ABSTRACT: Low efficiency of nitrogen from fertilizers is a major concern worldwide, threatening the sustainability of sugarcane production. The N use efficiency (NUE) by sugarcane can be improved by adopting better fertilizing management practices, reducing environmental impacts. This work evaluated the effects of varying N rates and time of application on stalks and sugar yield in ratoon harvested early in the crop season. The experimental design was a randomized block in a 2 × 4 factorial design and a control (no N) with five replications, including two application times (45 or 90 DAH – days after harvest) and four N rates (50, 100, 150, or 200 kg N ha−1). The time of N fertilizer application promoted differences in stalk yield, as the cumulative yield of two harvests was increased by 8 % (15 Mg ha−1) at 45 DAH when compared to the application at 90 DAH. The application performed at 45 DAH augmented sugar yield by 10 % (2.8 Mg ha−1 of sugar) in relation to 90 DAH. The N rates that promoted the highest sugarcane yield were, respectively, 122 and 144 kg N ha−1 in the first and second crop cycles. The average economical rates obtained for the first and second agricultural cycles were, respectively, 104 and 127 kg N ha−1, demonstrating that the gains by applying high amounts of fertilizers (rates above 150 kg N ha−1) may not cover the investment.

ABSTRACT: Sugarcane (saccharum spp.) in Brazil is managed on the basis of “production environments”. These “production environments” are used for many purposes, such as variety allocation, application of fertilizers and definition of the planting and harvesting periods. A quality classification is essential to ensure high economic returns. However, the classification is carried out by few and, most of the time, non-representative soil samples, showing unreal local conditions of soil spatial variability and resulting in classifications that are imprecise. One of the important tools in the precision agriculture technological package is the apparent electrical conductivity (ECa) sensors that can quickly map soil spatial variability with high-resolution and at low-cost. The aim of the present work was to show that soil ECa maps are able to assist classification of the “production environments” in sugarcane fields and rapidly and accurately reflect the yield potential. Two sugarcane fields (35 and 100 ha) were mapped with an electromagnetic induction sensor to measure soil ECa and were sampled by a dense sampling grid. The results showed that the ECa technique was able to reflect mainly the spatial variability of the clay content, evidencing regions with different yield potentials, guiding soil sampling to soil classification that is both more secure and more accurate. Furthermore, ECa allowed for more precise classification, where new “production environments”, different from those previously defined by the traditional sampling methods, were revealed. Thus, sugarcane growers will be able to allocate suitable varieties and fertilize their agricultural fields in a coherent way with higher quality, guaranteeing greater sustainability and economic return on their production.