Potencial e lacunas de produtividade na cultura da mandioca em ambiente subtropical

Abstract

With the increase in the world population, expected to occur by the end of the century, there is a need to boost food production. The sustainable alternative to achieve higher production is to improve yield of agricultural crops, among which cassava has a fundamental role. Knowledge of potential yield and yield gap, as well the biophysical and management factors in each agricultural system, is critical to obtain success in this challenge. The aim of this work is to estimate the potential yield and yield gap for cassava crop in a subtropical environment by identifying and quantifying the main biotic and management factors that limit or reduce crop yield. For the estimation of the potential yield, 9 buffer zones (climatic regions) were created, taken in consideration a coverage area greater than 5% of the cassava production, and the meteorological data were obtain from INMET stations. The yield potential and the water-limited yield potential were estimated using the Simanihot model, and the yield gaps were calculated from the average yield of 15 years of IBGE data, and the average yield of farmers in the Central Region (106 surveys). A regression tree was created in order to identifying the factors responsible for the yied gaps. In view of the current yield levels in the state of Rio Grande do Sul, this study allowed a better understanding of the factors that contribute to the reduction of cassava yield. The yield potential ranged from 51.9 to 61.7 ton.ha- 1 between the regions of Rio Grande do Sul, where the mean obtain for the state was 56.2 and 54.9 ton.ha- for yield potential and water-limited yield potential, respectively. The yield gap varied from 66 to 78% of the PP, where the contribution of water-limited gap (% LPPA) was 1.3 ton.ha-1 (3%) and the contribution caused by the gap of management (% LPM) was 39.8 ton.ha-1 (97%). The Central Region of RS showed the smallest management gap, where plant density can be the main factor causing this gap. Others factors such as planting date and weed control number, also can be added to plant density as factors that drive the management gap.