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Quantification and decomposition of yield gap of sugarcane mill

Grant number: 18/06396-7
Support type:Scholarships in Brazil - Master
Effective date (Start): January 01, 2019
Effective date (End): February 29, 2020
Field of knowledge:Agronomical Sciences - Agronomy - Agricultural Meteorology
Principal Investigator:Fabio Ricardo Marin
Grantee:Leticia Gonçalves Gasparotto
Home Institution: Escola Superior de Agricultura Luiz de Queiroz (ESALQ). Universidade de São Paulo (USP). Piracicaba , SP, Brazil


Economic projections indicate that by 2050 the world's population will increase by approximately 30% and consequently, demand for food will increase, while the area available for horizontal expansion of agriculture in the world is at most 5%. This realization implies the need to raise agricultural production in a sustainable way to ensure the future food supply of humanity. The identification of regions with potential to increase agricultural production can be made based on the agricultural efficiency analysis, given by the ratio between real yield (Yr) and potential yield (Yp) (or attainable) of a region; this analysis can also be done by the yield gap (Yg), given by the difference between Yp and Yr. Several studies have been carried out in this line for different cultures and in several countries of the world, usually at large spatial scales. There is, however, a demand for such studies in productive units, thus allowing producers to observe unused production and to intervene in the system in order to increase their productivity. The objective of this project is to quantify the agricultural efficiency of a sugarcane mill and which (and the weight of each) the main limiting and reducing factors that prevent the expression of the mill's yield. In order to do so, it is intended to use the DSSAT/CANEGRO model to simulate potential yield and compare it with the actual yield that will be obtained from the mill's data banks in the field scale. Thus, it will be possible to calculate the agricultural efficiency and map the efficiency of the plant and the Yg, per plot. The project will then move to a second phase, based on the field data collection, in which the selection of some plots in different environments (A and E, for example) with different levels of efficiency (high and low efficiency environment A); sites with high and low efficiencies in environment E). In these selected fields they will be visited with a pre-established methodology for identification and quantification of limiting and reducing factors. Finally, such surveys will be converted into losses through production functions available in the literature for each of the factors raised, finally to quantify and quantify Yg. Thus, it is hoped to support the producers in the construction of a plan to raise yield and prioritize investments in this planning. (AU)