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Incorporating Radiation and Nitrogen Nutrition into a Model of Kernel Number in Wheat
Author(s) -
DemotesMainard Sabine,
Jeuffroy MarieHélène
Publication year - 2001
Publication title -
crop science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.76
H-Index - 147
eISSN - 1435-0653
pISSN - 0011-183X
DOI - 10.2135/cropsci2001.412415x
Subject(s) - anthesis , mathematics , biology , agronomy , horticulture , botany , cultivar
Wheat ( Triticum aestivum L.) kernel number per square meter (KN) depends on radiation, temperature, and crop N nutrition. Some models of KN using climatic data or N nutrition characteristics as input variables account for variations either in radiation and temperature or in N nutrition, but not for both. Our objective was to produce a model of KN that accounts simultaneously for variations due to radiation, temperature, and crop N nutrition, and that has input variables that are simple to measure or to simulate. Field experiments were conducted over 3 yr with ‘Trémie’ winter wheat. Treatments involved the application of N fertilizer at different dates and rates to achieve various N deficiencies and the use of shading nets for various periods during spike growth to reduce incident radiation. Crop N status was assessed by determining N nutrition index (NNI) at anthesis. The KN was counted, it ranged from 9420 to 31 036 kernels m −2 Two characteristics of N nutrition (NNI at anthesis and IDD, the duration of deficiency before anthesis multiplied by its intensity) and three characteristics of radiation and temperature (photothermal quotient calculated from 45 d before anthesis to anthesis, from 30 d before anthesis to anthesis and from 20 d before anthesis to 10 d after anthesis) were used as input variables. Six relationships combining one characteristic of N nutrition and the photothermal quotient over one period were estimated. The best fit was obtained for a relationship between KN and the logarithm of NNI at anthesis and photothermal quotient over the 45 d preceding anthesis ( R 2 = 0.883, n = 19). This relationship could be useful for estimating KN in crop models, as its input variables are simple to simulate.

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