Soybean (Glycine max) is a highly self-pollinated species, but cross-pollination occasionally occurs and variations within cultivars can be observed under certain conditions. To explore the potential uses of natural hybridization and intra-cultivar/advanced line variations, 78 of breeding lines derived from the segregants of natural hybridization and the intra-cultivar/line variations and their 17 source cultivars/lines were evaluated over four crop seasons for yield, seed weight, and other agronomic traits. All the lines were also genotyped using BARCSoySNP6K assays to compare the genetic similarities between the new lines and the source genotypes. Analysis of variance results indicated that genotypic differences, year effects, and genotype × year interactions were significant for all the traits. The broad-sense heritability of the traits was estimated to be 67.22%–98.80%, suggesting that the traits were mainly affected by genetic factors. Compared with the source materials, yield of 34 breeding lines exceeded by >5%, and 17 of them had yield increases of 11.85%–41.59%. Seed weight increased significantly in 24 lines, and 11 lines showed improvements in both seed weight and yield, although there was a negative correlation between these two traits. In addition, 36 and 29 lines showed a shortened period of flowering and maturity, respectively. Plant height of 20 lines decreased by >8.5 cm. Genotypic matching rate between the new lines and the source materials varied from 48.86% to 99.90%. These results demonstrated that both segregations resulting from natural crossing and intra-cultivar/line variations could be used to improve important traits in soybean.
{"title":"Utilization of natural hybridization and intra-cultivar variations for improving soybean yield, seed weight, and agronomic traits","authors":"Guo-Liang Jiang, Patrick Mireku, Qijian Song","doi":"10.1002/csc2.21342","DOIUrl":"https://doi.org/10.1002/csc2.21342","url":null,"abstract":"Soybean (<i>Glycine max</i>) is a highly self-pollinated species, but cross-pollination occasionally occurs and variations within cultivars can be observed under certain conditions. To explore the potential uses of natural hybridization and intra-cultivar/advanced line variations, 78 of breeding lines derived from the segregants of natural hybridization and the intra-cultivar/line variations and their 17 source cultivars/lines were evaluated over four crop seasons for yield, seed weight, and other agronomic traits. All the lines were also genotyped using BARCSoySNP6K assays to compare the genetic similarities between the new lines and the source genotypes. Analysis of variance results indicated that genotypic differences, year effects, and genotype × year interactions were significant for all the traits. The broad-sense heritability of the traits was estimated to be 67.22%–98.80%, suggesting that the traits were mainly affected by genetic factors. Compared with the source materials, yield of 34 breeding lines exceeded by >5%, and 17 of them had yield increases of 11.85%–41.59%. Seed weight increased significantly in 24 lines, and 11 lines showed improvements in both seed weight and yield, although there was a negative correlation between these two traits. In addition, 36 and 29 lines showed a shortened period of flowering and maturity, respectively. Plant height of 20 lines decreased by >8.5 cm. Genotypic matching rate between the new lines and the source materials varied from 48.86% to 99.90%. These results demonstrated that both segregations resulting from natural crossing and intra-cultivar/line variations could be used to improve important traits in soybean.","PeriodicalId":10849,"journal":{"name":"Crop Science","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142118210","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
O. P. Yadav, S. K. Gupta, M. Govindaraj, D. V. Singh, A. Verma, R. Sharma, R. S. Mahala, S. K. Srivastava, P. S. Birthal
Pearl millet [Pennisetum glaucum (L.) R. Br.] is an important component of agri-food system in areas experiencing drought and high temperature and for increasing the resilience to climatic stresses and addressing malnutrition. The purpose of this review is to examine strategies for improving productivity, stress resilience, and nutritional quality of pearl millet and to understand its consumption pattern. Genetic diversification of hybrid parental lines remains strategically important to breed diverse, disease-resistant and drought-tolerant hybrids. Resistance to diseases, tolerance to drought, and high temperature and greater contents of iron and zinc are targeted in improving hybrid parental lines. Lodging resistance, compact panicles, panicle exertion, and improved seed set are universal traits, whereas duration, tillering ability, seed color, and seed size have a strong regional preference. The strategy of developing high-yielding and disease-resistant hybrids with adaptation to challenged agro-ecologies has led to increase in yield from 303 to 1219 kg/ha between 1960 and 2020. Yield and stress resilience are to be increased further using conventional breeding and new tools like genomic selection, speed breeding, genome editing, and precision phenotyping. Mainstreaming grain nutritional traits, viz., iron and zinc contents in genetic improvement are essential to develop high-yielding and nutrient-rich pearl millet. There is need to enhance the consumption of pearl millet by strengthening existing value-chain, providing consumer a choice of diverse range of food products, creating awareness about its health benefits and promotion through government schemes.
