Application of diagnosis and recommendation integrated system (DRIS) to sugarcane: a systematic literature review

Abstract

The Diagnosis and Recommendation Integrated System (DRIS) is widely used for the interpretation of diagnostics from chemical analyses of soil and plant tissue in different cultures. The objective is to carry out a systematic literature review on the feasibility of applying DRIS to the diagnosis of current soil fertility and nutritional status of sugarcane crops. Searches were carried out in five databases (Web of Science, Springer Link, Science Direct, Scielo, and Google Scholar). For this, eight search terms (T) were used: (T1: DRIS, T2: sugarcane, T3: soil analysis, T4: leaf analysis; T5: nutritional diagnosis; T6: soil fertility; T7: critical levels; T8: sufficiency ranges), and 14 combinations (C) of the terms. Each combination was searched in three languages (English, Portuguese and Spanish) in each database. The selection criteria for publications were as follows: scientific articles, answering at least one of the following questions (Q): Q1. Is DRIS efficient in determining the nutritional diagnosis of sugarcane as a function of leaf nutrient content? Q2. Is DRIS efficient in determining soil fertility cultivated with sugarcane as a function of soil chemical analysis? Q3. Can DRIS be used to replace the critical levels and/or sufficiency ranges method? The searches yielded 1,547 results, of which, after careful analysis, only 17 met the prerequisites and were selected. The articles dated from 1976 to 2022, written by 17 different authors. There is a scarcity in the literature of works that relate the DRIS methodology in sugarcane cultivation to the results of soil analysis and that compare DRIS to conventional methods of soil and leaf nutritional diagnosis. Based on the literature surveyed, in general, DRIS is efficient in assessing the nutritional status of sugarcane and soil fertility in cultivation areas; however, its efficiency increases when there are standards and calculations of indexes based on local or regional data.