Fruit producer advisory system using a connected fruit dendrometer, microclimate data, and machine learning algorithms

HEIG-VD is contributing its expertise and skills in intelligent data analysis and IoT solution design to an interdisciplinary project aimed at developing a decision support platform for precision agriculture.

Daily climate variations are unpredictable in the long term and have a direct impact on fruit growth and quality. The objective of this project, funded by Innosuisse, is to design, develop, and evaluate a decision support system to assist vegetable and fruit growers in maximizing crop quality and yield, as part of a sustainable development approach.

Today, commercial orchards are increasingly dependent on appropriate irrigation to ensure the best yields and optimize commercial quality. The most commonly used monitoring tools are based on soil moisture. A higher degree of accuracy can only be achieved by integrating indicators based directly on the plants, in particular monitoring their water stress and growth.

In greenhouses, tomato growers control the abiotic conditions that enable optimal crop management, but they are subject to external climatic factors that have a direct impact on their production, causing physiological disorders. These disorders can affect up to 30% of their yields and turnover.

Since November 1, 2021, researchers from Agroscope (the Swiss federal government's center of excellence for agricultural research) and HEIG-VD have been working with JDC Electronic SA to design a solution based on their new range of connected sensors, in particular a fruit dendrometer and an integrated climate measurement station, dedicated to agriculture. In this project, Agroscope is contributing its expertise to the development of an agricultural application that takes into account the needs and constraints of fruit and vegetable producers, as well as conducting field trials to collect fruit growth data that will be used to design and evaluate monitoring and advisory models. HEIG-VD will develop fruit growth models combining the expertise of agronomists and machine learning, as well as the IoT platform for collecting, storing, analyzing, and providing advice to optimize harvests by adjusting the management of orchards and greenhouses in terms of irrigation and climate in order to minimize the risk of physiological disorders and stress.