Universality of Kenworthy and DRIS norms for prata and cavendish bananas grown in two environments

Filho, Vagner Alves Rodrigues; Neves, Júlio César Lima; and, Sérgio Luiz Rodrigues Donato; Guimarães, Bruno Vinícius Castro

doi:10.36783/18069657rbcs20200120

Cited by 9 publications

(10 citation statements)

References 27 publications

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“…These differences in nutrient content affect DRIS norms because, in each study, the edaphoclimatic conditions are different. Rodrigues Filho et al 15 studied in two different Brazilian regions and added that differences in soil fertility, as well as in non-nutritional factors, interfere with DRIS norms. In light of this, the importance of speci c DRIS norms to diagnose nutrient imbalances in banana plantations in southern Ecuador is evident.…”

Section: Discussionmentioning

confidence: 99%

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New Approach to the Applicability of DRIS in Bananas Based on the Accuracy of Nutritional Diagnoses for Nitrogen and Potassium

Villaseñor-Ortiz

Prado

Silva

et al. 2022

Preprint

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DRIS (Diagnosis Recommendation Integrated System) is a tool used in the interpretation of leaf analyses that values the balance of nutrients, an important fact for a better assessment of the nutritional status of banana plants. Its usefulness depends on the ability to identify the nutrients that limit productivity in order to correct possible nutritional imbalances, but there is a lack of research in all crops, including bananas, to assess the accuracy of these diagnoses, which have a worrying global implication. To this end, this study evaluates DRIS norms for banana cultivation in Ecuador and the use of accuracy measurements for nutritional diagnosis, verifying the capacity of DRIS to detect true nutritional status based on plant response. The database created here contains 233 results referring to productivity and leaf contents of N, P, K, Ca, Mg, S, Cl, Fe, Mn, Cu, B, and Zn for banana trees in 2018, 2019, and 2020. Then, a field experiment evaluated doses of nitrogen and potassium and the accuracy of DRIS norms for N and K. The results show that the DRIS of banana produced in Ecuador depends on the nutrient being variable according to the crop nutritional status. The DRIS norms for diagnosis of N and K result in an acceptable accuracy to identify only deficiencies and toxicities, respectively, indicating the need for adjustments in these standards for later use in the field. Thus, there is a need for more research aiming to adopt calibrated DRIS diagnostic norms to assess the nutritional status of bananas in Ecuador.

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Section: Discussionmentioning

confidence: 99%

“…For example, some authors used the DRIS method, to obtain nutritional diagnostic standards for banana cultivation in some regions of the world [11][12][13][14][15] . The database of leaf samples and productivity ranged from 68 to 915 observations.…”

Section: Introductionmentioning

confidence: 99%

New Approach to the Applicability of DRIS in Bananas Based on the Accuracy of Nutritional Diagnoses for Nitrogen and Potassium

Villaseñor-Ortiz

Prado

Silva

et al. 2022

Preprint

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“…After the establishment of DRIS norms, DRIS-I, NBI, and mNBI indices are applied to identify deficiencies, excesses, or nutritional balance of macronutrients (N, P, K, Ca, Mg, S) and micronutrients (Fe, Mn, Zn, Cu, Mo, B) in leaf tissue. The results of these studies have been applied mainly in Brazil, in crops of wide commercial interest such as cotton, banana, soybean, potato, cacao, and sugarcane (Araújo et al, 2019;Dos Santos et al, 2019;Oliveira et al, 2019;Pereira et al, 2013;Pereira & Justino, 2021;Rodrigues-Filho et al, 2021), and in other agricultural species, including beans, garlic, carrots, atemoya, and cactus pear (Table I).…”

Section: A Nutrient Balance In Leaf Tissuementioning

confidence: 99%

Sistema Integrado de Diagnóstico y Recomendación, su aplicación y utilidad en la agricultura. Una Revisión

Carvajal

Álvarez

Gutiérrez³

2021

Cien. Agri.

