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Copyright of Brazilian Journal of Agricultural Sciences / Revista Brasileira de Ciências Agrárias is the property of Universidade Federal Rural de Pernambuco and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The application of biological products in agricultural crops has become increasingly prominent. The growth-promoting bacterium Azospirillum brasilense has been used as an alternative to promote greater yield in maize crops. In the context of precision agriculture, interpreting geospatial data has allowed for monitoring the effect of the application of products that increase the yield of corn crops. The objective of this work was to evaluate the potential of Kriging techniques and spectral models through images in estimating the gain in yield of maize crop after applying A. brasilense. Analyses were carried out in two commercial areas treated with A. brasilense. The results revealed that models of yield prediction by Kriging with a high volume of training data estimated the yield gain with a root-mean-square error deviation (RMSE%), mean absolute percentage error (MAPE%), and R2 to be 6.67, 5.42, and 0.88, respectively. For spectral models with a low volume of training data, yield gain was estimated with RMSE%, MAPE%, and R2 to be 9.3, 7.71, and 0.80, respectively. The results demonstrate the potential to map the spatial distribution of productivity gains in corn crops following the application of A. brasilense. [ABSTRACT FROM AUTHOR]