{"title":"Strategies for enhancing productivity, resilience, nutritional quality, and consumption of pearl millet [Pennisetum glaucum (L.) R. Br.] for food and nutritional security in India","authors":"O. P. Yadav, S. K. Gupta, M. Govindaraj, D. V. Singh, A. Verma, R. Sharma, R. S. Mahala, S. K. Srivastava, P. S. Birthal","doi":"10.1002/csc2.21346","DOIUrl":"https://doi.org/10.1002/csc2.21346","url":null,"abstract":"Pearl millet [<i>Pennisetum glaucum</i> (L.) R. Br.] is an important component of agri-food system in areas experiencing drought and high temperature and for increasing the resilience to climatic stresses and addressing malnutrition. The purpose of this review is to examine strategies for improving productivity, stress resilience, and nutritional quality of pearl millet and to understand its consumption pattern. Genetic diversification of hybrid parental lines remains strategically important to breed diverse, disease-resistant and drought-tolerant hybrids. Resistance to diseases, tolerance to drought, and high temperature and greater contents of iron and zinc are targeted in improving hybrid parental lines. Lodging resistance, compact panicles, panicle exertion, and improved seed set are universal traits, whereas duration, tillering ability, seed color, and seed size have a strong regional preference. The strategy of developing high-yielding and disease-resistant hybrids with adaptation to challenged agro-ecologies has led to increase in yield from 303 to 1219 kg/ha between 1960 and 2020. Yield and stress resilience are to be increased further using conventional breeding and new tools like genomic selection, speed breeding, genome editing, and precision phenotyping. Mainstreaming grain nutritional traits, viz., iron and zinc contents in genetic improvement are essential to develop high-yielding and nutrient-rich pearl millet. There is need to enhance the consumption of pearl millet by strengthening existing value-chain, providing consumer a choice of diverse range of food products, creating awareness about its health benefits and promotion through government schemes.","PeriodicalId":10849,"journal":{"name":"Crop Science","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142118209","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chromosome structural variations (SVs), such as deletion, duplication, inversion, and translocation, are important contributors to genetic diversification and crop improvement. Using genome editing tools such as clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR‐associated nuclease (Cas9), desired SVs involving large DNA fragments have been created in rice (Oryza sativa L.), maize (Zea mays L.), and Arabidopsis (Arabidopsis thaliana L.). However, it is still uncertain whether the size of DNA fragment involved could be a prohibiting factor to generate Cas9‐mediated SVs. In this study, we constructed five CRISPR/Cas9 vectors, each expressing two single‐guide RNAs (sgRNAs), to cut two sites spacing at 0.5, 5, 10, 20, and 30 Mb on rice chromosome 4 (Chr4), respectively. Meanwhile, another CRISPR/Cas9 vector cutting two sites, one on Chr4 and the other on Chr1, was also constructed for creation of chromosomal translocation between Chr1 and Chr4. These vectors were transfected into rice protoplasts by polyethylene glycol–mediated transformation. Specific primers were designed to detect desired SV events. The results showed that all designed SVs could be effectively generated by CRISPR/Cas9 in rice protoplasts. This study suggested that the size of DNA fragment involved is unlikely a prohibiting factor for creation of desired SV events.
{"title":"CRISPR/Cas9 effectively generate chromosome structural variations in rice protoplasts","authors":"Jiaying Sun, Yating Wang, Chenchu Guo, Ruiyun Ge, Tuya Naren, Linjian Jiang","doi":"10.1002/csc2.21334","DOIUrl":"https://doi.org/10.1002/csc2.21334","url":null,"abstract":"Chromosome structural variations (SVs), such as deletion, duplication, inversion, and translocation, are important contributors to genetic diversification and crop improvement. Using genome editing tools such as clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR‐associated nuclease (Cas9), desired SVs involving large DNA fragments have been created in rice (<jats:italic>Oryza sativa</jats:italic> L.), maize (<jats:italic>Zea mays</jats:italic> L.), and Arabidopsis (<jats:italic>Arabidopsis thaliana</jats:italic> L.). However, it is still uncertain whether the size of DNA fragment involved could be a prohibiting factor to generate Cas9‐mediated SVs. In this study, we constructed five CRISPR/Cas9 vectors, each expressing two single‐guide RNAs (sgRNAs), to cut two sites spacing at 0.5, 5, 10, 20, and 30 Mb on rice chromosome 4 (Chr4), respectively. Meanwhile, another CRISPR/Cas9 vector cutting two sites, one on Chr4 and the other on Chr1, was also constructed for creation of chromosomal translocation between Chr1 and Chr4. These vectors were transfected into rice protoplasts by polyethylene glycol–mediated transformation. Specific primers were designed to detect desired SV events. The results showed that all designed SVs could be effectively generated by CRISPR/Cas9 in rice protoplasts. This study suggested that the size of DNA fragment involved is unlikely a prohibiting factor for creation of desired SV events.","PeriodicalId":10849,"journal":{"name":"Crop Science","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142101177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Anthracnose (ANTH) caused by Colletotrichum lindemuthianum is a major disease of common bean (Phaseolus vulgaris L.). The genetic basis of ANTH resistance in the Middle American