RT info:eu-repo/semantics/article
T1 Assessment of RGB vegetation indices to estimate chlorophyll content in sugar beet leaves in the final cultivation stage
A1 Sánchez Sastre, Luis Fernando
A1 Alte da Veiga, Nuno M. S.
A1 Ruiz Potosme, Norlan Miguel
A1 Carrión Prieto, Paula
A1 Marcos Robles, José Luis
A1 Navas Gracia, Luis Manuel
A1 Martín Ramos, Pablo
K1 Beta vulgaris
K1 Chlorophyll
K1 Clorofila
K1 Sugar beet
K1 Remolacha azucarera
K1 Unmanned aerial vehicles
K1 Vehículos aéreos no tripulados
AB Estimation of chlorophyll content with portable meters is an easy way to quantify crop nitrogen status in sugar beet leaves. In this work, an alternative for chlorophyll content estimation using RGB-only vegetation indices has been explored. In a first step, pictures of spring-sown ‘Fernanda KWS’ variety sugar beet leaves taken with a commercial camera were used to calculate 25 RGB indices reported in the literature and to obtain 9 new indices through principal component analysis (PCA) and stepwise linear regression (SLR) techniques. The performance of the 34 indices was examined in order to evaluate their ability to estimate chlorophyll content and chlorophyll degradation in the leaves under different natural light conditions along 4 days of the canopy senescence period. Two of the new proposed RGB indices were found to improve the already good performance of the indices reported in the literature, particularly for leaves featuring low chlorophyll contents. The 4 best indices were finally tested in field conditions, using unmanned aerial vehicle (UAV)-taken photographs of a sugar beet plot, finding a reasonably good agreement with chlorophyll-meter data for all indices, in particular for I2 and (R−B)/(R+G+B). Consequently, the suggested RGB indices may hold promise for inexpensive chlorophyll estimation in sugar beet leaves during the harvest time, although a direct relationship with nitrogen status still needs to be validated.
PB MDPI
SN 2624-7402
YR 2020
FD 2020
LK https://uvadoc.uva.es/handle/10324/52598
UL https://uvadoc.uva.es/handle/10324/52598
LA eng
NO AgriEngineering, 2020, vol. 2, n. 1, p. 128-149
NO Producción Científica
DS UVaDOC
RD 24-nov-2024