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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Vydáno v:	Journal of agricultural engineering (Pisa, Italy) Ročník 54; číslo 4
Hlavní autoři:	Zhao, Jiangui, Zhu, Tingyu, Qiu, Zhichao, Li, Tao, Wang, Guoliang, Li, Zhiwei, Du, Huiling
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Bologna PAGEPress Publications 01.01.2023
Témata:	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
On-line přístup:	Získat plný text
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