Journal of Crop Research
Online ISSN : 2424-1318
Print ISSN : 1882-885X
ISSN-L : 1882-885X
Research Article
Estimation of Dry Matter Weight of Soybean Using the New Vegetation Index
Seito KamakiSota NakamotoDaesung HohTatsuya InamuraHiromo Inoue
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JOURNAL OPEN ACCESS

2021 Volume 66 Pages 47-53

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Abstract

It is expected to greatly contribute to the subsequent fertilization management and yield prediction, if the above-ground dry matter weight can be estimated accurately in the crop cultivation process. We tested if dry matter weight of soybean could be estimated using a new vegetation index, which combines daily chlorophyll index and daily irradiance (∑(CI×I)). For comparison, the normalized differential vegetation index (NDVI) and the chlorophyll index (CI) were used. Soybean cultivar Sachiyutaka was cultivated in Nara at 2018 and 2019, and Kyoto at 2020, and various soybean populations with different dry matter weights were obtained by changing the planting density or nitrogen fertilizer applications. We measured dry matter weight of soybeans 4 to 5 times and two vegetation indexes, NDVI and CI, 5 to 6 times during the growing period, at about two weeks intervals, as a guide. From the relationship between dry matter weight of soybeans and each vegetation index, we obtained the regression formula and coefficient of determination. As a result, ∑(CI×I) was significantly related to the dry matter weight throughout the three years, and coefficients of determination ranged from 0.90 to 0.97. In addition, in the growing period after the beginning of flowering, there was no significant difference in the slope and Y-axis intercept of the regression formula of the dry matter weight by using ∑(CI×I) among years. It was clarified that ∑(CI×I) could be used to estimate dry matter weight of soybean with one regression formula in the growing period after the beginning of flowering even in different populations. These results indicate that the new vegetation index of ∑(CI×I) is effective as an index for estimating the dry matter weight of soybean.

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© 2021 The Society of Crop Science and Breeding in Kinki, Japan
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