Abstract:

Estimating nitrogen content of apple leaves rapidly non-destructive and timely is the basis of ensuring apple yield and quality锛� and the inversion of leaf nitrogen content using hyperspectral technology can provide theoretical basis for reasonable fertilization. The spectral and corresponding leaf nitrogen content of apple leaves were analyzed and modeling in apple critical growing stage from 2012 to 2013 in Feicheng锛� Shandong Province. Based on the above data锛� the correlation between leaf nitrogen content and original spectrum锛� first order differential spectrum锛� three-sided spectral index was firstly analysed in order to select sensitive spectral index of leaf nitrogen content锛� Secondly锛� the spectral index NDSI and RSI was built which were sensitive to leaf nitrogen content锛� Finally锛� the prediction model of the apple leaf nitrogen content was established based on the way that was grey correlation analysis-partial least squares regression and out-of-bag data- random forest algorithm. The results showed锛� 锛�1锛� The sensitive bands between leaf nitrogen content and original spectrum and first-order differential spectrum were 553锛� 711锛� 527锛� 708 and 559 nm锛� the spectral indices sensitive to leaf nitrogen content were NDSI_{锛�567锛�615锛�}and RSI_{锛�554锛�615锛�}锛� the best correlation between leaf nitrogen content and the three-sided spectral index was Sdy. 锛�2锛� The result showed that OOB-RF estimation model had better accuracy and reliability锛� which can guide fruit tree variable fertilization using leaf nitrogen content. This way achieved prediction of leaf nitrogen content between regional and annual levels锛� and had a wide range of potential applications.

Key words: Apple leaf, Leaf nitrogen content, Grey relational analysis, Random forest, Partial least squares

鎽樿锛�

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鍏抽敭璇�: 鑻规灉鍙剁墖, 鍙剁墖姘惈閲�, 鐏拌壊鍏宠仈鍒嗘瀽, 闅忔満妫灄, 鍋忔渶灏忎簩涔樻硶