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Ridder ProDrain

Ridder ProDrain

Product catalog summary

Overview: The document discusses the Ridder ProDrain system, which is designed for precise irrigation and transpiration monitoring in controlled environment agriculture. It emphasizes the importance of accurate water management for crop health and productivity.

Key Features:

Control Based on Undersaturation Level: ProDrain allows irrigation based on the substrate's undersaturation level, ensuring precise water application tailored to crop needs.
Unique Transpiration Measurement: The system measures real-time transpiration rates, aiding in climate control strategies and serving as a research tool for model validation.
Growth Monitoring for Hanging Crops: ProDrain can measure crop growth by weighing plants, providing data on fruit load and growth rates.
Suitable for All Substrate-Grown Crops: The system is versatile, applicable to various crops like tomatoes, cucumbers, and roses.

Benefits:

24/7 Irrigation Scheduling: ProDrain provides continuous data for precise irrigation, even at night, enhancing water management.
Maximum CO2 Assimilation: By monitoring plant activity, ProDrain helps optimize photosynthesis and crop yields.
Tailored Water Management: The system prevents over or under-irrigation, reducing risks like root rot or stunted growth.

Technical Insights:

Real-Time Measurements: ProDrain measures irrigation water, drain water, and plant transpiration with high accuracy.
Data Utilization: The system provides management information for stress detection, growth monitoring, and production planning.

Research and Validation: The document includes findings from Wageningen University, emphasizing the system's accuracy and utility in research.

Case Study: Village Farms in Texas uses ProDrain for irrigation management and has integrated it into their GATES™ concept, highlighting its effectiveness in high radiation climates.

Introduction to ProDrain System: ProDrain monitors and manages plant growth by measuring plant weight and growth rates. It helps anticipate and prevent stress situations in plants by adjusting environmental controls based on past observations. The system provides insights into plant development by tracking absolute plant weight and cumulative fresh weight increase, allowing for production forecasting without manual counting.

Continuous Monitoring and Data Analysis: The system continuously weighs a specific area of crop plants and uses algorithms to filter out variations caused by harvesting or other activities. This results in accurate measurements of growth rate, cumulative fresh weight increase, and total weight increase per day. These metrics are crucial for yield forecasting and understanding plant development trends over time.

Field Experiences: Paul Selina from Village Farms shares his experience with ProDrain, highlighting its utility in adjusting watering, ventilation, and screening strategies based on growth data. The system provides insights into daily growth patterns, helping predict future production levels and optimize harvesting strategies.

Growth Patterns and Stress Indicators: ProDrain data reveals daily growth patterns, showing how plant activity fluctuates throughout the day. These patterns, visualized as waves, indicate plant stress levels and potential yield outcomes. Large wave amplitudes suggest stress, while more stable patterns are preferred for optimal growth.

Greenhouse Process Control and Transpiration Model: A study demonstrates the integration of intelligent algorithms in greenhouse process computers to optimize crop growth and save energy. A transpiration model was developed to predict crop transpiration based on climate measurements, with real-time comparisons to actual data. The model helps identify suboptimal crop performance and alerts growers to potential issues.

Implementation and Results: The transpiration model was tested in greenhouses in the Netherlands and Texas, showing close agreement between predicted and measured data. The study highlights the potential of model-based knowledge in improving greenhouse management and crop performance.

Conclusion: ProDrain and the transpiration model demonstrate the benefits of integrating advanced monitoring and predictive algorithms in greenhouse management. These systems provide valuable insights into plant growth, enabling growers to optimize conditions and improve yields.

System Architecture and Integration: The document describes a greenhouse control system architecture that includes a script controller, greenhouse process controller (MTA), Prodrain controller, and Synopta user interface. The script controller operates independently, ensuring that its failure does not affect the overall system. It imports input values such as radiation intensity, air temperature, and transpiration rate from the MultiMa process computer and connects with Ridder process computers' management software, Synopta. Data is stored every minute and accessible via company network or remote access.

Transpiration and Photosynthesis Prediction: The Leaf Area Index (LAI) is estimated from night transpiration and used alongside climate data to predict transpiration. Real-time comparisons between measured and predicted transpiration trigger warnings if discrepancies exceed a set threshold. Photosynthesis rates are predicted using stomatal conductance values, with real-time data available on the Synopta interface.

