783 KiB  
Article
Genotype Performance Estimation in Targeted Production Environments by Using Sparse Genomic Prediction
by Osval A. Montesinos-López, Paolo Vitale, Guillermo Gerard, Leonardo Crespo-Herrera, Carolina Saint Pierre, Abelardo Montesinos-López and José Crossa
Plants 2024, 13(21), 3059; https://doi.org/10.3390/plants13213059 - 31 Oct 2024
Viewed by 703
Abstract
In plant breeding, Multi-Environment Trials (METs) evaluate candidate genotypes across various conditions, which is financially costly due to extensive field testing. Sparse testing addresses this challenge by evaluating some genotypes in selected environments, allowing for a broader range of environments without significantly increasing [...] Read more.
In plant breeding, Multi-Environment Trials (METs) evaluate candidate genotypes across various conditions, which is financially costly due to extensive field testing. Sparse testing addresses this challenge by evaluating some genotypes in selected environments, allowing for a broader range of environments without significantly increasing costs. This approach integrates genomic information to adjust phenotypic data, leading to more accurate genetic effect estimations. Various sparse testing methods have been explored to optimize resource use. This study employed Incomplete Block Design (IBD) to allocate lines to environments, ensuring not all lines were tested in every environment. We compared IBD to Random line allocation, maintaining a consistent number of environments per line across both methods. The primary objective was to estimate grain yield performance of lines using Genomic Estimated Breeding Values (GEBVs) computed through six Genomic Best Linear Unbiased Predictor (GBLUP) methods. In the first five methods, missing values were predicted before cross-environment adjustment; in the sixth, adjustment was performed directly. Using the Bayesian GBLUP model, we analyzed genotype performance under both IBD and random allocation. Results indicate that computing GEBVs for a target population of environments (TPE) using available phenotype and marker data is effective for selection. The IBD method showed superior performance with less variability compared to random allocation. These findings suggest that using IBD designs can enhance selection accuracy and efficiency, and that pre-adjustment prediction of missing lines may not necessarily improve selection outcomes. Full article
(This article belongs to the Special Issue Genetics, Genomics, and Biotechnology for Cereal Crop Improvements)
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18 pages, 4758 KiB  
Article
Performance and Stability Analysis of Extra-Early Maturing Orange Maize Hybrids under Drought Stress and Well-Watered Conditions
by Tégawendé Odette Bonkoungou, Baffour Badu-Apraku, Victor Olawale Adetimirin, Kiswendsida Romaric Nanema and Idris Ishola Adejumobi
Agronomy 2024, 14(4), 847; https://doi.org/10.3390/agronomy14040847 - 18 Apr 2024
Cited by 4 | Viewed by 1281
Abstract
The consistently low yield turnout of maize on farmers’ fields owing to drought and the nutritional challenges attributable to the consumption of white endosperm maize pose a major threat to food and nutritional security in Sub-Saharan Africa (SSA). The objectives of this study [...] Read more.
