Forecasting sunflower grain yield using remote sensing data and statistical models-Reference-Cited by-同舟云学术

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Forecasting sunflower grain yield using remote sensing data and statistical models

Published:2023-01 Issue: Volume:142 Page:126677
ISSN:1161-0301
Container-title:European Journal of Agronomy
language:en
Short-container-title:European Journal of Agronomy

Author:

Debaeke P.,Attia F.,Champolivier L.,Dejoux J.-F.,Micheneau A.,Bitar A. Al,Trépos R.

Funder

Agence Nationale de la Recherche

Ministère de l'Agriculture et de l'Alimentation

Publisher

Elsevier BV

Subject

Plant Science,Soil Science,Agronomy and Crop Science

Reference59 articles.

1. Intercepted solar radiation during seed filling determines sunflower weight per seed and oil concentration;Aguirrezabal;Crop Sci.,2003

2. Analysis and modelling of the factors controlling seed oil content in sunflower: a review;Andrianasolo;OCL - Oilseeds fats Crops Lipids,2016

3. Modeled analysis of the biophysical nature of spectral shifts and comparison with information content of broad bands;Baret;Remote Sens. Environ.,1992

4. LAI, fAPAR and fCover CYCLOPES global products derived from VEGETATION: Part 1: principles of the algorithm;Baret;Remote Sens. Environ.,2007

5. GAI estimates of row crops from downward looking digital photos taken perpendicular to rows at 57.5° zenith angle: theoretical considerations based on 3D architecture models and application to wheat crops;Baret;Agric. . Met.,2010

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