Diversity Panel (MDP) is unknown. The objectives of this study were to identify (1) Middle American accessions resistant to races 7, 19, 51, 63, 167, and 1085 of C. lindemuthianum and (ii) genomic regions and positional candidate genes associated with resistance to these races. The MDP composed of 240 Middle American accessions was evaluated for resistance to races 7, 19, 51, 63, 167, and 1085. The MDP was genotyped with 211,763 single nucleotide polymorphisms (SNPs), and mixed linear model analysis was conducted to identify genomic regions associated with resistance to the six races. Seven accessions were highly resistant to all six races, and these can be used as sources of resistance to improve specific market classes in the Middle American gene pool. The genomic region (385,894 bp) on chromosome Pv04 was significantly associated with resistance to race 167. Genomic regions on Pv02 (41,570,325 bp), Pv07 (24,122,343 bp), and Pv11 (51,707,917 bp) were significantly associated with resistance to race 19. Disease resistance (R) genes with the nucleotide binding‐APAF resistance protein and CED‐4 domain were identified as positional candidate genes on Pv04 and Pv11. There were no SNPs significantly associated with resistance to races 7, 51, 63, and 1085. Pyramiding the identified genomic regions on Pv04, Pv07, and Pv11 could provide durable ANTH resistance in Middle American varieties for races 19 and 167.
{"title":"Genome‐wide association analysis of resistance to anthracnose in the Middle American Diversity Panel of common bean (Phaseolus vulgaris L.)","authors":"Willard Sinkala, Swivia Hamabwe, Kuwabo Kuwabo, Chikoti Mukuma, Kelvin Kamfwa","doi":"10.1002/csc2.21335","DOIUrl":"https://doi.org/10.1002/csc2.21335","url":null,"abstract":"Anthracnose (ANTH) caused by <jats:italic>Colletotrichum lindemuthianum</jats:italic> is a major disease of common bean (<jats:italic>Phaseolus vulgaris</jats:italic> L.). The genetic basis of ANTH resistance in the Middle American Diversity Panel (MDP) is unknown. The objectives of this study were to identify (1) Middle American accessions resistant to races 7, 19, 51, 63, 167, and 1085 of <jats:italic>C. lindemuthianum</jats:italic> and (ii) genomic regions and positional candidate genes associated with resistance to these races. The MDP composed of 240 Middle American accessions was evaluated for resistance to races 7, 19, 51, 63, 167, and 1085. The MDP was genotyped with 211,763 single nucleotide polymorphisms (SNPs), and mixed linear model analysis was conducted to identify genomic regions associated with resistance to the six races. Seven accessions were highly resistant to all six races, and these can be used as sources of resistance to improve specific market classes in the Middle American gene pool. The genomic region (385,894 bp) on chromosome Pv04 was significantly associated with resistance to race 167. Genomic regions on Pv02 (41,570,325 bp), Pv07 (24,122,343 bp), and Pv11 (51,707,917 bp) were significantly associated with resistance to race 19. Disease resistance (R) genes with the nucleotide binding‐APAF resistance protein and CED‐4 domain were identified as positional candidate genes on Pv04 and Pv11. There were no SNPs significantly associated with resistance to races 7, 51, 63, and 1085. Pyramiding the identified genomic regions on Pv04, Pv07, and Pv11 could provide durable ANTH resistance in Middle American varieties for races 19 and 167.","PeriodicalId":10849,"journal":{"name":"Crop Science","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142090020","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nitrogen fertilizer application and increasing planting density have been recognized as essential measures to achieve higher wheat (Triticum aestivum L.) yields. However, inadequate management practices often lead to poor culm quality and lodging. We hypothesized that optimizing culm characteristics could be a feasible approach to improving both lodging resistance and yield. In this study, field experiments involved five nitrogen levels (0, 180, 240, 300, and 360 kg ha−1) and three planting densities (225, 375, and 525 × 104 ha−1). Two wheat cultivars with different lodging resistance were selected and their culm morphological characteristics, biochemical components, field lodging rate, and yield in different treatments were measured. We found that field lodging rate in wheat was negatively correlated with yield, and there was a contradiction between increasing spike number and lodging resistance. Culm carbohydrate accumulation affected field lodging rate by regulating culm quality rather than the center of gravity height. Compared with Xinmai 26, Xinhuamai 818 had higher culm carbohydrate accumulation, which increased the breaking strength and yield by 14.2% and 17.0%. Nitrogen application and planting density had significant effects on yield and lodging resistance. Compared with N0 treatment, increasing nitrogen application rate improved yield of 67.2%–83.2% by increasing spike number and grain number per spike, and the N2 treatment showed the largest increase. Planting density had little effect on yield. Reducing planting density can increase the culm carbohydrate accumulation and enhance lodging resistance. Compared with D3 treatment, the culm breaking strength was increased by 27.6% under the D1 treatment. This study determined that the optimal combination of nitrogen and density for improving wheat lodging resistance and yield is 240 kg ha−1 and 225 × 104 ha−1. This combination enhances culm breaking strength by increasing carbohydrate accumulation and achieves high yield by increasing grain number per spike, 1000‐grain weight, and stabilizing spike number.