The consistently low yield turnout of maize on farmers’ fields owing to drought and the nutritional challenges attributable to the consumption of white endosperm maize pose a major threat to food and nutritional security in Sub-Saharan Africa (SSA). The objectives of this study were to assess the performance of newly developed extra-early maturing orange hybrids under managed drought and well-watered conditions, compare the outcomes of multiple-trait base index and multi-trait genotype–ideotype distance index selection procedures, and identify drought-tolerant hybrids with stable performance across contrasting environments for commercialization in SSA. One hundred and ninety orange hybrids and six checks were evaluated under managed drought and well-watered conditions at Ikenne for two seasons between 2021 and 2023. A 14 × 14-lattice design was used for the field evaluations under both research conditions. Drought stress was achieved by the complete withdrawal of irrigation water 25 days after planting. Results revealed significant differences among the hybrids under drought and well-watered conditions. Grain yield, ears per plant, and plant aspect under managed drought were correlated to the same traits under well-watered conditions, suggesting that the expression of these traits is governed by common genetic factors. Twenty-nine hybrids were identified as top-performing drought-tolerant hybrids by the multiple-trait base index and the multi-trait genotype–ideotype distance index. Of the selected outstanding 29 hybrids, 34% were derived from crosses involving the tester TZEEIOR 197, demonstrating the outstanding genetic potential of this inbred line. Further analysis of the 29 selected hybrids revealed TZEEIOR 509 × TZEEIOR 197 as the hybrid that combined the most drought-tolerant adaptive traits. However, the hybrids TZEEIOR 526 × TZEEIOR 97, TZEEIOR 384 × TZEEIOR 30, TZEEIOR 515 × TZEEIOR 249, TZEEIOR 510 × TZEEIOR 197, TZEEIOR 479 × TZEEIOR 197, and TZEEIOR 458 × TZEEIOR 197 were identified as the most stable hybrids across drought and well-watered conditions. These hybrids should be extensively tested in multi-location trials for deployment and commercialization in SSA. Full article
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14 pages, 1505 KiB  
Article
Vegetable Response to Added Nitrogen and Phosphorus Using Machine Learning Decryption and the N/P Ratio
by Léon Etienne Parent
Horticulturae 2024, 10(4), 356; https://doi.org/10.3390/horticulturae10040356 - 3 Apr 2024
Viewed by 1224
Abstract
The current N and P fertilization practices for vegetable crops grown in organic soils are inaccurate and and may potentially damage the environment. New fertilization models are needed. Machine learning (ML) methods can combine numerous features to predict crop response to N and [...] Read more.
The current N and P fertilization practices for vegetable crops grown in organic soils are inaccurate and and may potentially damage the environment. New fertilization models are needed. Machine learning (ML) methods can combine numerous features to predict crop response to N and P fertilization. Our objective was to evaluate machine learning predictions for marketable yields, N and P offtakes, and the N/P ratio of vegetable crops. We assembled 157 multi-environmental fertilizer trials on lettuce (Lactuca sativa), celery (Apium graveolens), onion (Allium cepa), and potato (Solanum tuberosum) and documented 22 easy-to-collect soil, managerial, and meteorological features. The random forest models returned moderate to substantial strength (R2 = 0.73–0.80). Soil and managerial features were the most important. There was no response to added P and null to moderate response to added N in independent universality tests. The N and P offtakes were most impacted by P-related features, indicating N–P interactions. The N/P mass ratios of harvested products were generally lower than 10, suggesting P excess that would trigger plant N acquisition and possibly alter soil N and C cycles through microbial processes. Crop response prediction by ML models and ex post N/P ratio diagnosis and N and P offtakes proved to be useful tools to guide N and P management decisions in organic soils. Full article
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12 pages, 619 KiB  
Article
Genomic Prediction for Inbred and Hybrid Polysomic Tetraploid Potato Offspring
by Rodomiro Ortiz, Fredrik Reslow, Ramesh Vetukuri, M. Rosario García-Gil, Paulino Pérez-Rodríguez and José Crossa
Agriculture 2024, 14(3), 455; https://doi.org/10.3390/agriculture14030455 - 11 Mar 2024
Viewed by 4254
Abstract
Potato genetic improvement begins with crossing cultivars or breeding clones which often have complementary characteristics for producing heritable variation in segregating offspring, in which phenotypic selection is used thereafter across various vegetative generations (Ti). The aim of this research was to [...] Read more.
