Modelo agrometeorológico-espectral de estimativa de rendimento de grãos de trigo no Rio Grande do Sul

Abstract

Agrometeorological-spectral model to estimate wheat yield in the State of Rio Grande do Sul, BrazilThis study aimed to estimate the wheat yield within the Cotrijal Cooperative's operational area (northern Rio Grande do Sul), using spectral and meteorological variables. Yield data (1991)(1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006), monthly agrometeorological data (1991)(1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006) and spectral data (NDVI/MODIS, 2000-2006 were used in the analyses. The existence of a significant increase in grain yield due to the incorporation of new technologies was analyzed (technology trend).The choice of the independent variables was based on the analysis of the correlation between yield and spectral and meteorological data. For the multiple linear regression of grain yield estimation the following independent variables were used: rainfall (October), frost damage index (September), degree-days (accumulated from May to October) and NDVI (integrated from June to October). The multiple linear regressions showed satisfactory results with estimation errors below 10%, in most examined years. Accuracy, easy implementation and low cost of regressions pointed to the possibility of joint use of spectral and agrometeorological data in estimating wheat yield in the Cotrijal region. However, further studies are recommended to verify the results of the generated models when incorporating a longer series of spectral data.

Soybean yield modeling using bootstrap methods for small samples

“…Although the model determined by this method (M 71 ) has been the same selected by the conventional method using Akaike, the application of this methodology serve to attest the 10 ical variables in this essay to be due to the fact of the limitation on the spatial representation of the results to be obtained from the collected data in weather stations. (Junges & Fontana, 2011).…”

Correlations between spectral and biophysical data obtained in canola canopy cultivated in the subtropical region of Brazil

“…Junges (2011) found positive correlations between the maximum and the integrated NDVI, for wheat grain yield in Rio Grande do Sul. Similarly, Rodrigues et al (2013) associated vegetation indices and absorption of atmospheric CO 2 , which is useful in the context of climate change discussions.…”

“…Studies have been conducted in areas with climatic and management conditions similar to those of the present study for the following annual crops: soybean (Melo et al, 2008), irrigated rice (Klering et al, 2016), and wheat (Junges & Fontana, 2011). Despite the importance of grain yield studies, models to estimate canola grain yields adjusted to the specific management and climate conditions of the state of Rio Grande do Sul are not yet available in the literature.…”

Modelo agrometeorológico-espectral para estimativa da produtividade de grãos de arroz irrigado no Rio Grande do Sul

“…Nesses levantamentos, são considerados dados obtidos através de entrevistas com produtores, cooperativas agrícolas e informações de crédito agrícola (Junges e Fontana 2011). A obtenção dessas informações é trabalhosa e onerosa, e os dados coletados, de certa forma, são subjetivos (Liu 2007).…”