{"title":"Optimizing nitrogen fertilization and planting density management enhances lodging resistance and wheat yield by promoting carbohydrate accumulation and single spike development","authors":"Haimeng Mu, Zhuangzhuang Wang, Lifang Sun, Yuan Huang, Yifan Song, Rong Zhang, Zijun Wu, Kaixia Fu, Jianzhao Duan, Guozhang Kang, Tiancai Guo, Yonghua Wang","doi":"10.1002/csc2.21327","DOIUrl":"https://doi.org/10.1002/csc2.21327","url":null,"abstract":"Nitrogen fertilizer application and increasing planting density have been recognized as essential measures to achieve higher wheat (<jats:italic>Triticum aestivum</jats:italic> L.) yields. However, inadequate management practices often lead to poor culm quality and lodging. We hypothesized that optimizing culm characteristics could be a feasible approach to improving both lodging resistance and yield. In this study, field experiments involved five nitrogen levels (0, 180, 240, 300, and 360 kg ha<jats:sup>−1</jats:sup>) and three planting densities (225, 375, and 525 × 10<jats:sup>4</jats:sup> ha<jats:sup>−1</jats:sup>). Two wheat cultivars with different lodging resistance were selected and their culm morphological characteristics, biochemical components, field lodging rate, and yield in different treatments were measured. We found that field lodging rate in wheat was negatively correlated with yield, and there was a contradiction between increasing spike number and lodging resistance. Culm carbohydrate accumulation affected field lodging rate by regulating culm quality rather than the center of gravity height. Compared with Xinmai 26, Xinhuamai 818 had higher culm carbohydrate accumulation, which increased the breaking strength and yield by 14.2% and 17.0%. Nitrogen application and planting density had significant effects on yield and lodging resistance. Compared with N0 treatment, increasing nitrogen application rate improved yield of 67.2%–83.2% by increasing spike number and grain number per spike, and the N2 treatment showed the largest increase. Planting density had little effect on yield. Reducing planting density can increase the culm carbohydrate accumulation and enhance lodging resistance. Compared with D3 treatment, the culm breaking strength was increased by 27.6% under the D1 treatment. This study determined that the optimal combination of nitrogen and density for improving wheat lodging resistance and yield is 240 kg ha<jats:sup>−1</jats:sup> and 225 × 10<jats:sup>4</jats:sup> ha<jats:sup>−1</jats:sup>. This combination enhances culm breaking strength by increasing carbohydrate accumulation and achieves high yield by increasing grain number per spike, 1000‐grain weight, and stabilizing spike number.","PeriodicalId":10849,"journal":{"name":"Crop Science","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142090152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Meseret Wondifraw, Zachary J. Winn, Scott D. Haley, John A. Stromberger, Emily Hudson‐Arns, R. Esten Mason
The water absorption capacity (WAC) of hard wheat (Triticum aestivum L.) flour affects end‐use quality characteristics, including loaf volume, bread yield, and shelf life. However, improving WAC through phenotypic selection is challenging. Phenotyping for WAC is time consuming and, as such, is often limited to evaluation in the latter stages of the breeding process, resulting in the retention of suboptimal lines longer than desired. This study investigates the potential of univariate and multivariate genomic predictions as an alternative to phenotypic selection for improving WAC. A total of 497 hard winter wheat genotypes were evaluated in multi‐environment advanced yield and elite trials over 8 years (2014–2021). Phenotyping for WAC was done via the solvent retention capacity (SRC) using water as a solvent (SRC‐W). Traits that exhibited a significant correlation (r ≥ 0.3) with SRC‐W and were evaluated earlier than SRC‐W were included in the multivariate genomic prediction models. Kernel hardness and diameter were obtained using the single kernel characterization system (SKCS), and break flour yield and total flour yield (T‐Flour) were included. Cross‐validation showed the mean univariate genomic prediction accuracy of SRC to be r = 0.69 ± 0.005, while bivariate and multivariate models showed an improved prediction accuracy of r = 0.82 ± 0.003. Forward validation showed a prediction accuracy up to r = 0.81 for a multivariate model that included SRC‐W + All traits (SRC‐W, Diameter, SKCS hardness and diameter, F‐Flour, and T‐Flour). These results suggest that incorporating correlated traits into genomic prediction models can improve early‐generation prediction accuracy.
