The dimensions of mechanized agricultural systems depend on the edaphoclimatic conditions, crops, and work regimes. This study aimed to geographically estimate the monthly available time and number of favorable hours for agricultural field spraying in the state of Mato Grosso do Sul, Brazil. The meteorological restrictions imposed during unfavorable hours were as follows: ambient temperature above 32 ºC, relative humidity below 50 %, wind speed above 15 km h-1, and volumetric soil humidity above 39 % (equivalent to 90 % of the available water capacity). Mathematical models were then developed considering a period of ten years, which used historical data from the ground monitoring stations of the National Institute of Meteorology within the region. The subsequent algorithm was programmed and installed in a web server to simulate the time required for agricultural field spraying. During the cropping period in the region, there were climatic restrictions on performing agricultural spraying, with relative humidity being the variable with the most significant impact. However, soil moisture conditions restricted the available time for agricultural spraying more than the wind speed, relative air humidity, or ambient temperature.
Nitrogen is the main nutrient required by corn crop, especially in Cerrado soils. Remote sensing techniques can be used to generate additional information now of nitrogen fertilization recommendation. This work investigated the association of plant height and dry matter phenological variables together with NDVI, REDEDGE, SAVI, and IV 760/550 vegetation indices (VIs) with corn grain yield, under different N doses. Sowing occurred in November 2016, at a spacing of 0.45 m between rows and a 60,000 ha-1 plant population. Four N doses (0, 80, 160, and 240 kg of N ha-1) were applied at phenological stage V4. The experimental design consisted of randomized blocks, containing four N doses in topdressing and 16 replications. The active optical sensor Crop Circle ACS-470 was used to obtain the VIs. The NDVI, SAVI, and RE indices have a high positive association with each other and with the variables plant height and dry matter. Polynomial regression equations were adjusted between the variables in response as doses of N. Afterwards, they were estimated as correlations between variables and results expressed through the network of correlations. Finally, a multivariate analysis of canonical variables was performed to understand the interrelationship between the variables and each dose of N applied. NDVI and RE have a positive relationship of moderate magnitude with grain yield in corn crops.
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