Prediction of Sugarcane Yield by Soil Attributes under Straw Removal Management

Sugarcane (Saccharum spp.) straw removal from the field has the potential to produce short-term gains at the cost of long-term sustainability. The objective of this study was (i) to develop a model capable to predict sugarcane yield (straw and stalk) by soil attributes and (ii) to discover why yields are minimally impacted following straw removal. In this 2-yr experiment, the sugarcane straw removal effects on crop yields and soil attributes were investigated at two sites, Valparaiso and Capivari, in southeastern Brazil. Soil samples from the 0–5, 0–10, 0–20, and 0–30 cm were analyzed for C, N, Ca, Mg, P, K, pH, bulk density (BD), and soil penetration resistance (PR). The data were subjected to descriptive statistical, geostatistical, correlation and regression analyses. The findings showed that the straw and stalk yield can be predicted using soil attributes data at sites where the straw is removed. The best modeling coefficients for stalk yield were obtained using soil data from the 0–20 cm layer. The straw removal induced reduction in soil C, chemical and physical quality (0–5 cm) depending on site, but did not result in lower yields. The research findings provide important information that will lead to sustainable bioenergy production in Brazil.