China＇s Super Hybrid Rice Breeding Program has made significant progress over the past two decades. In this paper, we reviewed our studies on the yield potential and stability in super hybrid rice and discussed the s...China＇s Super Hybrid Rice Breeding Program has made significant progress over the past two decades. In this paper, we reviewed our studies on the yield potential and stability in super hybrid rice and discussed the strategies for super hybrid rice production. The results of our studies show that rice yield potential has been increased by 12% in super hybrid cultivars as compared with ordinary hybrid and inbred cultivars. The higher grain yields in super hybrid rice cultivars are attributed to larger panicle size coupled with higher biomass production or higher harvest index. However, grain yields in super hybrid rice cultivars vary widely among locations depending on soil and climatic factors. Therefore, it is important to tailor target yield to local conditions in super hybrid rice production. The target yield for super hybrid rice production can be determined by the average yield method or the regression model method. Improving soil quality is critical to achieving the target yield in super hybrid rice production. Favorable crop rotations such as rice-oilseed rape and novel soil management practices, such as biochar addition, are effective approaches to improve soil quality. It is needed to develop simplified cultivation tech- nologies for super hybrid rice to meet the changes in socioeconomic environments during the period of transition. There are such technologies as no-tillage direct seeding and mechanized transplanting at high hill density with single seedling per hill.展开更多
Estimation of yield performance for crop products is a topic of interest in agriculture.In breeding programs,we cannot test all possible hybrids created by crossing two parents(inbred and tester)since it would be too ...Estimation of yield performance for crop products is a topic of interest in agriculture.In breeding programs,we cannot test all possible hybrids created by crossing two parents(inbred and tester)since it would be too time consuming and costly.In this paper,we exploit different machine learning algorithms including decision tree,gradient boosting machine,random forest,adaptive boosting,XGBoost and neural network to predict the yield of corn hybrids using data provided in the 2020 Syngenta Crop Challenge.The participants were asked to predict the yield of missing hybrids which were not tested before.Our results show that the prediction obtained by XGBoost is more accurate than other models with a root mean square error equal to 0.0524.Therefore,we use XGBoost model to estimate the yield performance for untested combinations of inbreds and testers.Using this approach,we identify hybrids with high predicted yield that can be bred to increase corn production.展开更多
用 Eberhart & Russell 模式和 Shukla 方法,比较分析了14个 T 型冬小麦 F_1杂种和10个纯系(亲本)品种在5个不同地点的产量和品质性状的稳定性。结果表明,所有性状都存在显著的基因型×环境互作。在基因型×环境互作的模式...用 Eberhart & Russell 模式和 Shukla 方法,比较分析了14个 T 型冬小麦 F_1杂种和10个纯系(亲本)品种在5个不同地点的产量和品质性状的稳定性。结果表明,所有性状都存在显著的基因型×环境互作。在基因型×环境互作的模式与性质上,杂种和纯系品种都主要表现为非线性响应。杂种小麦的产量表现比纯系品种更为稳定,但在蛋白质含量及干、湿面筋含量上,杂种对有利环境条件的响应比纯系品种敏感。稳定性好的品种之间或与稳定性一般的品种杂交,其 F_1杂种一般表现稳定。杂种湿面筋含量的高低与其稳定性表现密切相关。蛋白质产量与籽粒产量在稳定性反应上较为一致。通过研究认为,回归分析模型在测定基因型对于环境响应的稳定性方面不失为一种有效的方法。展开更多
基金supported by the Earmarked Fund for China Agriculture Research System(CARS-01)
文摘China＇s Super Hybrid Rice Breeding Program has made significant progress over the past two decades. In this paper, we reviewed our studies on the yield potential and stability in super hybrid rice and discussed the strategies for super hybrid rice production. The results of our studies show that rice yield potential has been increased by 12% in super hybrid cultivars as compared with ordinary hybrid and inbred cultivars. The higher grain yields in super hybrid rice cultivars are attributed to larger panicle size coupled with higher biomass production or higher harvest index. However, grain yields in super hybrid rice cultivars vary widely among locations depending on soil and climatic factors. Therefore, it is important to tailor target yield to local conditions in super hybrid rice production. The target yield for super hybrid rice production can be determined by the average yield method or the regression model method. Improving soil quality is critical to achieving the target yield in super hybrid rice production. Favorable crop rotations such as rice-oilseed rape and novel soil management practices, such as biochar addition, are effective approaches to improve soil quality. It is needed to develop simplified cultivation tech- nologies for super hybrid rice to meet the changes in socioeconomic environments during the period of transition. There are such technologies as no-tillage direct seeding and mechanized transplanting at high hill density with single seedling per hill.
文摘Estimation of yield performance for crop products is a topic of interest in agriculture.In breeding programs,we cannot test all possible hybrids created by crossing two parents(inbred and tester)since it would be too time consuming and costly.In this paper,we exploit different machine learning algorithms including decision tree,gradient boosting machine,random forest,adaptive boosting,XGBoost and neural network to predict the yield of corn hybrids using data provided in the 2020 Syngenta Crop Challenge.The participants were asked to predict the yield of missing hybrids which were not tested before.Our results show that the prediction obtained by XGBoost is more accurate than other models with a root mean square error equal to 0.0524.Therefore,we use XGBoost model to estimate the yield performance for untested combinations of inbreds and testers.Using this approach,we identify hybrids with high predicted yield that can be bred to increase corn production.