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El equilibrio de nutrientes determina el rendimiento y calidad de los cultivos. El Sistema Integrado de Diagnóstico y Recomendación-DRIS propone un análisis holístico sobre la base de la interrelación entre nutrientes, compara las proporciones de los elementos minerales de los cultivos con valores óptimos conocidos como normas DRIS e identifica desequilibrios, deficiencias y/o excesos en los nutrientes de la planta para clasificarlos por orden de importancia. Existen trabajos de revisión científica orientados al desarrollo de propuestas metodológicas para obtención de las normas DRIS en diversos cultivos y el cálculo de sus respectivos índices, pero, estos no dilucidan las funcionalidades reales de este sistema de diagnóstico; por lo tanto, la siguiente revisión tiene como objetivo, dar a conocer las aplicaciones y utilidades del DRIS en la agricultura a nivel mundial desarrolladas durante los últimos 10 años. Considerando lo anteriormente expuesto los estudios científicos sugieren: balance de nutrientes en tejido foliar y suelo, dinámica de elementos minerales según etapa fenológica, niveles críticos y rangos de suficiencia, relación suelo-planta, balance nutricional por uso de fertilizantes y abonos verdes, variabilidad espacial y DRIS, translocación de metales pesados, nutrición e incidencia de problemas fitosanitarios, fitotoxicidad en plantas irrigadas con aguas residuales de riego agrícola, Rangos de Suficiencia en tejido foliar bajo condiciones salinas, análisis de savia y normas DRIS en semillas. El DRIS es una herramienta para el diagnóstico nutricional, susceptible de validación en los sistemas agrícolas a nivel mundial.

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“…Adequate nutrition of banana plants depends on the availability of nutrients in the rhizosphere, statically predicted by soil analysis, and on the consequent absorption by the plant, evaluated by tissue analysis, which better reflects the dynamics over the whole process. This suggests that leaf analysis interpretation requires the adjustment of specific, local norms or reference values, to the detriment of universal norms (Rodrigues Filho et al, 2021a).…”

Section: Introductionmentioning

confidence: 99%

“…For 'Prata-Anã' banana, in different regions, norms were adjusted by methods involving univariate relationships between nutrients, such as Sufficiency Range, SR (Pereira et al, 2015;Silva, 2015), Critical Level, CLz (Carvalho Júnior et al, 2019) and Boundary Line, BL (Rodrigues Filho et al, 2021b); bivariate relationships, such as Diagnosis and Recommendation Integrated System, DRIS (Pereira et al, 2015;Rodrigues Filho et al, 2021a;Carvalho, 2006) and Balance Indices of Kenworthy, BIKW (Rodrigues Filho et al, 2021b); multivariate relationships, such as Compositional Nutrient Diagnosis, CND (Lima Neto et al, 2021); and machine learning, CoDa (Lima Neto et al, 2020). In addition, the Mathematical Chance, MCh (Wadt et al, 1998) was also applied, which according to the authors allows the use of data from leaf analysis and yield of commercial plantations or calibration tests as long as they are robust.…”

Section: Introductionmentioning

confidence: 99%

Nutrient reference values for ‘BRS Platina’ banana in improved fertility soils

et al. 2022

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Reference values of leaf nutrient contents are essential for nutritional assessment of plants. The objective was to establish nutritional reference values for ‘BRS Platina’ banana in improved fertility soil, using the sufficiency range (SR), border Line (BL) and mathematical chance (MCh) methods, in addition to the critical level obtained by the reduced normal distribution (CLz). The study was carried out in Guanambi-BA, considering nutrient contents and yields of an experiment arranged in randomized blocks, 5 x 6 factorial scheme, with five doses of K2O (0, 200, 400, 600 and 800 kg ha-1) supplied with fertilizers for organic management and six sampling times (210; 390; 570; 750; 930 and 1,110 days after planting), totaling 90 plots. Plots with high yield, ≥ 38.40 t ha-1, formed the reference population and plots with yield ≥ 47.43 t ha-1 formed the reference subpopulation. There was convergence between the optimal values obtained by the methods evaluated. Therefore, the reference values adjusted by the SR, BL, MCh and CLz methods can be used with assertiveness to interpret the foliar analysis of the ‘BRS Platina’ banana in improved fertility soils. Furthermore, among these, MCh stands out as it provides narrower optimal ranges.

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Universality of Kenworthy and DRIS norms for prata and cavendish bananas grown in two environments

Cited by 9 publications

References 27 publications

New Approach to the Applicability of DRIS in Bananas Based on the Accuracy of Nutritional Diagnoses for Nitrogen and Potassium

New Approach to the Applicability of DRIS in Bananas Based on the Accuracy of Nutritional Diagnoses for Nitrogen and Potassium

Sistema Integrado de Diagnóstico y Recomendación, su aplicación y utilidad en la agricultura. Una Revisión

Nutrient reference values for ‘BRS Platina’ banana in improved fertility soils

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