Integrating genetic gain and gap analysis to predict improvements in crop productivity

Wiley - Tập 60 Số 2 - Trang 582-604 - 2020
Mark Cooper1, Tom Tang2, Carla Gho3, Tim Hart2, Graeme Hammer1, Carlos D. Messina2
1Queensland Alliance for Agriculture and Food Innovation, Centre for Crop Science, University of Queensland, Brisbane, QLD, 4072 Australia
2Research and Development, Corteva Agriscience, Johnston, IA, 50131 USA
3Viluco Experiment Station, Corteva Agriscience, Santa Filomena 1609, PO Box 267, Buin, Chile

Tóm tắt

AbstractA Crop Growth Model (CGM) is used to demonstrate a biophysical framework for predicting grain yield outcomes for Genotype by Environment by Management (G×E×M) scenarios. This required development of a CGM to encode contributions of genetic and environmental determinants of biophysical processes that influence key resource (radiation, water, nutrients) use and yield‐productivity within the context of the target agricultural system. Prediction of water‐driven yield‐productivity of maize for a wide range of G×E×M scenarios in the U.S. corn‐belt is used as a case study to demonstrate applications of the framework. Three experimental evaluations are conducted to test predictions of G×E×M yield expectations derived from the framework: (1) A maize hybrid genetic gain study, (2) A maize yield potential study, and (3) A maize drought study. Examples of convergence between key G×E×M predictions from the CGM and the results of the empirical studies are demonstrated. Potential applications of the prediction framework for design of integrated crop improvement strategies are discussed. The prediction framework opens new opportunities for rapid design and testing of novel crop improvement strategies based on an integrated understanding of G×E×M interactions. Importantly the CGM ensures that the yield predictions for the G×E×M scenarios are grounded in the biophysical properties and limits of predictability for the crop system. The identification and delivery of novel pathways to improved crop productivity can be accelerated through use of the proposed framework to design crop improvement strategies that integrate genetic gains from breeding and crop management strategies that reduce yield gaps.

Từ khóa


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Wiley

Tập 60 Số 2

582-604

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