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The Plant Response Potential to Fertilization (RPF) method, as it has been interpreted, may result in nutritional diagnoses with low efficiency. In this regard, this work aimed to validate the RPF criterion and determine the percent value to be considered as culm yield increase based on the accuracy of nutritional diagnoses for nutrient P in sugarcane by the CND method. The study used data collected from five experimental areas located in three municipalities in the state of São Paulo, Brazil, in 2013 crop year. Database comprised productivity and leaf contents of nutrients obtained from the reference population that indicated yields over 172 tons ha−1. The CND indices were interpreted by the RPF criterion, with introduction of variable f, and accuracy was determined considering as insufficient diagnosis when the addition of P resulted in yields increase over 5; 10; 15; 20; 25; 30; 35 and 40% between the control situation and the response situation. The use of factor f = 0 in the IBNm adjustment allowed to obtain higher sugarcane culm yields or lower yield losses, which corresponds to the abandonment of interpretation of nutritional indices by the RPF method. The CND is effective in assessing the plants nutritional status when culm yield increases over 35 and 40% are used as reference between the control situation and the response situation with application of P in sugarcane crops. [ABSTRACT FROM AUTHOR]

The use of accuracy measures for modeling the formulas of the Comprehensive Diagnosis and Recommendation System (DRIS), can improve the efficiency of the method in assessing the nutritional status in sugarcane. Therefore, the objective was to use the accuracy measures proposed by Wadt and Lemos for the modeling of DRIS formulas in sugarcane, based on the nutritional status for phosphorus. The database was created based on productivity and leaf contents of N, P, K, Ca, Mg, S, B, Cu, Fe, Mn and Zn for sugarcane, considered in two agricultural years. (2013 and 2014) making a total of 1,224 samples. DRIS formula modeling was performed using the seven accuracy measures proposed by Wadt and Lemos. The lowest productivity losses were registered using the sensitivity factor f = 2.5 and the productivity response limit of 40% in the 2013 and 2014 harvest. However, there is a need for a greater number of studies to achieve productivity gains when adopt DRIS to assess the nutritional status of sugarcane. The measure of accuracy of nutritional sufficiency at the response limit of 20 and 40% showed a better performance, which can avoid losses in the management of fertilization. [ABSTRACT FROM AUTHOR]

The use of different criteria for the definition of the reference population, combined with measures of accuracy of nutritional diagnoses, can enable the definition of the best set of Integrated Diagnosis and Recommendation System (DRIS) standards for sugarcane. In this context, the objective was to use the accuracy measures proposed by Wadt and Lemos to define the best criterion for defining the reference population for the DRIS method in sugarcane, based on the nutritional status for phosphorus. The database was created based on productivity and leaf contents of N, P, K, Ca, Mg, S, B, Cu, Fe, Mn and Zn for sugar cane, considered in two agricultural years (2013 and 2014), making a total of 1,224 samples, composed of five reference populations that showed productivity above 172; 193; 214; 235 and 256 t ha−1. The Average Nutritional Balance Index (NBIm), DRIS index and productivity were studied; degree of agreement between standards and measures of accuracy of nutritional diagnoses for phosphorus. The measures of global accuracy, excess and nutritional deficiency, showed diagnostic performance below 50% in the 2013 and 201 harvests. The accuracy for balance, sufficiency and nutritional toxicity showed high performance of the nutritional diagnoses regardless of the harvest. The analysis of the accuracy of the nutritional diagnoses for phosphorus identified low performance of all sets of DRIS standards, however, with better performance of the standards derived from reference populations of average productivity + 1.0 standard deviation in the 2013 and 2014 harvests. [ABSTRACT FROM AUTHOR]