Potato genetic improvement begins with crossing cultivars or breeding clones which often have complementary characteristics for producing heritable variation in segregating offspring, in which phenotypic selection is used thereafter across various vegetative generations (Ti). The aim of this research was to determine whether tetrasomic genomic best linear unbiased predictors (GBLUPs) may facilitate selecting for tuber yield across early Ti within and across breeding sites in inbred (S1) and hybrid (F1) tetraploid potato offspring. This research used 858 breeding clones for a T1 trial at Umeå (Norrland, 63°49′30″ N 20°15′50″ E) in 2021, as well as 829 and 671 clones from the breeding population for T2 trials during 2022 at Umeå and Helgegården (Skåne, 56°01′46″ N 14°09′24″ E), respectively, along with their parents (S0) and check cultivars. The S1 and F1 were derived from selfing and crossing four S0. The experimental layout was an augmented design of four-plant plots across testing sites, where breeding clones were non-replicated, and the parents and cultivars were placed in all blocks between the former. The genomic prediction abilities (r) for tuber weight per plant were 0.5944 and 0.6776 in T2 at Helgegården and Umeå, respectively, when T1 at Umeå was used as the training population. On average, r was larger in inbred than in hybrid offspring at both breeding sites. The r was also estimated using multi-environment data (involving at least one S1 and one F1) for T2 performance at both breeding sites. The r was strongly influenced by the genotype in both S1 and F1 offspring irrespective of the breeding site. Full article
(This article belongs to the Special Issue Feature Papers in Genotype Evaluation and Breeding)
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15 pages, 1816 KiB  
Article
Assessment of Yield Stability of Bambara Groundnut (Vigna subterranea (L.) Verdc.) Using Genotype and Genotype–Environment Interaction Biplot Analysis
by Rita Adaeze Linus, Oluwaseyi Samuel Olanrewaju, Olaniyi Oyatomi, Emmanuel Ohiosinmuan Idehen and Michael Abberton
Agronomy 2023, 13(10), 2558; https://doi.org/10.3390/agronomy13102558 - 4 Oct 2023
Cited by 8 | Viewed by 1875
Abstract
Biplot analysis has emerged as a crucial statistical method in plant breeding and agricultural research. The objective of this research was to identify the best-performing genotype(s) for the environments in three distinct regions of Nigeria while also examining the characteristics and magnitude of [...] Read more.
Biplot analysis has emerged as a crucial statistical method in plant breeding and agricultural research. The objective of this research was to identify the best-performing genotype(s) for the environments in three distinct regions of Nigeria while also examining the characteristics and magnitude of genotype–environment interaction (GEI) effects on the yield of Bambara groundnut (BGN). The study was conducted in Ibadan, Ikenne, and Mokwa, utilizing a sample of 30 accessions. The yield of BGN was found to be significantly affected by accessions, environment, and their interaction through a combined analysis of variance, with a p-value < 0.001. Biplots were utilized to demonstrate the pattern of interaction components, specifically the genotype’s main effect and genotype–environment interaction (GEI). The initial two principal components elucidated the complete variance of the GGE model, encompassing both genetic and genotype-by-environment interaction effects (PC1 = 87.81%, PC2 = 12.19%). The accessions that exhibited superior performance in each respective environment, as determined by the “which-won-where” polygon, were identified as TVSu-2223, TVSu-2236, TVSu-2240, and TVSu-2249 in Mokwa; TVSu-2214 in Ikenne; and TVSu-2188 in Ibadan. The accessions TVSu-2207 and TVSu-2199 exhibited stability in all environments, whereas the accessions TVSu-2226, TVSu-2249, TVSu-2209, TVSu-2184, TVSu-2204, and TVSu-2236 demonstrated adaptability. In addition, the accessions TVSu-2240 and TVSu-2283 were stable and adaptable in all environments. The accessions that were chosen have been suggested as suitable parental lines for breeding programs aimed at enhancing grain yield in the agro-ecological zones that were evaluated. This study’s findings identify BGN accessions with adaptability and stability across selected environments in Nigeria, suggesting specific accessions that can serve as suitable parental lines in breeding programs to enhance grain yield, thereby holding promise for improving food security. Full article
(This article belongs to the Special Issue Frontier Studies in Legumes Genetic Breeding and Production)
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11 pages, 1062 KiB  
Article
Performance and Stability of Improved Cassava (Manihot esculenta Crantz) Clones in Demand Creation Trials in Nigeria
by ThankGod Oche Ogwuche, Mercy Elohor Diebiru-Ojo, Adetoro Najimu, Chukwunalu Okolie Ossai, Ukoabasi Ekanem, Bidemi Adegbite, Gideon Oyebode and Peter Kulakow
Crops 2023, 3(3), 209-219; https://doi.org/10.3390/crops3030020 - 2 Aug 2023
Viewed by 1998
Abstract
Cassava fresh root yield and dry matter content constitute major determinants of demand by end-users. Increased demand for the seeds of improved varieties will facilitate the development of a sustainable seed system. However, for wide acceptability, there is a need to continuously evaluate [...] Read more.
