Hello everyone! I’m Shohei.
Plant factories are attracting attention as the next generation of agriculture, which allows stable production regardless of the weather. However, it requires management methods and know-how that are different from traditional agriculture. Data analysis is particularly important.
At the plant factory, various environmental factors such as temperature, humidity, light intensity, CO2 concentration, and nutrient solution composition can be precisely controlled. This huge amount of data is truly a treasure trove.
Through proper analysis, you can obtain various benefits that will lead to the success of your plant factory, such as increasing yield, improving quality, and reducing costs.
In this article, we will explain the importance of data analysis in plant factories in an easy-to-understand manner, even for beginners.
What exactly is a plant factory? If so, please refer to the following articles.
Why is data analysis important? The key to realizing crop management that does not rely on experience and intuition
In conventional agriculture, crop management was generally performed based on many years of experience and intuition.
However, in a closed environment such as a plant factory, even the slightest environmental change can have a major impact on crop growth. Therefore, it may be difficult to ensure stable yields if management relies only on experience and intuition.
What is important here is logical crop management based on data. At the plant factory, we can quantify environmental data and growth conditions using various sensors. By analyzing this data, you can:
- Identify factors influencing Yield
- Elucidating the optimal growth environment
- Early detection of signs of disease and poor growth
Data analysis enables more accurate crop management, which not only leads to higher yields, improved quality, and reduced costs, but also has the benefit of building a stable supply system.
Basic knowledge of data analysis: What data should be recorded?
There is a wide variety of data that should be recorded at a plant factory, but it can be broadly divided into the following three types.
- Environmental data: temperature, humidity, light intensity, CO2 concentration, water temperature, EC, pH, etc.
- Cultivation data: variety, sowing date, harvesting date, yield, number of defective seedlings, etc.
- Equipment data: lighting hours, air conditioning temperature settings, Nutrient solution design, etc.
When recording this data, please note the following points:When recording this data, please note the following points:
- Accuracy: Calibrate sensors regularly to obtain accurate data
- Completeness: Record all necessary data without omission
- Continuity: Accumulating data over a long period of time
In some cases, a dedicated system is introduced to record data, but there is also a method of using spreadsheet software.
The important thing is to record it in a way that is easy for you to see and manage.
However, obtaining accurate and large amounts of data may require mechanization and automation of the production process. This point is also explained in the article below.
Data analysis procedure: Data utilization techniques that lead to increased yield
Data analysis is performed using the following steps.
- Objective setting: Set a specific objective for what you want to clarify (e.g. increase yield, reduce costs)
- Data collection: Collect the necessary data according to the purpose
- Data visualization: Visually represent data in an easy-to-understand manner using graphs, tables, etc.
- Analysis/Consideration: Find relationships between data, formulate and verify hypotheses
- Implementation of improvement measures: Improve the cultivation environment and management methods based on the analysis results
- Effectiveness verification: Verify the effectiveness of improvement measures and re-analyze if necessary.
Data analysis doesn’t just happen once. It is important to continually collect and analyze data and make repeated improvements.
How to improve yield through data analysis
Data analysis is an essential skill for improving plant factories, but it also requires the knowledge and know-how of managers.
For example, the percentage of trimming garbage.
Don’t just look at it and think, “There’s a lot of trash.” You can find out various things with just one piece of Trimming garbage data, as shown below.
- Garbage generation status
- Quality of work that day
- Inadequacy of cultivation process
- Dense planting degree
Whether or not you know these things will make a big difference in how you can improve your shots.
Plant factories that are producing results have a deep understanding of the knowledge that leads to profitability and utilize their unique know-how.
This site provides know-how specialized in “profitability”. If you are interested, please check the content below.
Summary: Data analysis serves as a compass for plant factory management
Data analysis in plant factories is essential for increasing yield, improving quality, reducing costs, and achieving stable supply.
Data analysis may sound difficult, but no special knowledge or skills are required. First, let’s start with daily records.
Plant factories demonstrate their true value through scientific management based on data. Let’s actively utilize data analysis and create the future of the plant factory!
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