硬质小麦（Triticum aestivum L.）面粉的吸水能力（WAC）会影响最终使用的质量特性，包括面包体积、面包产量和保质期。然而，通过表型选择来提高吸水率具有挑战性。WAC 的表型分析非常耗时，因此通常仅限于育种过程后期的评估，导致次优品系的保留时间超过预期。本研究调查了单变量和多变量基因组预测作为表型选择替代品的潜力，以改进 WAC。在为期 8 年（2014-2021 年）的多环境先进产量和精英试验中，共对 497 个硬冬小麦基因型进行了评估。通过以水为溶剂的溶剂保持能力（SRC）（SRC-W）对WAC进行表型。与SRC-W呈显著相关（r≥0.3）且早于SRC-W进行评估的性状被纳入多变量基因组预测模型。使用单仁表征系统（SKCS）获得了果仁硬度和直径，并将破碎粉产量和总面粉产量（T-面粉）包括在内。交叉验证表明，SRC 的平均单变量基因组预测准确率为 r = 0.69 ± 0.005，而双变量和多变量模型的预测准确率提高到了 r = 0.82 ± 0.003。正向验证结果表明，包含 SRC-W + 所有性状（SRC-W、直径、SKCS 硬度和直径、F-面粉和 T-面粉）的多元模型的预测准确率高达 r = 0.81。这些结果表明，将相关性状纳入基因组预测模型可提高早期预测的准确性。
{"title":"Advancing water absorption capacity in hard winter wheat using a multivariate genomic prediction approach","authors":"Meseret Wondifraw, Zachary J. Winn, Scott D. Haley, John A. Stromberger, Emily Hudson‐Arns, R. Esten Mason","doi":"10.1002/csc2.21321","DOIUrl":"https://doi.org/10.1002/csc2.21321","url":null,"abstract":"The water absorption capacity (WAC) of hard wheat (<jats:italic>Triticum aestivum</jats:italic> L.) flour affects end‐use quality characteristics, including loaf volume, bread yield, and shelf life. However, improving WAC through phenotypic selection is challenging. Phenotyping for WAC is time consuming and, as such, is often limited to evaluation in the latter stages of the breeding process, resulting in the retention of suboptimal lines longer than desired. This study investigates the potential of univariate and multivariate genomic predictions as an alternative to phenotypic selection for improving WAC. A total of 497 hard winter wheat genotypes were evaluated in multi‐environment advanced yield and elite trials over 8 years (2014–2021). Phenotyping for WAC was done via the solvent retention capacity (SRC) using water as a solvent (SRC‐W). Traits that exhibited a significant correlation (<jats:italic>r</jats:italic> ≥ 0.3) with SRC‐W and were evaluated earlier than SRC‐W were included in the multivariate genomic prediction models. Kernel hardness and diameter were obtained using the single kernel characterization system (SKCS), and break flour yield and total flour yield (T‐Flour) were included. Cross‐validation showed the mean univariate genomic prediction accuracy of SRC to be <jats:italic>r</jats:italic> = 0.69 ± 0.005, while bivariate and multivariate models showed an improved prediction accuracy of <jats:italic>r</jats:italic> = 0.82 ± 0.003. Forward validation showed a prediction accuracy up to <jats:italic>r</jats:italic> = 0.81 for a multivariate model that included SRC‐W + All traits (SRC‐W, Diameter, SKCS hardness and diameter, F‐Flour, and T‐Flour). These results suggest that incorporating correlated traits into genomic prediction models can improve early‐generation prediction accuracy.","PeriodicalId":10849,"journal":{"name":"Crop Science","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142050634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Elisabeth C. A. Kitchin, Henry J. Sneed, David S. McCall
This study evaluates the effectiveness of fine‐tuning a semantic segmentation model to identify and quantify dollar spot in turfgrasses, the most extensively managed and researched disease of turfgrasses worldwide. Using the DeepLabV3+ model, recognized for its capability to segment complex shapes and integrate multi‐scale contextual information, the research leveraged a diverse dataset comprising various turfgrass species, disease stages, and lighting conditions to ensure robust model training. The trained model is able to identify and segment disease instances accurately and precisely, and the results indicate the potential for model‐based assessment to outperform traditional visual assessment methods in speed, accuracy, and consistency. The development of deep learning models on extensive datasets like ImageNet requires significant computational resources. However, by fine‐tuning a pretrained semantic segmentation model, we adapted it for disease segmentation using only a standard personal computer's graphics processing unit. This approach not only conserves resources but also highlights the practicality of deploying advanced deep learning applications in turfgrass pathology with limited computational capacity. The proposed model provides a new tool for turfgrass researchers and professionals to rapidly and accurately quantify this important disease under real‐world growing conditions. Additionally, the findings suggest the potential to apply deep learning algorithms to other turfgrass diseases to support data‐driven decisions. This could enhance disease management practices and improve decision‐making processes for fungicidal treatments, thereby improving the economic and environmental sustainability of turfgrass management.
