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| Filter results3 paper(s) found. |
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1. Beyond the Mean: A Quantile Count Regression Analysis of Precision Farming Technology Adoption Intensity by German FarmersThis study examines the factors influencing precision agriculture technology adoption intensity among German farmers using an innovative quantile count regression approach that reveals heterogeneous relationships across different segments of the adoption distribution. While previous research has primarily relied on mean-based regression models that may mask important variation in adoption determinants, this analysis provides new insights into how factors affect low, moderate, and high technology... M. Michels, O. Musshoff |
2. Can Management Zones Be Useful in Guiding Mechanized Peanut Harvesting?Mechanized peanut harvesting presents challenges due to the crop’s indeterminate growth habit, which results in non-uniform maturation across the field; the ideal harvest point is reached when the maturity index exceeds 0.7. Consequently, analyzing the spatial variability of maturation is essential for identifying homogeneous areas and guiding harvest at the optimal time. In this context, Management Zones (MZs), as a Precision Agriculture tool, enable the subdivision of fields into more... A. Andrade Da Silva, T.C. Moura Oliveira, E. Sales, S. Luns, E.M. Perussi, R.H. De Souza Silva, S. Luns, R.P. Silva, J. , A.L. De Brito Filho , R.P. Silva |
3. Evaluation of the Similarity between Management Zones Based on Spectral Indices and Soil Electrical ConductivityThe delineation of management zones is one of the main strategies in precision agriculture, as it enables site-specific interventions and improves input-use efficiency. Soil electrical conductivity (EC) is widely used to represent the spatial variability of soil physical and chemical attributes and is often considered a reliable indicator. However, acquiring EC data requires specific equipment and field operations, which may increase operational costs. In contrast, spectral indices derived from... |