Prediction of nitrogen and phosphorus contents in citrus leaves based on hyperspectral imaging

• Published in: International journal of agricultural and biological engineering Vol. 8; no. 2; p. 80
• Main Authors: Yanli, Liu, Qiang, Lyu, Shaolan, He, Shilai, Yi, Xuefeng, Liu, Rangjin, Xie, Yongqiang, Zheng, Lie, Deng
• Format: Journal Article
• Language: English
• Published: Beijing International Journal of Agricultural and Biological Engineering (IJABE) 01.04.2015
• Subjects: Accuracy; Chlorophyll; Citrus fruits; Leaves; Methods; Nitrogen; Nutrition; Nutritional status; Phosphorus content; Software; Spectrum analysis; Support vector machines; United States > US; China; Taiwan
• ISSN: 1934-6344; 1934-6352
• DOI: 10.3965/j.ijabe.20150802.1464

The nutritional status of citrus leaves is very important to the determining of fertilization plants. The spectrum technique is a quick, un-injured method and is becoming widely used for plant nutrient estimation. The possibility and method of using spectrum technique to estimate the nutrient of citrus leaf was explored in this study. A total amount of 135 leaves from the mature spring shoots of navel orange trees (C. sinensis Osbeck, Newhall) were collected and randomly grouped into two sets of samples. The hyperspectral images were scanned upper and lower side of each leaf and then the total nitrogen (N) and phosphorus (P) contents of each leaf were measured. The raw spectra data were extracted to generate average spectra curves, preprocessed with five different methods, and was used to build N and P content prediction models. The study suggested that the hyperspectral image data from the upper side of the citrus leaves are suitable for nondestructive estimation of nutrient content.