Cassava fresh root yield and dry matter content constitute major determinants of demand by end-users. Increased demand for the seeds of improved varieties will facilitate the development of a sustainable seed system. However, for wide acceptability, there is a need to continuously evaluate candidate varieties for stability across different agroecological zones. Participatory Demand Creation Trials (DCTs) were established to evaluate cassava varieties with farmers and processors utilizing the best agronomic practices. The multi-year DCTs were conducted in 20 environments (7 locations) during the 2016–2017, 2017–2018, 2018–2019, and 2019/2020 cropping seasons with two replications. The plot sizes were 320 m2 with a spacing of 1 m × 0.8 m. The traits evaluated were Plant Vigor (PV), root number, fresh yield, dry yield, Dry Matter Content (DMC), and bundle estimation. The traits were subjected to a GGE biplot in R software to identify high-yielding and stable genotypes. Results obtained from the 20 environments showed that genotype (G), environment (E), and GXE interaction effects were significant (p < 0.01) for all the traits but PV. The heritability ranged from 56% (PV) to 96% (DMC). The average fresh yield t/ha ranged from 25.5 (IBA30572) to 35.4 (IBA980505). The DMC ranged from CR36/5 (36.1%) to IBA010040 (30.7%). The dry yield ranged from 8.8% (IBA30572) to 11.4 (IBA980505). Estimated bundles ranged from 13.5 (CR36-5) to 15.7 (IBA950289). Three varieties, IBA961632, TMEB419, and CR36/5, were identified as the most promising high dry matter content varieties for cassava processors and farmers in Nigeria, and genotype IBA961632 was the most stable. The study revealed greater genotypic effects than from the environment and high genetic advances. Full article
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10 pages, 878 KiB  
Article
Potential of Temperate, Tropical, and Sub-Tropical Exotic Maize Germplasm for Increased Gains in Yield Performance in Sub-Tropical Breeding Programs
by Rejoice Shumirai Nyoni, Cosmos Magorokosho and Casper Nyaradzai Kamutando
Agronomy 2023, 13(6), 1605; https://doi.org/10.3390/agronomy13061605 - 14 Jun 2023
Cited by 2 | Viewed by 2050
Abstract
Exotic germplasm (i.e., germplasm beyond the breeder’s target area) has traditionally been used to broaden the genetic base of local (germplasm within the breeder’s target area) populations, but little has been done to assess gains that could be induced by this breeding practice [...] Read more.
Exotic germplasm (i.e., germplasm beyond the breeder’s target area) has traditionally been used to broaden the genetic base of local (germplasm within the breeder’s target area) populations, but little has been done to assess gains that could be induced by this breeding practice in the sub-tropical regions of Africa. Here, eight maize (Zea mays L.) inbred lines developed from pedigree crosses of exotic and local (i.e., sub-tropically adapted lines; STALs) were inter-mated together with six elite STALs, in a partial diallel mating scheme, in order to depict yield gains that can be made when exotic genes are integrated within the sub-tropical maize germplasm pool. The crossing scheme yielded a total of 91 F1s which were evaluated together with nine commercial checks in multi-environmental trials (METs) at eight locations representing agro-ecologies in which maize is predominantly grown in Zimbabwe. Across site Analysis of Variance (ANOVA) showed differences in grain yield (GY) performance of the F1s. Significant genotype x environment effects was also detected for GY (i.e., GEI; p < 0.05). F1s of parents with a temperate background [i.e., P7 (S) x P2 (T)] showed the highest GY potential (e.g., G44; GY = 10.52 tha−1). Apart from showing high GY potential, G44 also demonstrated to be stable across diverse agro-ecologies and to mature earlier than the best commercial check hybrid. In conclusion, incorporation of exotic genes, especially those from temperate regions, may improve the yielding ability and stability and can introduce earliness in the maturity of maize populations in sub-tropical regions. Full article
(This article belongs to the Special Issue Plant Genetic Resources and Biotechnology)
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36 pages, 1102 KiB  
Review
Breeding Wheat for Powdery Mildew Resistance: Genetic Resources and Methodologies—A Review
by Theresa Bapela, Hussein Shimelis, Tarekegn Terefe, Salim Bourras, Javier Sánchez-Martín, Dimitar Douchkov, Francesca Desiderio and Toi John Tsilo
Agronomy 2023, 13(4), 1173; https://doi.org/10.3390/agronomy13041173 - 20 Apr 2023
Cited by 11 | Viewed by 5431
Abstract
Powdery mildew (PM) of wheat caused by Blumeria graminis f. sp. tritici is among the most important wheat diseases, causing significant yield and quality losses in many countries worldwide. Considerable progress has been made in resistance breeding to mitigate powdery mildew. Genetic host [...] Read more.
