Variation in Rice Yields and Determinants Among Paddy Fields

Dongpo Li (), Teruaki Nanseki (), Yuji Matsue (), Yosuke Chomei () and Shuichi Yokota ()
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Dongpo Li: Hunan University of Technology and Business
Teruaki Nanseki: Kyushu University
Yuji Matsue: Kyushu University
Yosuke Chomei: Kyushu University
Shuichi Yokota: Yokota Farm Co. Ltd.

A chapter in Empirical Analyses on Rice Yield Determinants of Smart Farming in Japan, 2021, pp 27-48 from Springer

Abstract: Abstract This chapter identified the variation and determinants of rice yield measured by the smart combine harvesterSmart combine harvester, from among different rice yields within large-scale farms. Apart from to the paddy yield with 15% moisture, we studied the variations in the concerning ratios for unsorted and sorted brown riceSorted brown rice as well. The sample included 351 fields from a farm corporation scaled over 113 hectares, located in the Kanto region of Japan. The candidate determinants were the field area and condition, nitrogen amount, time of transplanting or seeding, stage-specific growth indicators of chlorophyll content, number of panicles, plant height, and leaf plate valueLPV (leaf plate value). In addition, soil properties, average temperature, and solar radiation were incorporated. Meanwhile, the varieties, cultivation practices, and soil types were adopted as dummy variables. The empirical analysis was conducted using multivariate linear regression, with logarithmic transformations of the continuous variables. The result indicated that panicle numbers in the full-heading stage and transplanting or sowing time were the most important continuous determinant, following by nitrogen amount, humus content, and so forth. Within the significant discrete determinants, Akidawara and Milky queen were found to be the productive and unproductive varieties, respectively, while the well-drained direct sowing was found to negatively affecting yield.

Date: 2021
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DOI: 10.1007/978-981-33-6256-7_2

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