Agronomic characteristics associated with the normalized difference vegetation index (NDVI) in the peanut crop

Abstract

Advances in agricultural technology have led to the development of active remote sensing equipment that can potentially estimate components of crop production; however, this assessment is still in its early stages for the peanut crop. The objective of this study was to evaluate the normalized difference vegetation index (NDVI) generated by a terrestrial sensor and its relationship with agronomic variables of peanut crops grown at different densities. The parameters evaluated were the NDVI, pod yield, mass of 100 grains, green and dry mass and vegetation cover. The study was conducted in an experimental field and used a randomized block design with plots consisting of four plant populations (86,111, 103,520, 127,603 and 141,144 plants ha -1 ) with six replicates per treatment. The two densest populations of peanut plants showed similar behavior among the variables analyzed, whereas the variables of vegetation cover, yield and plant population strongly correlated with the NDVI obtained by the terrestrial sensor. For the seeding rates, the higher densities (14 and 18 seeds m -1 ) are the most recommended because showed the highest values of productivity and vegetation cover. The results indicated that the NDVI obtained through the GreenSeeker sensor can be used to estimate productivity, vegetation cover and plant population on peanut crop. This may provide an additional tool for farmers to evaluate the potential of their culture; enabling even that agronomic measures can take effect so that this potential is improved.

Vegetation indices in the prediction of biomass and grain yield of white oat under irrigation levels

“…The biomass estimate was not as accurate as the grain yield estimate. In peanut, Zerbato et al (2016) reported an R 2 of 0.27 in the estimation of crop biomass, whereas, in rice and barley, the highest R 2 Figure 5. Performance of the models using the IRVI in the estimation of white oat grain yield at the stages 4 (a), 8 (b), 10 (c) and 10.5.4 (d), according to the phenological scale of Feeks and Large (Large 1954).…”

Correlations Among Vegetation Indices and Peanut Traits During Different Crop Development Stages

“…According to Amaral et al (2015a), many active optical sensors can be found, but there is little research comparing the efficiency of these devices for the determination of the parameters of cultures. Using terrestrial remote-sensing with the Normalized Difference Vegetation Engenharia Agrícola, Jaboticabal, v.39, special issue, p.33-40, sep. 2019 Index (NDVI) associated with agronomic characteristics of the peanut crop, it was previously verified that results obtained with the GreenSeeker sensor can be used to determine the population characteristics of plant cover and yield estimates, and as an additional tool for farmers to detect crop potential (Zerbato et al, 2016).…”

Use of Active Optical Sensor in the Characteristics Analysis of the Fertigated Brachiaria With Treated Sewage

“…Zerbato et al (2016), evaluating the linear correlation between NDVI and peanut yield in the production of green and dry peanut mass, obtained positive linear regression and determination coefficients of 0.3161 and 0.2761, respectively. The low NDVI values were attributed to naked soil exposure between rows of plants.…”

“…One of the applications of the geotechnologies use is the estimation of agricultural productivity and the nutritional status of the crops in a fast and precise way, due to the close relation between these variables and vegetation indices (Zerbato et al, 2016). The high correlation between biomass accumulation and vegetation indices occurs due to the high levels of chlorophyll in the plant, which varies according to the environmental conditions and crop management, such as nitrogen application, resulting in increments of leaf area and photosynthetic activity (Grohs et al, 2011).…”