Application of Remote Sensing Techniques to Discriminate the Effect of Different Soil Management Treatments over Rainfed Vineyards in Chianti Terroir
The work aimed to discriminate among different soil management treatments in terms of beneficial effects by high-resolution thermal and spectral vegetation imagery using an unmanned aerial vehicle and open-source GIS software. Five soil management treatments were applied in two organic vineyards (cv...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-02-01
|
| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/13/4/716 |
| _version_ | 1797396425900818432 |
|---|---|
| author | Àngela Puig-Sirera Daniele Antichi Dylan Warren Raffa Giovanni Rallo |
| author_facet | Àngela Puig-Sirera Daniele Antichi Dylan Warren Raffa Giovanni Rallo |
| author_sort | Àngela Puig-Sirera |
| collection | DOAJ |
| description | The work aimed to discriminate among different soil management treatments in terms of beneficial effects by high-resolution thermal and spectral vegetation imagery using an unmanned aerial vehicle and open-source GIS software. Five soil management treatments were applied in two organic vineyards (cv. Sangiovese) from Chianti Classico terroir (Tuscany, Italy) during two experimental years. The treatments tested consisted of conventional tillage, spontaneous vegetation, pigeon bean (<i>Vicia faba</i> var. minor Beck) incorporated in spring, mixture of barley (<i>Hordeum vulgare</i> L.) and clover (<i>Trifolium squarrosum</i> L.) incorporated or left as dead mulch in late spring. The images acquired remotely were analyzed through map-algebra and map-statistics in QGIS and correlated with field ecophysiological measurements. The surface temperature, crop water stress index (CWSI) and normalized difference vegetation index (NDVI) of each vine row under treatments were compared based on frequency distribution functions and statistics descriptors of position. The spectral vegetation and thermal-based indices were significantly correlated with the respective leaf area index (R<sup>2</sup> = 0.89) and stem water potential measurements (R<sup>2</sup> = 0.59), and thus are an expression of the crop vigor and water status. The gravel and active limestone soil components determined the spatial variability of vine biophysical (e.g., canopy vigor) and physiological characteristics (e.g., vine chlorophyll content) in both farms. The vine canopy surface temperature, and CWSI were lower on the spontaneous and pigeon bean treatments in both farms, thus evidencing less physiological stress on the vine rows derived from the cover crop residual effect. In conclusion, the proposed methodology showed the capacity to discriminate across soil management practices and map the spatial variability within vineyards. The methodology could serve as a simple and non-invasive tool for precision soil management in rainfed vineyards to guide producers on using the most efficient and profitable practice. |
| first_indexed | 2024-03-09T00:51:07Z |
| format | Article |
| id | doaj.art-fd2edfa8bb4445968aa48e98809a3287 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-09T00:51:07Z |
| publishDate | 2021-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-fd2edfa8bb4445968aa48e98809a32872023-12-11T17:14:51ZengMDPI AGRemote Sensing2072-42922021-02-0113471610.3390/rs13040716Application of Remote Sensing Techniques to Discriminate the Effect of Different Soil Management Treatments over Rainfed Vineyards in Chianti TerroirÀngela Puig-Sirera0Daniele Antichi1Dylan Warren Raffa2Giovanni Rallo3Department of Agriculture, Food and Environment (DAFE), University of Pisa, 80, 56124 Pisa, ItalyDepartment of Agriculture, Food and Environment (DAFE), University of Pisa, 80, 56124 Pisa, ItalyInstitute of Life Sciences, Group of Agroecology, Scuola Superiore Sant’Anna, 56127 Pisa, ItalyDepartment of Agriculture, Food and Environment (DAFE), University of Pisa, 80, 56124 Pisa, ItalyThe work aimed to discriminate among different soil management treatments in terms of beneficial effects by high-resolution thermal and spectral vegetation imagery using an unmanned aerial vehicle and