Powdery mildew (PM) of wheat caused by Blumeria graminis f. sp. tritici is among the most important wheat diseases, causing significant yield and quality losses in many countries worldwide. Considerable progress has been made in resistance breeding to mitigate powdery mildew. Genetic host resistance employs either race-specific (qualitative) resistance, race-non-specific (quantitative), or a combination of both. Over recent decades, efforts to identify host resistance traits to powdery mildew have led to the discovery of over 240 genes and quantitative trait loci (QTLs) across all 21 wheat chromosomes. Sources of PM resistance in wheat include landraces, synthetic, cultivated, and wild species. The resistance identified in various genetic resources is transferred to the elite genetic background of a well-adapted cultivar with minimum linkage drag using advanced breeding and selection approaches. In this effort, wheat landraces have emerged as an important source of allelic and genetic diversity, which is highly valuable for developing new PM-resistant cultivars. However, most landraces have not been characterized for PM resistance, limiting their use in breeding programs. PM resistance is a polygenic trait; therefore, the degree of such resistance is mostly influenced by environmental conditions. Another challenge in breeding for PM resistance has been the lack of consistent disease pressure in multi-environment trials, which compromises phenotypic selection efficiency. It is therefore imperative to complement conventional breeding technologies with molecular breeding to improve selection efficiency. High-throughput genotyping techniques, based on chip array or sequencing, have increased the capacity to identify the genetic basis of PM resistance. However, developing PM-resistant cultivars is still challenging, and there is a need to harness the potential of new approaches to accelerate breeding progress. The main objective of this review is to describe the status of breeding for powdery mildew resistance, as well as the latest discoveries that offer novel ways to achieve durable PM resistance. Major topics discussed in the review include the genetic basis of PM resistance in wheat, available genetic resources for race-specific and adult-plant resistance to PM, important gene banks, and conventional and complimentary molecular breeding approaches, with an emphasis on marker-assisted selection (MAS). Full article
(This article belongs to the Special Issue Crop Powdery Mildew—Series II)
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24 pages, 3355 KiB  
Article
Detection of High-Performance Wheat Genotypes and Genetic Stability to Determine Complex Interplay between Genotypes and Environments
by Ibrahim Al-Ashkar, Mohammed Sallam, Khalid F. Almutairi, Mohamed Shady, Abdullah Ibrahim and Salem S. Alghamdi
Agronomy 2023, 13(2), 585; https://doi.org/10.3390/agronomy13020585 - 18 Feb 2023
Cited by 14 | Viewed by 2531
Abstract
Abiotic stress decreases crop production worldwide. In order to recommend suitable genotypes for cultivation under water deficit and heat stress conditions, an overall understanding of the genetic basis and plant responses to these stresses and their interactions with the environment is required. To [...] Read more.
