Contributions of leaf analysis to the sustainable and rational use of agricultural inputs

By Luiz Fernando Costa Ribeiro Silva and Letícia Almeida, from the Federal University of Viçosa

09.07.2024 | 15:39 (UTC -3)

Leaf tissue analysis is a very important step in sustainable management, both in the economic and, mainly, environmental spheres. 

This evaluation is very affordable in relation to its cost, which is in the range of R$25,00 – R$40,00/sample for complete chemical analysis. However, values ​​vary depending on the laboratory, region and number of samples. Due to its cost-benefit, it proves to be an important ally that allows the identification of necessary adjustments to the nutritional management of the crop and, consequently, getting closer to the ideal fertilization recommendation for the crop.

The results of leaf analysis require interpretation, as do data from a soil analysis. After this interpretation and correct use of its analyzes there is a greater gain in productivity and economic return on the agricultural property. An example of this return is the information that the nutrient has its content in the appropriate range, but is limiting due to excess when compared to other nutrients, therefore, the expenditure on this nutrient was higher than necessary. This allows the producer to make corrections at the exact point.

There are several methods for interpreting data from a leaf analysis, including: Sufficiency Range, Critical Leaf Level, Integrated Diagnosis and Recommendation System (DRIS), Nutritional Composition Diagnosis (CND), etc. However, there are relative differences between the methods and not all of them are widely used. As an example of this limitation, the mathematical calculations involved in DRIS are complex and not very accessible.

The time of collection, number of plants sampled, which leaf to be sampled is relative to each crop and these data are published in the literature. However, a material that compiles this information is useful for the agronomist, technician and/or producer to speed up the process of analyzing and interpreting plant tissue data. Thus, several materials are found on the internet that enable such action (Figure 1).

Figure 1: example of a spreadsheet that compiles information on material collection methods for leaf analysis
Figure 1: example of a spreadsheet that compiles information on material collection methods for leaf analysis

Methods such as Sufficiency Range, DRIS and CND are the main means of evaluating the nutritional status of plants, as they guarantee the technician greater power to react with the data presented. 

The Sufficiency Range method proposes easy interpretation of analytical results, presenting an ideal range of the evaluated nutrient content. The CND method takes into account mathematical calculations that consider the relationship between all nutrients, a factor that allows nutritional imbalances to be identified. Therefore, it is important to perform interpretation with more than one method to assist in decision making.

The most common method for interpreting the results of leaf analysis is the Sufficiency Range, due to its ease of use (Wadt et al., 2013). Nutritional Composition Diagnosis favors a more accurate diagnosis of the nutritional status of the crop, as it is based on multiple nutrient interactions (Partelli et al., 2014). Furthermore, it is a method that is not as sensitive to some factors such as; cultivar, growth stage or collection leaf position (Gopalasundaram et al., 2012; Mccray et al., 2016).

As an example of data interpretation, it can be suggested that limitations due to deficiency of cationic nutrients (K, Ca and Mg), when they occur more frequently, are due to insufficient base saturation (Dezordi et al., 2016). An interpretation that would not be entirely possible with soil analysis alone.

After understanding the importance of leaf analysis for determining the nutritional status of plants, one can see how effective it is not only in this regard, but also in optimizing the decision-making resources of the technician, producer, agronomist and everyone responsible for agriculture. worldwide.

*By Luiz Fernando Costa Ribeiro Silva e Leticia Almeida, from the Federal University of Viçosa

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