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Predicting maize kernel sink capacity early in development
Affiliation:1. Departamento de Producción Vegetal, Facultad de Agronomía, Universidad de Buenos Aires, Av. San Martín 4453, C1417DSE, Capital Federal, Argentina;2. Department of Agronomy, Iowa State University, 1563 Agronomy Hall, Ames, IA 50011-1010, USA;1. INTA EEA Paraná, Ruta11, km12.5, 3100 Paraná, Argentina;2. FCA (UNER), Ruta11, km10, 3100 Paraná, Argentina;3. South Australian Research and Development Institute, Australia;1. School of Agriculture, Food and Wine, The University of Adelaide, Waite Campus, Urrbrae, SA 5064, Australia;2. Department of Plant Science and Crop Protection, University of Nairobi, P.O Box 29053-00625, Kangemi, Nairobi, Kenya;3. South Australian Research and Development Institute, Waite Campus, Urrbrae, SA 5064, Australia;1. The Key Laboratory of Oasis Eco-agriculture, Xinjiang Production and Construction Group, College of Agronomy, Shihezi University, Shihezi 832000, China;2. Institute of Crop Sciences, Chinese Academy of Agricultural Sciences/Key Laboratory of Crop Physiology and Ecology, Ministry of Agriculture, Beijing 100081, China;3. Institute of Crop Sciences, Ningxia Academy of Agriculture Sciences, Yongning, Ningxia Hui Autonomous Region 750105, China;1. Department of Agroecology, Environmental Sciences Research Institute, Shahid Beheshti University, G.C., P.O. Box 19835-196, Tehran, Iran;2. DuPont Pioneer, 8305 NW 62nd Avenue, Johnston, IA 50131, United States;3. Agri-Science Queensland, Department of Agriculture and Fisheries, 203 Tor Street, Toowoomba, QLD 4350, Australia;4. Epagri, 89620-000 Campos Novos, SC, Brazil;5. The University of Queensland, Queensland Alliance for Agriculture and Food Innovation, Brisbane, QLD 4072, Australia;6. CSIRO Agriculture and Food, Queensland Bioscience Precinct, 306 Carmody Road, St. Lucia, QLD 4067, Australia;1. State Key Laboratory of Grassland Agro-ecosystems, Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs, College of Pastoral Agricultural Science and Technology, Lanzhou University, Lanzhou, 730000, China;2. Institute of Integrative Biology, ETH Zürich, Zürich, 8092, Switzerland;3. UMR EMMAH, INRA, UAPV, 84914, Avignon, France;4. Life Science and Technology School, Lingnan Normal University, Zhanjiang, 524048, China;5. CSIRO Agriculture Flagship, PO Box 102, Toowoomba, Qld, 4350, Australia;6. The UWA Institute of Agriculture and School of Agriculture and Environment, The University of Western Australia, LB 5005, Perth, WA 6001, Australia;1. Universidad de Buenos Aires, Facultad de Agronomía, Departamento de Producción Vegetal, Cátedra de Cerealicultura, Buenos Aires, Argentina. Av. San Martín 4453, C1417DSE, Buenos Aires, Argentina;2. Universidad de Buenos Aires, Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura (IFEVA), Facultad de Agronomía, Buenos Aires, Argentina;3. Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Argentina;4. Center for Crop Sciences, Queensland Alliance for Agriculture and Food Innovation (QAAFI), The University of Queensland, Gatton Campus, Gatton 4343, Queensland, Australia
Abstract:Development of maize (Zea mays L.) kernels follows a predictable pattern involving rapid increase in dry weight and large changes in water content (WC). We showed previously that final kernel weight (KW) was closely correlated with maximum WC achieved during rapid grain filling. The objectives of the current work were (i) to test if percent moisture content (MC, measured on a fresh weight basis) could be used to normalize genetic and environmental variations in kernel development shown to affect final KW and (ii) to determine whether final KW could be predicted from kernel WC prior to rapid grain filling. The data examined included results from five hybrids varying more than 2-fold in final KW grown in the field, and from previously published results. When KW and WC were expressed relative to their maximum values obtained during kernel development, a single model described the relationship between dry weight accumulation and MC for the larger seeded hybrids (199–352 mg kernel−1) and published results (222–359 mg kernel−1). Two smaller seeded yellow-flint popcorn hybrids, however, accumulated less dry matter per unit moisture than expected. Nonetheless, all genotypes exhibited a common developmental relationship between kernel WC (expressed as a percent of the maximum value) and MC under well-watered conditions. A new model was developed to couple this developmental relationship to final KW. This model accurately predicted final KW from kernel WC values measured prior to rapid grain filling (∼80% MC; root mean square error, RMSE, of 28.9 mg kernel−1) for all hybrids examined and all published results for which KW and kernel WC data were available. The model also provided a simple means to determine whether final KW was limited by photosynthate supply during kernel development.
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