{"title":"Leveraging deep learning for dollar spot detection and quantification in turfgrass","authors":"Elisabeth C. A. Kitchin, Henry J. Sneed, David S. McCall","doi":"10.1002/csc2.21329","DOIUrl":"https://doi.org/10.1002/csc2.21329","url":null,"abstract":"This study evaluates the effectiveness of fine‐tuning a semantic segmentation model to identify and quantify dollar spot in turfgrasses, the most extensively managed and researched disease of turfgrasses worldwide. Using the DeepLabV3+ model, recognized for its capability to segment complex shapes and integrate multi‐scale contextual information, the research leveraged a diverse dataset comprising various turfgrass species, disease stages, and lighting conditions to ensure robust model training. The trained model is able to identify and segment disease instances accurately and precisely, and the results indicate the potential for model‐based assessment to outperform traditional visual assessment methods in speed, accuracy, and consistency. The development of deep learning models on extensive datasets like ImageNet requires significant computational resources. However, by fine‐tuning a pretrained semantic segmentation model, we adapted it for disease segmentation using only a standard personal computer's graphics processing unit. This approach not only conserves resources but also highlights the practicality of deploying advanced deep learning applications in turfgrass pathology with limited computational capacity. The proposed model provides a new tool for turfgrass researchers and professionals to rapidly and accurately quantify this important disease under real‐world growing conditions. Additionally, the findings suggest the potential to apply deep learning algorithms to other turfgrass diseases to support data‐driven decisions. This could enhance disease management practices and improve decision‐making processes for fungicidal treatments, thereby improving the economic and environmental sustainability of turfgrass management.","PeriodicalId":10849,"journal":{"name":"Crop Science","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142050635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Fusarium wilt resistance of Gossypium barbadense is very important to maintain its yield and quality, and to disease resistance breeding. Although many individual genes, which are quantitative trait loci associated with wilt resistance have been identified, knowledge of genes controlling wilt resistance in G. barbadense is still limited. In order to screen the InDel fragment related to Fusarium wilt resistance in G. barbadense, a genome‐wide association study was conducted using 110 recombinant inbred lines of Xinhai 14 (susceptible cotton) and 06–146 (resistant cotton). In this study, 207,040 high‐quality InDel loci were identified, of which 595 and 632 InDels were significantly associated (p < 1 × 10−3) with wilt resistance in G. barbadense in the additive and dominant effect module analyses, respectively. Combined transcriptome expression analysis within the FOV7 stably inherited qFOV7‐D03‐1 interval identified three ≥2 bp InDels for two differentially expressed genes. qPCR analysis was used to further validate that the expression of GB_D03G0204 and GB_D03G0238 was significantly different in the parental, resistant, and high susceptibility varieties. The GB_D03G0238 gene InDel was significant in both additive and dominant effect models, and the GB_D03G0204 gene InDel was significantly associated with wilt resistance in G. barbadense in the dominant effect model. The InDel fragments related to wilt resistance in G. barbadense discovered in this study can help gain insights into the genetic basis of wilt resistance and improve cotton breeding with excellent wilt resistance and high fiber quality traits.
