Near-infrared leaf reflectance modeling of Annona emarginata seedlings for early detection of variations in nitrogen concentration  

作　　者：Rafaela Lancas Gomes Marília Caixeta Sousa Felipe Girotto Campos Carmen Sílvia Fernandes Boaro José Raimundo de Souza Passos Gisela Ferreira 

机构地区：[1]Bioestatistic,Plant Biology,Parasitology and Zoology Department,Bioscience Institute(IBB),Universidade Estadual Paulista(UNESP),Botucatu,Sao Paulo,Brazil

出　　处：《Journal of Forestry Research》2023年第1期269-282,共14页林业研究（英文版）

基　　金：a scholarship from Capes(Coordena??o de Aperfei?oamento de Pessoal de Nível Superior)-Brazil(Award number:001)for the first author。

摘　　要：Nitrogen(N)monitoring is essential in nurseries to ensure the production of high-quality seedlings.Nearinfrared spectroscopy(NIRS)is an instantaneous,nondestructive method to monitor N.Spectral data such as NIRS can also provide the basis for developing a new vegetation spectral index(VSI).Here,we evaluated whether NIRS combined with statistical modeling can accurately detect early variations in N concentration in leaves of young plants of Annona emargiaata and developed a new VSI for this task.Plants were grown in a hydroponics system with 0,2.75,5.5or 11 mM N for 45 days.Then we measured gas exchange,chlorophylla fluorescence,and pigments in leaves;analyzed complete leaf nutrients,and recorded spectral data for leaves at 966 to 1685 nm using NIRS.With a statistical learning approach,the dimensionality of the spectral data was reduced,then models were generated using two classes(N deficiency,N)or four classes(0,2.75,5.5,11 mM N).The best combination of techniques for dimensionality reduction and classification,respectively,was stepwise regression(PROC STEPDISC)and linear discriminant function.It was possible to detect N deficiency in seedlings leaves with 100%precision,and the four N concentrations with93.55%accuracy before photosynthetic damage to the plant occurred.Thereby,NIRS combined with statistical modeling of multidimensional data is effective for detecting N variations in seedlings leaves of A.emarginata.

关 键 词：Mineral nutrition of plants Near-infrared spectroscopy Spectral vegetation index Digital signature Statistical learning Fluorescence of chlorophylla 

分 类 号：S667.1[农业科学—果树学]