Hyperspectral prediction of pigment content in tomato leaves based on logistic-optimized sparrow search algorithm and back propagation neural network

Leaf pigment content can reflect the nutrient elements content of the cultivation medium indirectly. To rapidly and accurately predict the pigment content of tomato leaves, chlorophyll a, chlorophyll b, chlorophyll and carotenoid were extracted from leaves of tomato seedlings cultured at different n...

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Bibliographic Details
Published in:	Journal of agricultural engineering (Pisa, Italy) Vol. 54; no. 4
Main Authors:	Zhao, Jiangui, Zhu, Tingyu, Qiu, Zhichao, Li, Tao, Wang, Guoliang, Li, Zhiwei, Du, Huiling
Format:	Journal Article
Language:	English
Published:	Bologna PAGEPress Publications 01.01.2023
Subjects:	Algorithms Back propagation Back propagation networks Carotenoids Chlorophyll Convergence Fertilization Hyperspectral imaging Infrared imaging Leaves logistic chaotic mapping Low concentrations Machine learning Mapping Neural networks Nitrogen Nutrient concentrations Nutrient content Pigments pigments content Predictions Root-mean-square errors Search algorithms Seedlings sparrow search algorithm tomato leaf Tomatoes
ISSN:	1974-7071, 2239-6268
Online Access:	Get full text
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