open-source GIS software. Five soil management treatments were applied in two organic vineyards (cv. Sangiovese) from Chianti Classico terroir (Tuscany, Italy) during two experimental years. The treatments tested consisted of conventional tillage, spontaneous vegetation, pigeon bean (<i>Vicia faba</i> var. minor Beck) incorporated in spring, mixture of barley (<i>Hordeum vulgare</i> L.) and clover (<i>Trifolium squarrosum</i> L.) incorporated or left as dead mulch in late spring. The images acquired remotely were analyzed through map-algebra and map-statistics in QGIS and correlated with field ecophysiological measurements. The surface temperature, crop water stress index (CWSI) and normalized difference vegetation index (NDVI) of each vine row under treatments were compared based on frequency distribution functions and statistics descriptors of position. The spectral vegetation and thermal-based indices were significantly correlated with the respective leaf area index (R<sup>2</sup> = 0.89) and stem water potential measurements (R<sup>2</sup> = 0.59), and thus are an expression of the crop vigor and water status. The gravel and active limestone soil components determined the spatial variability of vine biophysical (e.g., canopy vigor) and physiological characteristics (e.g., vine chlorophyll content) in both farms. The vine canopy surface temperature, and CWSI were lower on the spontaneous and pigeon bean treatments in both farms, thus evidencing less physiological stress on the vine rows derived from the cover crop residual effect. In conclusion, the proposed methodology showed the capacity to discriminate across soil management practices and map the spatial variability within vineyards. The methodology could serve as a simple and non-invasive tool for precision soil management in rainfed vineyards to guide producers on using the most efficient and profitable practice.https://www.mdpi.com/2072-4292/13/4/716cover cropscrop water stress index (CWSI)spectral vegetation indexsustainable agriculture |
| spellingShingle | Àngela Puig-Sirera Daniele Antichi Dylan Warren Raffa Giovanni Rallo Application of Remote Sensing Techniques to Discriminate the Effect of Different Soil Management Treatments over Rainfed Vineyards in Chianti Terroir Remote Sensing cover crops crop water stress index (CWSI) spectral vegetation index sustainable agriculture |
| title | Application of Remote Sensing Techniques to Discriminate the Effect of Different Soil Management Treatments over Rainfed Vineyards in Chianti Terroir |
| title_full | Application of Remote Sensing Techniques to Discriminate the Effect of Different Soil Management Treatments over Rainfed Vineyards in Chianti Terroir |
| title_fullStr | Application of Remote Sensing Techniques to Discriminate the Effect of Different Soil Management Treatments over Rainfed Vineyards in Chianti Terroir |
| title_full_unstemmed | Application of Remote Sensing Techniques to Discriminate the Effect of Different Soil Management Treatments over Rainfed Vineyards in Chianti Terroir |
| title_short | Application of Remote Sensing Techniques to Discriminate the Effect of Different Soil Management Treatments over Rainfed Vineyards in Chianti Terroir |
| title_sort | application of remote sensing techniques to discriminate the effect of different soil management treatments over rainfed vineyards in chianti terroir |
| topic | cover crops crop water stress index (CWSI) spectral vegetation index sustainable agriculture |
| url | https://www.mdpi.com/2072-4292/13/4/716 |
| work_keys_str_mv | AT angelapuigsirera applicationofremotesensingtechniquestodiscriminatetheeffectofdifferentsoilmanagementtreatmentsoverrainfedvineyardsinchiantiterroir AT danieleantichi applicationofremotesensingtechniquestodiscriminatetheeffectofdifferentsoilmanagementtreatmentsoverrainfedvineyardsinchiantiterroir AT dylanwarrenraffa applicationofremotesensingtechniquestodiscriminatetheeffectofdifferentsoilmanagementtreatmentsoverrainfedvineyardsinchiantiterroir AT giovannirallo applicationofremotesensingtechniquestodiscriminatetheeffectofdifferentsoilmanagementtreatmentsoverrainfedvineyardsinchiantiterroir |