Model performance in estimating the yield of common bean cultivars

Vinicius Augusto Filla, Anderson Prates Coelho, João Victor Trombeta Bettiol, Fábio Tiraboschi Leal, Leandro Borges Lemos, David Luciano Rosalen


The use of vegetation indices has good potential for predicting the productivity of several crops, but factors such as the time of assessment, cultivar, and plant phenology can influence the performance of predictive models. The objective of this study was to evaluate and compare the precision of estimating the common bean grain yield, according to the normalized difference vegetation index (NDVI), using individual models per cultivar and a general model with all cultivars. The cultivars IAC Imperador and IPR Campos Gerais, with determined and indeterminate growth habits, respectively, were evaluated. They were subjected to different nitrogen management methods to provide grain yield variability. NDVI evaluations were conducted throughout the culture cycle on six dates during the vegetative and reproductive stages. The common bean grain yield was estimated with high precision as a function of NDVI, obtaining a precision of up to 78% and an average error close to 350 kg ha-1. The greatest fit of estimation was obtained in the phenological reproductive stages of beans, especially after crop flowering. General models, composed of data from more than one cultivar, had similar precision and, in some cases, superiority to the fitted models for each cultivar, demonstrating the feasibility of using the same model for several genotypes.


Crop forecast. NDVI. Phaseolus vulgaris L.. Remote sensing. Vegetation index.

Texto completo:

PDF (English)


AMARAL, C. B.; OLIVEIRA, G. H. F.; MÔRO, G. V. Phenotyping open-pollinated maize varieties for environments with low nitrogen availability. Archives of Agronomy and Soil Science, 64, n. 10, p. 1465-1472, 2018.

BELSLEY, D. A.; KUH, E.; WELCH, R. E. Regression diagnostics: identifying data and sources of colinearity. New York: John Wiley & Sons Inc., 1980. 292 p.

CASA, R.; CASTRIGNANÒ, A. Analysis of spatial relationships between soil and crop variables in a durum wheat field using a multivariate geostatistical approach. European Journal of Agronomy, 28, n. 3, p. 331-342, 2008.

CAO, Z. et al. A new three-band spectral index for mitigating the saturation in the estimation of leaf area index in wheat. International Journal of Remote Sensing, v. 38, n. 13, p. 3865-3885, 2017.

COELHO, A. P. et al. Estimation of irrigated oats yield using spectral indices. Agricultural Water Management, v. 223, 105700, 2019.

COELHO, A. P. et al. Validation of white oat yield estimation models using vegetation indices. Bragantia, 79, n. 2, p. 236-241, 2020.

CONAB. Companhia Nacional de Abastecimento. Acompanhamento da safra brasileira de grãos - Safra 2020/2021 - Quarto levantamento. Brasília, DF: CONAB, 2021. 85 p.

CORNELL, J. A.; BERGER, R. D. Factors that influence the value of the coefficient of determination in simple linear and nonlinear regression models. Phytopathology, 77, n. 1, p. 63-70, 1987.

DAMIAN, J. M. et al. Applying the NDVI from satellite images in delimiting management zones for annual crops. Scientia Agricola, 77, n. 1, e20180055, 2020.

DUAN, T. et al. Dynamic monitoring of NDVI in wheat agronomy and breeding trials using an unmanned aerial vehicle. Field Crops Research, v. 210, p. 71-80, 2017.

SANTOS, H. G. et al. Sistema brasileiro de classificação de solos. 5 ed. Brasília, DF: Embrapa, 2018. 356 p.

ESQUERDO, J. C. D. M.; JÚNIOR, J. Z.; ANTUNES, J. F. G. Use of NDVI/AVHRR time-series profiles for soybean crop monitoring in Brazil. International Journal of Remote Sensing, v. 32, n. 13, p. 3711-3727, 2011.

