Croptimal performs real time immediate tests and analysis in the field for crops, soil and water, replacing traditional complicated methods that are typically undertaken at distant laboratories and normally require days to weeks for results. The data collected by Croptimal is accumulated in a Cloud-based database that will provide “big-data” for intelligent recommendations and data mining trends.
Doron Reinis, Chief Operating Officer of Eurocontrol, stated, “The Croptimal service being provided to Kibbutz Sha’ar HaAmakim is expected to increase yields, reduce expenses and boost the revenue of the kibbutz. The almond is a species of tree native to the Middle East, the Indian subcontinent and North Africa. World production of almonds is over 3 million tons per year and with growing demand. This project for kibbutz Sha’ar HaAmakim will serve as a case study enhancing the Croptimal platform as a beneficial solution to this specific market.”
Bruce Rowlands, Chairman and Chief Executive Officer, added ”We are very pleased that our Croptimal technology and service has been embraced so quickly proving that our model of 'taking the laboratory to the field' to provide actionable results is the way of the future. Croptimal’s technology and service can be applied to virtually any crop and our team in Israel is currently working on tomatoes, potatoes and corn with interest expressed on numerous other crops including marijuana.”
Croptimal is a private Israeli company formed in early 2017 and is 100% owned by Eurocontrol. Croptimal’s service was developed following the need and demand of farmers and agronomists to increase crop yields, both quality and quantity to meet the rapidly increasing world population. Croptimal offers a suite of in-field decision support tools to agronomists and farmers based on an innovative system of big database analysis (machine learning) utilizing unique hardware and software that enables continuous measurement of nutrients in soil, water and plant tissue. Croptimal’s technology offers a comprehensive and accurate service that encompasses a full range of in-field measurement activities, including collecting and automatically preparing samples and inputting them to the measurement systems, collecting environmental data using real-time systems installed in the field, conducting the measurements and transferring the measurement results to the farmer and ultimately providing fertilizer recommendations to the farmer or accompanying agronomist. Croptimal’s unique technology measures N, P, K in their available forms as well as other micro and macro elements. The in-field nutrients measurement technology reduces time of measurement from a 10 to 14 day cycle with traditional laboratories to a full cycle of 10 minutes. The measurement data, based on the unique hybrid technologies developed by Croptimal, is fed into an expansive database with unique ID, time and location signature which in addition to the measurement data of nutrients, also collects key environmental data (temperature, UV radiation, humidity, etc.) based on time and location regularly streamed to Croptimal’s Cloud database. Croptimal has developed unique machine learning algorithms that performs correlation analysis between environmental events (temperature, UV radiation, humidity, etc.) and the measurement data of nutrients combined with fertilization recommendations from expert agronomists to correlate it with the yield results allowing Croptimal to create Dynamic Growth Protocols to enable accurate fertilization recommendations based on the past event and to the extent known, a future event (for example; weather forecast). Efficient and timely fertilization recommendations are enabled by the precise and fast measurement methods and enhanced by the real time feedback from the analysis algorithm of the Cloud big-data base. Due to the efficiency of Croptimal’s decision support tools and the Dynamic Growth Protocol it is possible for Croptimal to supply a more qualified and comprehensive service at a price that is lower than farmers are currently paying while enabling continuous improvement of yield and the ability to measure it over time.