Abstract
Geospatial technologies are presented as an alternative for the monitoring and control of crops, as demonstrated through the analysis of spectral responses (SR) of each species. In this study, it was intended to determine the effects of the application of nanonutrients (Zn and Mn) in cabbage (Brassica oleracea var. capitate L.) by analyzing the relationship between the vegetation indices (VI) NDVI, GNDVI, NGRDI, RVI, GVI, CCI RARSa and the content of chlorophyll (CC), from two trials established in the field and in the greenhouse, together with the calculation of dry biomass production in the field through the use of digital models and its further validation. The results indicated that for greenhouse experiments no significant differences were found between the VIs in the implemented treatments, rather for their phenological states. Whereas in the field assays it was evidenced that there were significant differences between the VIs for the treatments, as well as for the phenological states. The SR issued in the field allowed the evaluation of the behavior of the crop due to the application of nanonutrients, which did not occur in the greenhouse, in the same way. The SR also enabled the spectral characterization of the crop in its phenological states in the two trials. All this information was stored in a digital format, which allowed the creation of a spectral library which was published on a web server. The validation of the dry biomass allowed, by statistical analysis, the efficiency of the method used for its estimation to be confirmed.
Highlights
Nowadays, precision agriculture is an innovative approach developed within the management of agricultural production systems, as it allows the analysis and monitoring of crops, as well as production factors such as seeds, fertilizers, water control, among others [1,2,3,4,5]
The spectral response can be analyzed by using several vegetation Indexes (IV), such as the Normalized Difference Vegetation Index (NDVI), green band (GNDVI), Normalized Green–Red Difference Index (NGRDI), Regulatory volume increase (RVI), global vegetation index (GVI), chlorophyll content index (CCI), or ratio analysis of reflectance spectra—chlorophyll a (RARSa)
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Summary
Precision agriculture is an innovative approach developed within the management of agricultural production systems, as it allows the analysis and monitoring of crops, as well as production factors such as seeds, fertilizers, water control, among others [1,2,3,4,5]. In the visible part of the spectrum (450–750 nm), the spectral characteristics of vegetation are controlled by the photosynthetic process (absorption), whereas in the near-infrared region (800–1700 nm) they are controlled by the internal structure of the leaves where the incident energy can be reflected between 40% to 50%, depending on the health or type of vegetation [47,48] This information is registered and classified in spectral libraries that aim to facilitate the identification, monitoring, and follow-up of agricultural coverage [49]. The spectral response can be analyzed by using several vegetation Indexes (IV), such as the Normalized Difference Vegetation Index (NDVI), green band (GNDVI), Normalized Green–Red Difference Index (NGRDI), Regulatory volume increase (RVI), global vegetation index (GVI), chlorophyll content index (CCI), or ratio analysis of reflectance spectra—chlorophyll a (RARSa) These indexes are quantitative measurements based on reflectance values as a function of wavelengths, which are used to measure the amount of Agronomy 2022, 12, x FOR PEER REVIEW. The CCM—200 Plus equipment from the Opti-sciences brand was
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