Our mobile data collection and yield prediction features for table grapes are now live in the Sensonomic app! Currently we support field sampling of Shoots and bunches before flowering (Phase 1) Bunches and berries from fruit set to veraison (Phase 2) We expect a plot-level prediction accuracy of 65% during Phase 1 67% during Phase 2 Exact accuracy will depend
Para español, haga clic aquí. Yield predictions from flowering Conducting a quick, visual assessment of olive flowering with Sensonomic’s mobile app can produce highly useful estimates of future yields. We have developed specialized algorithms to predict final harvest weight from flowering measurements with an accuracy of 81% down to plots of 50 ha. Predicting total harvest weight early in the
How technology can align incentives for producers, investors, and society Technology can only take you so far. Investors play a crucial role in making land assets more valuable over time. Land assets can provide both annual cash flow from agricultural production, and asset value increase over time. The asset typically increases in value due to limited supply, or through having
Producers can get a head start on planning for the harvest season by tracking how the extent and timing of flowering varies across their groves. In the Mediterranean region, flowering typically occurs between April and May.
Every spring olive producers carefully record the number of flowers on a sample of their trees with an important purpose in mind. The extent of flowering can be an early and strong predictor of the weight of olives at harvest in autumn with an accuracy of 60-75%.
How would you assess a business idea involving complex supply chains, and ensure the best decisions for the business’ early stage growth phase? Leveraging our knack for multimethodology, Sensonomic recently provided clients with essential resource mapping and supplier market information. This helped establish robust and evidence based operations. Found in everything from chocolate to hair treatment, the shea fruit
Agriculture is vital to feeding the world’s population but its environmental cost is massive, occupying 70% of ice-free land and driving deforestation. Recent proliferation of agricultural data presents an exciting opportunity to apply advanced analytics to improve efficiency and reduce impact. In this video I talk about my DPhil research at the University of Oxford on computational simulation to help
Adam Formica, our Senior Modeller, has just returned from three weeks spent in Fiji. He spoke with a wide range of stakeholders to better understand their agricultural system. He has returned with a sense of appreciation for the wonderfully welcoming and helpful people of Fiji, pages and pages of notes, and some brilliant data. This research is to lay the
Adam Formica, our Senior Modeller, has just returned from 3 weeks spent in Fiji. He spoke with a wide range of stakeholders to better understand their agricultural system. He has returned with a sense of appreciation for the wonderfully welcoming and helpful people of Fiji, pages and pages of notes, and some brilliant data. This research is to lay the
Can you imagine needing to relocate your whole village to escape the sea? Your crops failing due to unpredictable rains, or the salt rising up into their roots? Can you imagine being daily, existentially affected by the already apparent impacts of climate change? This is the reality for many living on the low-lying tropical island nations of Fiji, Vanuatu and