Evaluation of suitable base spray rate estimation methods for precision chemical applications in vineyards with different training systems

Authors: SAHNI, R - Washington State University; SCHRADER, M - Washington State University; RATHNAYAKE, A - Washington State University; KHOT, L - Washington State University; HOHEISEL, G - Washington State University; Zhu, Heping

Submitted to: American Journal of Enology and Viticulture
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/10/2024
Publication Date: 4/20/2024
Citation: Sahni, R., Schrader, M.J., Rathnayake, A., Khot, L., Hoheisel, G., Zhu, H. 2024. Evaluation of suitable base spray rate estimation methods for precision chemical applications in vineyards with different training systems. American Journal of Enology and Viticulture. 75(1). Article 0750009. https://doi.org/10.53444/ajev.2024.22064.
DOI: https://doi.org/10.53444/ajev.2024.22064

Interpretive Summary: Grape growers are adopting the intelligent spray technology to increase pesticide application efficiency. This technology automatically controls spray outputs to match the individual plant foliage volume. The base spray rate, the amount of sprays to cover a unit of foliage volume, is a critical parameter for intelligent sprayers to achieve desired amounts of sprays for best pest management. In this research, methods of tree row volume, leaf wall area and unit canopy row were compared for determining the optimal base spray rates for the intelligent sprayers used in two modern vineyards. The modified vertical shoot position trained wine grape and high cordon trained juice grape architectures were the two vineyards. Spray deposition and coverage were accessed for the comparisons. For the modified vertical shoot position grape architecture, the base spray rates estimated with the three methods were similar. However, for the high cordon trained juice grape architecture, the tree row volume method provided better spray performance than other two methods. Thus, the tree row volume method was recommended for integration with the intelligent spray system to automatically adjust base spray rates based on the canopy attributes. This recommendation would greatly simplify the system operation with enhanced grower adaptability.

Technical Abstract: Retrofit intelligent spray systems have been developed for precision agrochemical applications in perennial specialty crops. In such systems, although a 2D LiDAR estimated canopy density factor is used for individual nozzle actuation, the base spray rate (amount of spray liquid to treat unit canopy volume, L m-3) input critically governs the amount of spray mix delivered to the target. This rate is often decided by qualitative canopy characteristics and can be subjective. This study was conducted to evaluate the suitability of three base spray rate estimation methods and resulting spray coverage as well as deposition in modified vertical shoot position (MVSP) trained wine grape and high cordon (HC) trained juice grape architectures. Canopy parameters at full canopy growth stage were measured to estimate Tree Row Volume (TRV), Unit Canopy Row (UCR), and Leaf Wall Area (LWA) attributes. These canopy attributes aided in deriving base spray rates as 0.12, 0.30, and 0.14 L m-3 for MVSP and 0.13, 0.30, and 0.11 L m-3 for HC architecture grapevines, respectively. Field trials were then conducted to test suitability of these rates for precision applications by an airblast sprayer equipped with an intelligent spray retrofit kit. The grower-adapted application rate of 702 L ha-1 was used as a control. Overall, TRV method estimated base spray rate and resulting spray applications had comparable spray coverage and deposition compared to control. As TRV can be estimated with ease by grower, pertinent base spray rate estimation approach would ideally help to realized precision chemical applications in both MVSP and HC trained grapevines.