FERNÁNDEZ DE CÓRDOVA, F.; GEPTS, P. L.; LÓPEZ GENES, M. Etapas de desarrollo de la planta de frijol comúm (Phaseolus vulgaris L.). Cali: CIAT, 1986. 33 p.

FLÔRES, J. D. A. et al. Agronomic and qualitative traits of common bean as a function of the straw and nitrogen fertilization. Pesquisa Agropecuária Tropical, v. 47, n. 2, p. 195-201, 2017.

GROHS, D. S. et al. Modelo para estimativa do potencial produtivo em trigo e cevada por meio do sensor GreenSeeker. Engenharia Agrícola, v. 29, n. 1, p. 101-112, 2009.

GUAN, S., K. et al. Assessing Correlation of High-Resolution NDVI with Fertilizer Application Level and Yield of Rice and Wheat Crops Using Small UAVs. Remote Sensing, v. 11, n. 2, 112, 2019.

HASSAN, M. A. et al. A rapid monitoring of NDVI across the wheat growth cycle for grain yield prediction using a multi-spectral UAV platform. Plant Science, v. 282, p. 95-103, 2019.

KATSUHAMA, N. et al. Discrimination of areas infected with coffee leaf rust using a vegetation index. Remote Sensing Letters, v. 9, n. 12, p. 1186-1194, 2018.

LEWIS, J. E.; ROWLAND, J.; NADEAU, A. Estimating maize production in Kenya using NDVI: some statistical considerations. International Journal of Remote Sensing, v. 19, n. 13, p. 2609-2617, 1998.

LI, T. et al. Uncertainties in predicting rice yield by current crop models under a wide range of climatic conditions. Global Change Biology, v. 21, n. 3, p. 1328-1341, 2015.

LUMBIERRES, M. et al. Modeling biomass production in seasonal wetlands using MODIS NDVI land surface phenology. Remote Sensing, v. 9, n. 4, 392, 2017.

MAIA, S. C. M. et al. Criteria for topdressing nitrogen application to common bean using chlorophyll meter. Pesquisa Agropecuária Brasileira, v. 52, n. 7, p. 512-520, 2017.

MONTEIRO, P. F. C. et al. Assessing biophysical variable parameters of bean crop with hyperspectral measurements. Scientia Agricola, v. 69, n. 2, p. 87-94, 2012.

SULTANA, S. R. et al. Normalized difference vegetation index as a tool for wheat yield estimation: a case study from Faisalabad, Pakistan. The Scientific World Journal, v. 2014, p. 1-8, 2014.

SANDRINI, F. D. O. T. et al. Índices de vegetação na estimativa da produtividade do feijoeiro cultivado sob doses de nitrogênio. Revista Brasileira de Ciências Agrárias (Agrária), v. 14, n. 4, e7310, 2019.

SEO, B. et al. Improving remotely-sensed crop monitoring by NDVI-based crop phenology estimators for corn and soybeans in Iowa and Illinois, USA. Field Crops Research, v. 238, p. 113-128, 2019.

SORATTO, R. P. et al. Nutrient extraction and exportation by common bean cultivars under different fertilization levels: I-macronutrients. Revista Brasileira de Ciência do Solo, v. 37, n. 4, p. 1027-1042, 2013.

SOUZA, A. M. et al. Most consumed food in Brazil: National Dietary Survey 2008-2009. Revista Saúde Pública, v. 47, supl. 1, p. 190s-199s, 2013.

VIAN, A. L. et al. Nitrogen management in wheat based on the normalized difference vegetation index (NDVI). Ciência Rural, v. 48, n. 9, e20170743, 2018.

YANG, H. et al. Seasonal variations of leaf and canopy properties tracked by ground-based NDVI imagery in a temperate forest. Scientific Reports, v. 7, 1267, 2017.

Revista Ciência Agronômica ISSN 1806-6690 (online) 0045-6888 (impresso), Site:, e-mail: - Fone: (85) 3366.9702 - Expediente: 2ª a 6ª feira - de 7 às 17h.