Proximal sensing of vineyard soil and canopy vegetation for determining vineyard spatial variability in plant physiology and berry chemistry

Abstract

Proximal sensing is used in vineyards to precisely monitor and manage spatial and temporal variability while reducing laborious and repetitive measurements. Soil electrical conductivity (EC) and canopy vegetation indexes are two frequently assessed variables with off-the-shelf sensors. In this study, the ecophysiological variability of a commercial vineyard comprising three varieties in three blocks, Cabernet-Sauvignon (CS), Cabernet franc (CF), and Petit Verdot (PV), was investigated. Random sampling was used to continuously assess spatial variability in plant physiology and berry composition. Soil EC and NDVI were also continuously monitored throughout the season. There was a noticeable spatial pattern in the normalised differential vegetation index (NDVI) in the vineyard and soil EC. The spatial pattern of NDVI can be partially elucidated by the season-long stem water potential (Ψstem), which was lowest in the CS block. However, leaf photosynthesis did not match this spatial pattern. The spatial distribution of NDVI and soil EC did not satisfactorily explain the spatial variations in yield components and berry chemistry. Principal component analyses (PCA) were performed resulting in a clear discrimination of each of the three cultivars. Soil EC showed a significant relationship with Ψstem integrals, total skin anthocyanins and tri- to di-hydroxylated flavonoids. In each cultivar block, soil EC showed some capability to be related to plant water status, and NDVI showed a relationship with yield. Overall, this study provided evidence of the spatial variability of grapevine physiology in a commercial vineyard with three cultivars. Also, it showed that the cultivar effect and uniform crop level management can diminish the efficiency of proximal sensing, thus weakening the relationship of soil and canopy indexes with plant physiology and berry chemistry. Nonetheless, our study showed that it is possible to apply temporal proximal sensing methods when assessing plant water status, primary metabolism, yield and berry secondary metabolism, which give an indication of the possibility of managing the spatial variability of both plant physiology and berry chemistry.

Use of Active Sensors in Coffee Cultivation for Monitoring Crop Yield

“…It is evident that AOS sensors have great potential to be explored in coffee farming; the present study sought to provide an initial approach regarding the potential of using such sensors for PA management. Future studies may address the use of sensors in other scenarios (e.g., crops with different row orientations, mountain coffee, shaded coffee), as well as exploiting this information to create management strategies that optimize the management of inputs, as was done for annual crops [3,13,19,21]. The spatio-temporal evaluation of coffee yield also showed that, in a single field, there may exist coffee plants with inverted bienniality (Figures 7 and 8).…”

“…Unlike annual crops, active optical sensing for coffee should be performed with equipment turned to the side view of the plants, since positioning the sensor at the top of the plant is unfeasible due to the canopy height. Although the lateral positioning of active sensors was already adopted in some studies monitoring perennial crops [19][20][21], there is still a need to establish an optimized protocol for the acquisition and processing of these data for coffee crops in order to evaluate its spatial variability over its biennial cycle. For example, in crops with planting lines oriented in an east-west direction, there is no consensus on using data from only one of the side faces (i.e., using only the face that does not receive direct sunlight) or whether the best strategy is to use a methodology to calculate the average of both faces.…”

Adapting the Priestly-Taylor Index as a Physiological Stress Indicator in Vineyard Agrosystems

“…Leeuwen et al, 2010;Yu et al, 2021a). This method takes advantage of13 C discrimination in C 3 plants:…”

Orbital, aerial, and proximal sensing applied to monitoring the spatial variability of coffee plantations

“…It is evident that AOS sensors have a great potential to be explored in coffee farming, and that the present study sought to provide an initial approach regarding the potential of using these sensors for PA management. Future studies may address the use in other scenarios (e.g., crops with different row orientation, mountain coffee, shaded coffee), as well as exploiting this information to create management strategies that optimize the management of inputs, as has been done for annual crops TREVISAN et al, 2018;PALLOTTINO et al, 2019;YU et al, 2021).…”

“…Unlike annual crops, AOS sensing for coffee should be performed with equipment turned to the side view of the plants since positioning the sensor at the top of the plant is unfeasible due to the height of the canopy. Although the lateral positioning of active sensors has already been adopted in some studies that monitored perennial crops DARRA et al, 2021;YU et al, 2021), there is still a need to establish an optimized protocol for the acquisition and processing of these data for coffee crop in order to evaluate its spatial variability over its biennial cycle. For example, in crops with planting lines oriented in an east-west direction, there is no consensus on using data from only one of the side faces (e.g., using only the face that does not receive direct sunlight) or if the best strategy is to use a methodology to calculate the average of both faces.…”