About C-Crop Technology
C-Crop technology revolutionizes vineyard management by empowering farmers with precise monitoring capabilities. Our innovative platform offers detailed insights into vineyard yield and quality through precise measurements, accessible anytime and anywhere from smartphone devices
Few simple steps to measure your vineyards yield
2. Utilize the app's video recording feature to capture short videos of your vineyard. Ensure that you evenly spread the samples throughout the vineyard.
3. Once you have an internet connection, all videos will be automatically uploaded to C-Crop cloud.
4. After the processing is complete, which occurs rapidly and depends on your internet connection, you will receive a user-friendly report directly on the C-Crop app.
C-Crop Value for You
2. Sub-Plot Level Yield Data: Access detailed yield and yield components data at the sub-plot level, empowering you to make informed and right decisions.
3. Identify Performance Gaps: Identify and address any performance gaps in your vines to ensure optimal growth and productivity.
4. Efficient Resource Management: Effectively manage your resources, manpower, and inputs by leveraging C-Crop's comprehensive data.
Use Case: Accurate Table Grape Yield Estimation
Objective: To accurately estimate the yield of a table grape vineyard plot spanning 4.0 hectares in South Africa.
* 320 video samples were taken in the vineyard, with an average of 80 videos per hectare.
* These video samples were analyzed to estimate overall yield, as well as yield components including clusters density, clusters size, berries number and size per cluster.
Analysis and Yield Estimation:
* The video samples were analyzed using C-Crop’s platform to estimate the overall yield of the vineyard.
* Yield components, including clusters density, clusters size, and berries number and size per cluster, were also analyzed.
* The estimated yield was then compared to the actual yield, which was determined by weighing the harvested fruit in the packing house.
* The C-Crop platform achieved a high accuracy rate of more than 92% in predicting the yield of the vineyard.
* In addition to yield estimation, the platform identified the variability of yield within the vineyard plot.
* Through statistical analysis, two distinct sub-plots were identified, exhibiting a 60% difference in yield between the highest (blue) and lowest (red) sub-plots.
* Further investigation conducted by the grower team revealed that the difference in yield was attributed to the varying operation of two irrigation systems.