Abiotic stress decreases crop production worldwide. In order to recommend suitable genotypes for cultivation under water deficit and heat stress conditions, an overall understanding of the genetic basis and plant responses to these stresses and their interactions with the environment is required. To achieve these goals, the multitrait genotype-ideotype distance index (MGIDI) was utilized to recognize abiotic-stress-tolerant wheat genotypes, and the weighted average of absolute scores (WAASB) index as well as the superiority index, which enables weighting between the mean performance and stability (WAASBY), were utilized to recognize high-yielding and stable genotypes. Twenty wheat genotypes were examined to determine the abiotic stress tolerance capacity of the investigated genotypes under nine test environments (three seasons × three treatments). Abiotic stress significantly decreased most morpho-physiological and all agronomic traits; however, some abiotic-stress-tolerant genotypes expressed a slight reduction in the measured traits as compared with the control group. G04, G12, G13, and G17 were identified as convenient and stable genotypes using the MGIDI index under all environments. Based on the scores of the genotype index (WAASB), G01, G05, G12, and G17 were selected as superior genotypes with considerable stability in terms of the grain yield (GY). G04, G06, G12, and G18 were classified as cluster (I), the productive and stable genotypes, using the WAASBY superiority index. The combined indices (MGIDI and WAASB) and (MGIDI and WAASBY) revealed genotypes G12 and G17 and genotypes G04 and G12, respectively, as the most stable candidates. Therefore, these are considered novel genetic resources for improving productivity and stabilizing GY in wheat programs under optimal conditions, water deficit, and heat stress. The genotype G12 was jointly expressed in all three indices. Stability measures using WAASB may help breeders with decision-making when selecting genotypes and conducting multi-environment trials. Hence, these methods, if jointly conducted, can serve as a powerful tool to assist breeders in multi-environment trials. Full article
(This article belongs to the Special Issue Recent Advances in Bioinformatics for Plant Genetic Traits)
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18 pages, 3229 KiB  
Article
Assessing the Stability of Herbicide-Tolerant Lentil Accessions (Lens culinaris Medik.) under Diverse Environments
by Rind Balech, Fouad Maalouf, Somanagouda B. Patil, Karthika Rajendran, Lynn Abou Khater, Diego Rubiales and Shiv Kumar
Plants 2023, 12(4), 854; https://doi.org/10.3390/plants12040854 - 14 Feb 2023
Cited by 1 | Viewed by 2166
Abstract
Assessing the adaptability and stability of herbicide-tolerant lentil accessions to two broad-spectrum post-emergence herbicides in multi-environment trials has become a must in a breeding program to improve its selection. The adaptability and stability of 42 herbicide-tolerant lentil accessions were investigated using five stability [...] Read more.
Assessing the adaptability and stability of herbicide-tolerant lentil accessions to two broad-spectrum post-emergence herbicides in multi-environment trials has become a must in a breeding program to improve its selection. The adaptability and stability of 42 herbicide-tolerant lentil accessions were investigated using five stability parameters under eight different environments. Significant Genotype–Environment (GE) interaction was found for days to flowering (DFLR), days to maturity (DMAT), and seed yield per plant (SY). The analyzed stability parameters such as Cultivar superiority, Finlay–Wilkinson, Shukla, Static Stability, and Wricke’s Ecovalence ranked the tested accessions differently, confirming the importance of using a combination of stability parameters when evaluating the performance of a group of accessions. GGE biplot of the SY trait accounted for 60.79% of sums of squares of the GE interaction and showed that cool and high rainfall environments are ideal for testing the agronomic performance of tolerant accessions. The GGE biplot of SY showed that IG4605(19), IG195(6), and IG156635(12) were specifically adapted to one mega environment, whereas IG70056(38) was identified as a superior line having a high and stable yield. These lines should be included in lentil crossing programs to develop herbicide-tolerant cultivars adapted to diverse environments. Full article
(This article belongs to the Section Crop Physiology and Crop Production)
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16 pages, 3647 KiB  
Article
Do We Need to Breed for Regional Adaptation in Soybean?—Evaluation of Genotype-by-Location Interaction and Trait Stability of Soybean in Germany
by Cleo A. Döttinger, Volker Hahn, Willmar L. Leiser and Tobias Würschum
Plants 2023, 12(4), 756; https://doi.org/10.3390/plants12040756 - 8 Feb 2023
Cited by 5 | Viewed by 2153
Abstract
Soybean is a crop in high demand, in particular as a crucial source of plant protein. As a short-day plant, soybean is sensitive to the latitude of the growing site. Consequently, varieties that are well adapted to higher latitudes are required to expand [...] Read more.
