Accuracy of Various Sampling Techniques for Precision Agriculture: A Case Study in Brazil

被引:1
|
作者
Valente, Domingos Sarvio Magalhaes [1 ]
Pereira, Gustavo Willam [2 ]
de Queiroz, Daniel Marcal [1 ]
Zandonadi, Rodrigo Sinaidi [3 ]
Amaral, Lucas Rios do [4 ]
Bottega, Eduardo Leonel [5 ]
Costa, Marcelo Marques [6 ]
Coelho, Andre Luiz de Freitas [1 ]
Grift, Tony [7 ]
机构
[1] Univ Fed Vicosa UFV, Dept Agr Engn, BR-36570900 Vicosa, Brazil
[2] Inst Fed Sudeste Minas Gerais Campus Muriae IF Sud, BR-36884036 Muriae, Brazil
[3] Univ Fed Mato Grosso UFMT, Inst Agr & Environm Sci, BR-78550728 Sinop, Brazil
[4] Univ Campinas FEAGRI UNICAMP, Sch Agr Engn, BR-13083875 Campinas, Brazil
[5] Univ Fed Santa Maria UFSM, Acad Coordinat, Campus Cachoeira Sul, BR-96503205 Santa Maria, Brazil
[6] Univ Fed Jatai UFJ, Inst Agr Sci, BR-75801615 Jatai, Brazil
[7] Univ Illinois, Dept Agr & Biol Engn, Urbana, IL 61801 USA
来源
AGRICULTURE-BASEL | 2024年 / 14卷 / 12期
关键词
soil fertility; variable-rate application; geostatistics; management zones; MACHINE LEARNING-METHODS; APPARENT SOIL; ELECTRICAL-CONDUCTIVITY; MANAGEMENT ZONES; INTERPOLATION; DELINEATION; VARIOGRAMS; PH;
D O I
10.3390/agriculture14122198
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
Precision agriculture techniques contribute to optimizing the use of agricultural inputs, as they consider the spatial and temporal variability in the production factors. Prescription maps of limestone and fertilizers at variable rates (VRA) can be generated using various soil sampling techniques, such as point grid sampling, cell sampling, and management zone sampling. However, low-density grid sampling often fails to capture the spatial variability in soil properties, leading to inaccurate fertilizer recommendations. Sampling techniques by cells or management zones can generate maps of better quality and at lower costs than the sampling system by degree of points with low sampling density. Thus, this study aimed to compare the accuracy of different sampling techniques for mapping soil attributes in precision agriculture. For this purpose, the following sampling techniques were used: high-density point grid sampling method, low-density point grid sampling method, cell sampling method, management zone sampling method, and conventional method (considering the mean). Six areas located in the Brazilian states of Bahia, Minas Gerais, Mato Grosso, Goias, Mato Grosso do Sul, and Sao Paulo were used. The Root-Mean-Square-Error (RMSE) method was determined for each method using cross-validation. It was concluded that the cell method generated the lowest error, followed by the high-density point grid sampling method. Management zone sampling showed a lower error compared to the low-density point grid sampling method. By comparing different sampling techniques, we demonstrate that management zone and cell grid sampling can reduce soil sampling while maintaining comparable or superior accuracy in soil attribute mapping.
引用
收藏
页数:17
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