Modeling drip-irrigated rice yield using normalized difference vegetation index: a preliminary study

Averchev, О.; Osinnii, О.; Lavrenko, S.; Lykhovyd, P.

dc.contributor.author	Averchev, О.
dc.contributor.author	Osinnii, О.
dc.contributor.author	Lavrenko, S.
dc.contributor.author	Lykhovyd, P.
dc.date.accessioned	2024-01-09T08:21:28Z
dc.date.available	2024-01-09T08:21:28Z
dc.date.issued	2023
dc.identifier.citation	Osinnii, O., Averchev, O., Lavrenko, S., & Lykhovyd, P. (2023). Modeling drip-irrigated rice yield using normalized difference vegetation index: a preliminary study. International Conference “Agriculture for Life, Life for Agriculture”. Book of Abstracts. Section 1. Agronomy. (Bucharest, 2023). (pp. 132).	ru
dc.identifier.issn	2457-3205 (PRINT)
dc.identifier.uri	http://hdl.handle.net/123456789/8714
dc.description.abstract	Rice is one of the major food crops with a growing demand on the global market. The need for water-saving and environmentally friendly technologies presses current agricultural science to look for alternative ways of rice irrigation. The most prospective one is drip irrigation. Yield prediction is also of great importance for sustainable agriculture.	ru
dc.language.iso	en	ru
dc.publisher	University of Agronomic Sciences and Veterinary Medicine of Bucharest, Faculty of Agriculture, Romania	ru
dc.relation.ispartofseries	Section 1: Agronomy;
dc.subject	artificial neural network,	ru
dc.subject	regression	ru
dc.subject	remote sensing	ru
dc.subject	statistics	ru
dc.subject	yielding scale	ru
dc.title	Modeling drip-irrigated rice yield using normalized difference vegetation index: a preliminary study	ru
dc.type	Thesis	ru