Soybean is a crop in high demand, in particular as a crucial source of plant protein. As a short-day plant, soybean is sensitive to the latitude of the growing site. Consequently, varieties that are well adapted to higher latitudes are required to expand the cultivation. In this study, we employed 50 soybean genotypes to perform a multi-location trial at seven locations across Germany in 2021. Two environmental target regions were determined following the latitude of the locations. Adaptation and trait stability of seed yield and protein content across all locations were evaluated using Genotype plus Genotype-by-Environment (GGE) biplots and Shukla’s stability variance. We found a moderate level of crossing-over type genotype-by-location interaction across all locations. Within the environmental target regions, the genotype-by-location interaction could be minimised. Despite the positive correlation (R = 0.59) of seed yield between the environmental target regions and the same best-performing genotype, the genotype rankings differed in part substantially. In conclusion, we found that soybean can be grown at a wide range of latitudes across Germany. However, the performance of genotypes differed between the northern and southern locations, with an 18.8% higher mean yield in the south. This in combination with the observed rank changes of high-performing genotypes between both environmental target regions suggests that selection targeted towards environments in northern Germany could improve soybean breeding for those higher latitude regions. Full article
(This article belongs to the Special Issue Genetic Basis of Yield and Yield Stability in Major Crops)
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16 pages, 3217 KiB  
Article
Identification of Eco-Climatic Factors Driving Yields and Genotype by Environment Interactions for Yield in Early Maturity Soybean Using Crop Simulation
by Chloé Elmerich, Guénolé Boulch, Michel-Pierre Faucon, Lyes Lakhal and Bastien Lange
Agronomy 2023, 13(2), 322; https://doi.org/10.3390/agronomy13020322 - 20 Jan 2023
Cited by 5 | Viewed by 2418
Abstract
Deploying crops in regions bordering their initial distribution area requires adapting existing cultivars to particular environmental constraints. In this study, we revealed the main Eco-climatic Factors (EFs)—climatic factors recorded over specific phenological periods—impacting both yields and Genotype by Environment Interactions (GEI) for yield [...] Read more.
Deploying crops in regions bordering their initial distribution area requires adapting existing cultivars to particular environmental constraints. In this study, we revealed the main Eco-climatic Factors (EFs)—climatic factors recorded over specific phenological periods—impacting both yields and Genotype by Environment Interactions (GEI) for yield in early maturity soybeans (Glycine max (L.) Merrill) under high latitudes. A multi-year (2017–2021) and multi-environment (n = 112) database was built based on the official post-inscription French soybean trial network “SOJA Terres Inovia-GEVES-Partenaires”. Yields of 57 cultivars covering MG00 and MG000 maturity groups were considered. For each environment, 126 EFs were calculated using a Crop Growth Model (CGM) based on observed weather data and simulated developmental stages. Partial Least Square (PLS) regression analyses using the Variable Importance in Projection (VIP) score were used to sort out the most relevant EFs for their impact on yield levels on the one side and on GEI for yield on the other side. Our results confirmed that yield levels for both maturity groups were greatly influenced by climatic factors from the seed filling phenophases, mainly End of Pod to Physiological Maturity. The cumulative potential evapotranspiration during the End of Pod to Physiological Maturity period was the main EF affecting yield levels positively for both maturity groups (VIP = 2.86; R2 = 0.64). Interestingly, EFs explaining yield levels strongly differed from those explaining GEI, in terms of both climatic factors and phenophases. GEI were mostly influenced by climatic factors from First Flower to End of Pod; these factors were maximum temperatures and solar radiation intensity. Cold stress from Sowing to First Seed also appeared to be a critical driver for GEI in MG00 soybeans. The contrasted responses of several cultivars to the main GEI-drivers highlighted a potential genetic variability that could be exploited in early maturity soybean breeding. This study revealed the complexity of GEI ecophysiology, and our results should help breeding strategies to deliver germplasm that outperforms the existing genetic material for expanding the crop to northern European regions. Full article
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13 pages, 2247 KiB  
Article
Multi-Environment Trials and Stability Analysis for Yield-Related Traits of Commercial Rice Cultivars
by Seung Young Lee, Hyun-Sook Lee, Chang-Min Lee, Su-Kyung Ha, Hyang-Mi Park, So-Myeong Lee, Youngho Kwon, Ji-Ung Jeung and Youngjun Mo
Agriculture 2023, 13(2), 256; https://doi.org/10.3390/agriculture13020256 - 20 Jan 2023
Cited by 26 | Viewed by 5201
Abstract
Multi-environment trials (METs) are essential in plant breeding programs to evaluate crop productivity and adaptability in diverse environments. In this study, we demonstrated the practical use of METs to evaluate grain yield and yield-related traits using 276 Korean rice cultivars, divided into three [...] Read more.
