4.7 Article

Assessing the Contribution of ECa and NDVI in the Delineation of Management Zones in a Vineyard

期刊

AGRONOMY-BASEL
卷 12, 期 6, 页码 -

出版社

MDPI
DOI: 10.3390/agronomy12061331

关键词

vineyard; precision viticulture; management zones; within-field variability; ECa; NDVI

资金

  1. Transition towards a more carbon and nutrient efficient agriculture in Europe - European Union [H2020-SFS-30-2017, 773682]
  2. FCT-Fundacao para a Ciencia e a Tecnologia, I.P., in the scope of the project Linking Landscape, Environment, Agriculture and Food Research Centre [UIDB/04129/2020, UIDP/04129/2020]

向作者/读者索取更多资源

Precision fertilization using remotely sensed data, specifically soil electrical conductivity (ECa) and normalized difference vegetation index (NDVI), provides a cost-effective solution to identify soil fertility variability. Combining these two indicators allows for the delineation of different management zones and the discovery of soil fertility differences and ionic imbalances for targeted fertilization and soil management.
Precision fertilization implies the need to identify the variability of soil fertility, which is costly and time-consuming. Remotely measured data can be a solution. Using this strategy, a study was conducted, in a vineyard, to delineate different management zones using two indicators: apparent soil electrical conductivity (ECa) and normalized difference vegetation index (NDVI). To understand the contribution of each indicator, three scenarios were used for zone definition: (1) using only NDVI, (2) only ECa, or (3) using a combination of the two. Then the differences in soil fertility between these zones were assessed using simple statistical methods. The results indicate that the most beneficial strategy is the combined use of the two indicators, as it allowed the definition of three distinct zones regarding important soil variables and crop nutrients, such as soil total nitrogen, Mg2+ cation, exchange acidity, and effective cation exchange capacity, and some relevant cation ratios. This strategy also allowed the identification of an ionic unbalance in the soil chemistry, due to an excess of Mg2+, that was harming crop health, as reported by NDVI. This also impacted ECa and NDVI relationship, which was negative in this study. Overall, the results demonstrate the advantages of using remotely sensed data, mainly more than one type of sensing data, and suggest a high potential for differential crop fertilization and soil management in the study area.

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