{"title":"InDel variations and gene expression analysis related to Fusarium wilt resistance in Gossypium barbadense","authors":"Baojun Liu, Wanli Han, Jianyu Bai, Yu Yu, Xuwen Wang, Yanying Qu, Aixing Gu","doi":"10.1002/csc2.21330","DOIUrl":"https://doi.org/10.1002/csc2.21330","url":null,"abstract":"<jats:italic>Fusarium</jats:italic> wilt resistance of <jats:italic>Gossypium barbadense</jats:italic> is very important to maintain its yield and quality, and to disease resistance breeding. Although many individual genes, which are quantitative trait loci associated with wilt resistance have been identified, knowledge of genes controlling wilt resistance in <jats:italic>G. barbadense</jats:italic> is still limited. In order to screen the InDel fragment related to <jats:italic>Fusarium</jats:italic> wilt resistance in <jats:italic>G. barbadense</jats:italic>, a genome‐wide association study was conducted using 110 recombinant inbred lines of Xinhai 14 (susceptible cotton) and 06–146 (resistant cotton). In this study, 207,040 high‐quality InDel loci were identified, of which 595 and 632 InDels were significantly associated (<jats:italic>p </jats:italic>< 1 × 10<jats:sup>−3</jats:sup>) with wilt resistance in <jats:italic>G. barbadense</jats:italic> in the additive and dominant effect module analyses, respectively. Combined transcriptome expression analysis within the FOV7 stably inherited <jats:italic>qFOV7‐D03‐1</jats:italic> interval identified three ≥2 bp InDels for two differentially expressed genes. qPCR analysis was used to further validate that the expression of <jats:italic>GB_D03G0204</jats:italic> and <jats:italic>GB_D03G0238</jats:italic> was significantly different in the parental, resistant, and high susceptibility varieties. The <jats:italic>GB_D03G0238</jats:italic> gene InDel was significant in both additive and dominant effect models, and the <jats:italic>GB_D03G0204</jats:italic> gene InDel was significantly associated with wilt resistance in <jats:italic>G. barbadense</jats:italic> in the dominant effect model. The InDel fragments related to wilt resistance in <jats:italic>G. barbadense</jats:italic> discovered in this study can help gain insights into the genetic basis of wilt resistance and improve cotton breeding with excellent wilt resistance and high fiber quality traits.","PeriodicalId":10849,"journal":{"name":"Crop Science","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142050638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In an effort to find alternatives to paraquat for weed control and basal foliage removal in hops (Hummus lupulus L.), due to regulatory and safety concerns, a study was conducted across Oregon and Washington in 2020 and 2021. The study compared the efficacy of tiafenacil and tolpyralate against a nontreated control and carfentrazone. Applications were made early when hops were 2‐ to 3‐m tall (early), and at over 4 m (late). Tiafenacil showed 55%–85% effectiveness in basal foliage control, slightly higher than carfentrazone, and did not cause crop injury. Tiafenacil at 50 and 100 g a.i. ha−1 controlled Lolium multiflorum (Lam.) Husnot (63%). The mixture of tiafenacil and tolpyralate controlled 80% of L. multiflorum, Cirsium arvense L., and Bassia Scoparia (L.) A.J. Scott. In all cases, control was followed by weed regrowth. No signs of crop injury were observed in any of the studies with tiafenacil. Early applications of tiafenacil reduced yield between 0% and 40% relative to the nontreated control. Late applications of tolpyralate and tiafenacil did not significantly reduce yield. Tolpyralate was as effective as carfentrazone for weed control and basal foliage removal. Early applications of tolpyralate reduced plant height and yield relative to the nontreated control and consistently induced phytochemical injury. Tolpyralate yield reductions ranged from 0% to 84% relative to the nontreated control, depending on the trial. A mixture of tolpyralate and tiafenacil was the most effective treatment tested. We conclude that both tiafenacil and tolpyralate are safe for sucker applications in hops, but careful timing is needed to reduce the risk of injury with tolpyralate. The mixture of tiafenacil and tolpyralate can improve weed control comparable to available options.
{"title":"Evaluating tiafenacil and tolpyralate for weed control and basal foliage removal in hops","authors":"Ryan J. Hill, David R. King, Marcelo L. Moretti","doi":"10.1002/csc2.21322","DOIUrl":"https://doi.org/10.1002/csc2.21322","url":null,"abstract":"In an effort to find alternatives to paraquat for weed control and basal foliage removal in hops (<jats:italic>Hummus lupulus</jats:italic> L.), due to regulatory and safety concerns, a study was conducted across Oregon and Washington in 2020 and 2021. The study compared the efficacy of tiafenacil and tolpyralate against a nontreated control and carfentrazone. Applications were made early when hops were 2‐ to 3‐m tall (early), and at over 4 m (late). Tiafenacil showed 55%–85% effectiveness in basal foliage control, slightly higher than carfentrazone, and did not cause crop injury. Tiafenacil at 50 and 100 g a.i. ha<jats:sup>−1</jats:sup> controlled <jats:italic>Lolium multiflorum</jats:italic> (Lam.) Husnot (63%). The mixture of tiafenacil and tolpyralate controlled 80% of <jats:italic>L. multiflorum</jats:italic>, <jats:italic>Cirsium arvense</jats:italic> L., and <jats:italic>Bassia Scoparia</jats:italic> (L.) A.J. Scott. In all cases, control was followed by weed regrowth. No signs of crop injury were observed in any of the studies with tiafenacil. Early