Multi-environment trials (METs) are essential in plant breeding programs to evaluate crop productivity and adaptability in diverse environments. In this study, we demonstrated the practical use of METs to evaluate grain yield and yield-related traits using 276 Korean rice cultivars, divided into three maturity groups (81 early-, 90 medium-, and 105 medium–late-maturing cultivars) grown in three regions (Jeonju, Suwon, and Miryang) and two planting seasons (early and regular planting) for two years. Due to the narrow genetic variability of the commercial cultivars, which are cultivated in relatively similar environmental conditions, genotype-by-environment interaction (GEI) effects were not statistically significant. However, genotype and environment evaluation using GGE biplot analysis exhibited distinct patterns of mega-environment formation, winning genotypes, ranking genotypes, discriminating power, and representativeness according to the differences in planting seasons and regions. Moreover, the simultaneous selection of stable high-performance genotypes using a weighted average of absolute scores from the singular-value decomposition of the matrix of BLUPs (WAASB) and a multi-trait stability index (MTSI) revealed six recommended genotypes each for early-maturing (Manho, Namil, Unkwang, Odae 1ho, Sinunbong 1ho, and Jonong) and medium-maturing (Sobi, Cheongdam, Shinbaeg, Boramchal, Mimyeon, and Saemimyeon) cultivars, and four genotypes for medium–late-maturing cultivars (Hanmauem, Dami, Baegseolchal, and Hangangchalbyeo). The winning genotypes of each trait can be used as parents to develop regional specialty cultivars by fine-tuning favorable traits, and recommended genotypes can be utilized as elite climate-resilient parents that can aid breeders in improving yield potential and stability across the planting seasons and regions. Full article
(This article belongs to the Topic Plant Breeding, Genetics and Genomics)
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19 pages, 2383 KiB  
Article
GEM Project-Derived Maize Lines Crossed with Temperate Elite Tester Lines Make for High-Quality, High-Yielding and Stable Silage Hybrids
by Milica Perisic, Alden Perkins, Dayane Cristina Lima, Natalia de Leon, Bojan Mitrovic and Dusan Stanisavljevic
Agronomy 2023, 13(1), 243; https://doi.org/10.3390/agronomy13010243 - 13 Jan 2023
Cited by 3 | Viewed by 2769
Abstract
Maize silage is fundamental for high milk production in dairy farming. The incorporation of new genetic diversity into temperate maize germplasm has the potential to improve adapted cultivars, and it could be especially useful for improving the nutrition of silage varieties. The goal [...] Read more.
Maize silage is fundamental for high milk production in dairy farming. The incorporation of new genetic diversity into temperate maize germplasm has the potential to improve adapted cultivars, and it could be especially useful for improving the nutrition of silage varieties. The goal of this study is to assess the potential for lines from the Germplasm Enhancement of Maize (GEM) project to compete with commercial silage hybrids when crossed with elite temperate-adapted testers. We examined 35 GEM-derived hybrids along with five commercial checks in seven environments across three years in trials that were arranged in randomized complete block designs. Hybrids were compared based on their potential for conversion into animal productivity units: milk yield per hectare (Milk ha−1) and milk yield per ton of silage (Milk t−1). Broad phenotypic variation was observed for both traits, and the broad-sense heritability of Milk ha−1 and Milk t−1 were 0.24 and 0.31, respectively. Five out of six hybrids in the top 15%, based on a multi-trait stability index, were GEM-derived hybrids. The large proportions of phenotypic variance attributed to genotype by environment interactions (GEI) for quality traits suggests that local adaptation should be leveraged for silage breeding that make use of GEM-derived materials. Full article
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