Forecasting Plant Growth with PhytoVision; Case Study
Published On: April 6th, 2021
Crop growth forecasting is crucial when evaluating the profitability of each crop, and investment. You need to know how much you can produce in order to know how much you can sell. Your customers also need to know how much you can guarantee before doing big business together. Luckily, Paskal has it down to a science, and all the tools you need to get the results you want.
In this case study, Mikhail Vorobyev outlines how PhytoVision is one of the investments that farmers are making to increase their profits and commercial client base. From Israel to Russia and all over the world, this is one of the most innovative technologies for achieving an accurate and precise plant growth measurement and data.
We can see from the data and results of this case study that Vorobyev’s research with clients using PhytoVision directly supports this claim. In Venlo style greenhouses, the unforgiving climate of the Motherland is only a small factor for modern farmers.
See why more modern day greenhouse growers are implementing Paskal’s PhytoVision, regardless of climate and geographical location. Hear first hand from the experts in the field why working with this technology is so important to the food businesses in providing quality products.
Forecasting Growth with PhytoVision
By Mikhail Vorobyev, Paskal RUS Agronomist Consultant, Ph.D. in Agricultural Sciences
The issue of planning the yield of vegetable crops is very relevant today. Large manufacturers in Russia are in close contact with trading houses, wholesale, and logistics centers. On the one hand, this simplifies the process of selling products, but on the other hand, imposes greater responsibility on the manufacturer. It is important not only to obtain production, but also to accurately monitor the growth throughout the entire growing period. Specialists of modern greenhouse complexes are forced to make a forecast for fees for the year, month, week and even next day. In forecasting, they may rely on information from hybrid seed producers, or their own personal experience. However, this is not enough for an accurate forecast.
Seizing the Opportunity
The PhytoVision Plant Growth Monitoring System was created primarily to help the technician monitor the effects of various microclimate parameters in real time, as well as external factors, dietary patterns, etc. and the main criterion is growth. By a happy coincidence, when we started offering the PhytoVision system in Russia in 2017, among other features, the growth forecasting function was mentioned. Therefore, soon, when the first buyers appeared, we had to solve this issue.
Solving the Issue
This research was carried out together with our client in a complex of modern Venlo greenhouse structures with a total area of 30 hectares in Russia. Together with Paskal and the grower, we monitored the dependence of plant weight (data from PhytoVision sensors) and harvested data (information from system users) daily for several months. As an object of observation, a hybrid of a medium-fruited cucumber, “Meva” (selection of Rijk Zwaan), which has good stable growth, was chosen.
Measuring the Factors
As a result of our observations, we found out that the dependence between the weight of the whole plant and the weight of the fruits that we collect from the plant is linear. The next step is to determine the percentage of the weight of the fruit on the plant relative to the weight of the entire plant. With different cultivation technologies, on average, it is recommended to keep about 12 fruits on one adult Meva cucumber plant. In this case, the picking of the cucumber was carried out daily, one fruit was harvested. Thus, we could determine the average weight of the fruit that was removed from each plant.
Average weight of 1 fruit = total harvest / number of plants
Doing the Math
Knowing the average weight of the fruit, we can calculate the percentage (coefficient) of the weight of the harvested fruit from the total weight of the plant. Thanks to the PhytoVision plant growth monitoring system, we receive all the necessary information about changes in plant growth. For a more accurate calculation for predicting the yield for the next day, we took data on growth changes for the previous 7 days. This allows you to analyze changes in the dynamics of plant and fruit growth, because within a week, factors could have occurred that could adversely affect the growth of the plant and the fruits themselves. In other words, the more stable the plant growth, the more accurate the forecast. Using this technique, we were able to plan the harvest for the next day with an accuracy of 1-2%.
Chart 1. Stable growth – accurate forecast
Chart 2. Unstable growth – imprecise forecast
Down to a Science
The next step is to forecast the next week. For this, we calculated the arithmetic mean of plant growth for the previous week. Then, using the obtained coefficient of weight of fruits from the weight of the plants, a prediction was made. We would like to once again draw your attention to the fact that the more stable plant growth was in the previous and current weeks, the more accurate the forecast was.
Conclusions and Takeaways
In Russia, even in modern greenhouse complexes, using modern equipment, it is far from always possible to maintain an optimal microclimate. There are other reasons that can greatly affect the growth and productivity of plants. Under these conditions, agronomists consider the forecast for the next week to be normal with an error of 10%. Thanks to the use of the Paskal plant growth monitoring system, we were able to forecast the next week in the range of 2-5% accuracy.