数字农科院2.0

Nitrogen Status Diagnosis and Yield Prediction of Spring Maize after Green Manure Incorporation by Using a Digital Camera

文献类型： 外文期刊

作者： Bai Jin-shun;Cao Wei-dong;Zeng Nao-hua;Xiong Jing;Cao Wei-dong;Katshyoshi, Shimizu;Rui Yu-kui

作者机构：

关键词： Digital image;Green manure;Maize;Nitrogen status diagnosis

期刊名称： SPECTROSCOPY AND SPECTRAL ANALYSIS

ISSN： 1000-0593

年卷期： 2013 年 33 卷 12 期

页码：

收录情况： SCI

摘要： In order to explore the feasibility of using the image processing technology to diagnose the nitrogen status and to predict the maize yield, a field experiment with different nitrogen rates with green manure incorporation was conducted. Maize canopy digital images over a range of growth stages were captured by digital camera. Maize nitrogen status and the relationships between image color indices derived by digital camera for maize at different growth stages and maize nitrogen status indicators were analyzed. These digital camera sourced image color indices at different growth stages for maize were also regressed with maize grain yield at maturity. The results showed that the plant nitrogen status for maize was improved by green manure application. The leaf chlorophyll content (SPAD value), aboveground biomass and nitrogen uptake for green manure treatments at different maize growth stages were all higher than that for chemical fertilization treatments. The correlations between spectral indices with plant nitrogen indicators for maize affected by green manure application were weaker than that affected by chemical fertilization. And the correlation coefficients for green manure application were ranged with the maize growth stages changes. The best spectral indices for diagnosis of plant nitrogen status after green manure incorporation were normalized blue value (B/(R+G+B)) at 12-leaf (V12) stage and normalized red value (R/(R+G+B)) at grain-filling (R4) stage individually. The coefficients of determination based on linear regression were 0.45 and 0.46 for B/(R+G+B) at V12 stage and R/(R+G+B)) at R4 stage respectively, acting as a predictor of maize yield response to nitrogen affected by green manure incorporation. Our findings suggested that digital image technique could be a potential tool for in-season prediction of the nitrogen status and grain yield for maize after green manure incorporation when the suitable growth stages and spectral indices for diagnosis were selected.

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