applications of tiafenacil reduced yield between 0% and 40% relative to the nontreated control. Late applications of tolpyralate and tiafenacil did not significantly reduce yield. Tolpyralate was as effective as carfentrazone for weed control and basal foliage removal. Early applications of tolpyralate reduced plant height and yield relative to the nontreated control and consistently induced phytochemical injury. Tolpyralate yield reductions ranged from 0% to 84% relative to the nontreated control, depending on the trial. A mixture of tolpyralate and tiafenacil was the most effective treatment tested. We conclude that both tiafenacil and tolpyralate are safe for sucker applications in hops, but careful timing is needed to reduce the risk of injury with tolpyralate. The mixture of tiafenacil and tolpyralate can improve weed control comparable to available options.","PeriodicalId":10849,"journal":{"name":"Crop Science","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142050580","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Larissa C. Costa, Magno A. P. Ramalho, Ângela F. B. Abreu, Elaine A. Souza
Recurrent selection is an effective and well‐known breeding method recommended for quantitative traits. However, the method has not been applied so far for traits typically controlled by numerous major loci, which is the case of resistance to anthracnose in common bean (Phaseolus vulgaris L.). In this study, we report the effectiveness of a recurrent selection program in developing common bean progenies with resistance to multiple races of Colletotrichum lindemuthianum, the causal agent of anthracnose in this crop. A total of 10 common bean lines, with distinct and complementary resistance profiles to races 65, 73, 81, and 89 of C. lindemuthianum, were intercrossed to establish a base population (Cycle 0). From Cycle 0, five iterative cycles of recombination, inoculation, and selection were carried out. Our results demonstrate that this recurrent selection approach can effectively combine resistance in common bean to different isolates from multiple races of C. lindemuthianum. A progressive increase in the number of progenies resistant to a higher number of C. lindemuthianum isolates was observed over the selection cycles. The genetic gain from CI to CV was 38.75% when the progenies were evaluated against a mixture of isolates from the four races of the pathogen. The reliance on specific genes makes race‐specific anthracnose resistance in common bean vulnerable to breakdown. By allowing optimal combinations of different anthracnose resistance genes, this dynamic recurrent selection approach is an attractive option for the development of common bean cultivars with increased stability and durability for anthracnose resistance.
循环选择是一种有效且众所周知的育种方法，被推荐用于数量性状的育种。然而，迄今为止，该方法尚未应用于通常由多个主要基因位点控制的性状，蚕豆（Phaseolus vulgaris L.）对炭疽病的抗性就是这种情况。在本研究中，我们报告了一个循环选择计划在培育具有对该作物炭疽病病原菌 Colletotrichum lindemuthianum 的多种抗性的蚕豆后代方面的有效性。共有 10 个普通菜豆品系对 C. lindemuthianum 的第 65、73、81 和 89 个品系具有不同且互补的抗性，它们通过杂交建立了一个基础群体（第 0 周期）。从周期 0 开始，进行了五次反复的重组、接种和选择。我们的研究结果表明，这种循环选择方法能有效地结合蚕豆对 C. lindemuthianum 多个品系不同分离株的抗性。在不同的选择周期中，对更多的 C. lindemuthianum 分离物具有抗性的后代数量逐渐增加。当后代针对病原体四个种族的分离株混合体进行评估时，从 CI 到 CV 的遗传增益为 38.75%。对特定基因的依赖使得普通豆类的种族特异性炭疽病抗性容易崩溃。通过对不同的抗炭疽病基因进行优化组合，这种动态循环选择方法对于培育具有更高抗炭疽病稳定性和持久性的四季豆栽培品种来说是一种极具吸引力的选择。
{"title":"Recurrent selection for broad‐spectrum resistance to anthracnose in common bean","authors":"Larissa C. Costa, Magno A. P. Ramalho, Ângela F. B. Abreu, Elaine A. Souza","doi":"10.1002/csc2.21319","DOIUrl":"https://doi.org/10.1002/csc2.21319","url":null,"abstract":"Recurrent selection is an effective and well‐known breeding method recommended for quantitative traits. However, the method has not been applied so far for traits typically controlled by numerous major loci, which is the case of resistance to anthracnose in common bean (<jats:italic>Phaseolus vulgaris</jats:italic> L.). In this study, we report the effectiveness of a recurrent selection program in developing common bean progenies with resistance to multiple races of <jats:italic>Colletotrichum lindemuthianum</jats:italic>, the causal agent of anthracnose in this crop. A total of 10 common bean lines, with distinct and complementary resistance profiles to races 65, 73, 81, and 89 of <jats:italic>C. lindemuthianum</jats:italic>, were intercrossed to establish a base population (Cycle 0). From Cycle 0, five iterative cycles of recombination, inoculation, and selection were carried out. Our results demonstrate that this recurrent selection approach can effectively combine resistance in common bean to different isolates from multiple races of <jats:italic>C. lindemuthianum</jats:italic>. A progressive increase in the number of progenies resistant to a higher number of <jats:italic>C. lindemuthianum</jats:italic> isolates was observed over the selection cycles. The genetic gain from CI to CV was 38.75% when the progenies were evaluated against a mixture of isolates from the four races of the pathogen. The reliance on specific genes makes race‐specific anthracnose resistance in common bean vulnerable to breakdown. By allowing optimal combinations of different anthracnose resistance genes, this dynamic recurrent selection approach is an attractive option for the development of common bean cultivars with increased stability and durability for anthracnose resistance.","PeriodicalId":10849,"journal":{"name":"Crop Science","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142042576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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