ABSTRACT Spatial variability management of soil chemical attributes is one of the approaches to be employed in the face of the constant challenge of increasing agricultural yield to meet world demand. In this sense, precision agriculture has as one of its tools the application of inputs at varying rates, which seeks to determine the ideal amount of fertilizer at each point of the crop, contrary to the conventional recommendation approach based on average values. In this context, this work studied the fertilizer recommendation methods used in site-specific nutrient management and the calculation methodologies for N, P, and K recommendations. For this purpose, a systematic literature study (SLS), consisting of systematic literature mapping, snowballing, and systematic literature review was performed. The analyzed studies were grouped into five domains (precision agriculture, soil fertility, site-specific nutrient application, fertilizer recommendation methods, and recommendation software for site-specific nutrient application). As a result, the SLS identified 12 methods for recommending N, nine for recommending P, and six for recommending K, in addition to five computer programs for precision agriculture that perform fertilizer recommendations at varying rates.

ABSTRACT The application of nitrogen (N) fertilizer is complex and expensive, so its correct management has financial and environmental benefits. The use of optical proximity sensors is a promising technique. However, the movement of the agricultural machinery or of the person carrying the sensor will result in height differences and/or different tilt and twist angles with respect to the canopy. We considered whether these variations would affect the reflectance measurement. In this study, we took normalized difference vegetation index (NDVI) readings of a wheat canopy, to which 90 kg ha-1 of urea had been applied in stage 5, and observed the NDVI in stages 6, 8 and 10.5. We also tested soybeans, to which 90 kg ha-1 of urea had been applied in stage R1, and took NDVI readings in stages R2 and R5. Our goal was to study the effects of the position of an active reflectance sensor (GreenSeeker) on the NDVI index at different heights and at different angles to the canopy. We observed that the height of the sensor affected the NDVI depending on the stage of the plant and that angles up to 15° of the sensor did not directly affect the readings.

ABSTRACT: Optimization of N management is one of the great challenges to be overcome in grain production, as it is directly related to productivity and can also cause environmental damage. Precision agriculture aims to solve this problem by applying nitrogen fertilizer at varying rates. Reflectance sensors are instruments capable of estimating N needs in various crops, including grain crops. However, it is not clear how these sensors perform under varying solar radiation and cloud cover, due to a lack of research on their temporal variability. Thus, this study examined the temporal variability of the NDVI (normalized difference vegetation index), as measured by an active reflectance sensor, in both soybean and wheat crops. The NDVI data were collected using a GreenSeeker sensor every 15 minutes over 12 or 14 consecutive hours. Incident solar radiation was recorded using an Instrutherm MES-100 pyranometer. In all experiments in soybean and wheat, NDVI was negatively influenced by irradiation, showing higher values at the beginning and end of the day. Changes in cloud cover also affected NDVI values during the experiments.