Model Validation and Implementation: The transpiration model was validated using historical data from a Dutch greenhouse, showing high correlation between predicted and measured transpiration rates. The model was implemented in greenhouses in The Netherlands and Texas, successfully predicting transpiration under varying climatic conditions. Differences in climate between locations were noted, with Texas having higher radiation and temperature.

Results and Discussion: The model accurately predicted transpiration across different conditions and cultivars, proving robust for general application. The system architecture allows for safe implementation of models without risking control continuity. The user-friendly interface facilitates the integration of custom software, enabling researchers and consultants to add applications. The document suggests potential for further applications based on energy, water, or CO2 balance models.

Figures and Data: Figures illustrate measured and predicted transpiration rates, highlighting instances of significant discrepancies due to factors like water availability. The document emphasizes the importance of real-time data comparison and storage for effective greenhouse management.

Conclusion: The integration of transpiration and photosynthesis models into greenhouse process computers represents a new generation of greenhouse control, allowing for the addition of various applications to enhance crop management.

Catalog excerpts

Accurate irrigation and transpiration monitoring ridder.com ridder.com Ridder ProDrain

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Make your crops thrive with precision irrigation Ridder ProDrain allows you to monitor the water uptake, transpiration level and growth rate of your crop plants. ProDrain Control based on undersaturation level Growth monitoring for hanging crops displays real-time information on irrigation, water uptake, transpiration, growth, the substrate’s saturation level and the Every grower knows that you should avoid a wet root If used for hanging crops (e.g. high-wire tomatoes or drain water volume 24 hours a day. It even displays this information when there is no solar irradiance (incoming sunlight)...

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Maximize production by placing your crop in control Monitor plant transpiration with ProDrain Commercial growers have always been taught that That’s why growers are extremely interested in the actual Measures plant transpiration maximum crop production depends on maintaining the water uptake and transpiration rate of their crop plants. ProDrain accurately measures plant transpiration: ideal greenhouse climate. This makes sense, of course, What not many growers know, however, is that it has been ♦Weight measurement of irrigation water, gutter weight and drain water ♦ and up to now, most growers...

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TranspirationPeter van Beveren vs. model measurement October 15, 2013 Peter van Beveren Radiation (W m−2 ) Transpiration (g m−2 h−1 ) Radiation (W m−2 tot (−) τ) Transpiration (g m−2 h−1 ) τtot (−) Wageningen University and Research Centre (WUR) findings Real-time symbolic view Real-time transpiration measurement Plant transpiration under normal and diffuse glass Plant transpiration under normal glass is much more irregular than under diffuse glass. This is shown clearly in the graphs below. 13-Apr-12 14-Apr-12 15-Apr-12 16-Apr-12 17-Apr-12 18-Apr-12 19-Apr-12 20-Apr-12 13-Apr-12 14-Apr-12 15-Apr-12...

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How does ProDrain work? ProDrain constantly measures the weight of the irrigation Fully automated irrigation based on water uptake Paul Selina water, the drain water, the substrate slab and the plants The desired water quantity in the substrate slabs can be (the last-named in the case of hanging crops). The system represented as the moisture content from 0-100%. The We’ve been using Ridder ProDrain since 2007. First keeps track of all fluctuations in weight. Since measurements problem is that irrigation is applied in volume (e.g. litres) at our GATES™ greenhouse and now all our Texas are performed...

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Measure to manage All growers aim to produce the best-quality product, in maximum quantities, at the right times and with as few resources as Experiences from the field possible. Tracking daily crop performance is the key to producing maximum yields. To monitor crop performance, ProDrain Paul Selina Village Farms has been working with ProDrain for The increase in plant weight is far from stable throughout determines the actual crop growth rate by measuring the increase in fresh weight. over seven years. He uses the plant weight and growth data the day. At night, water uptake and plant transpiration...

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Real-time comparison of measured and simulated crop transpiration in greenhouse process control A.N.M. de Koning and I. Tsafaras as for conditioning the greenhouse climate. With numerous rules (if …then) and mutual influences and associated settings, Applying more intelligent algorithms in the process computers that control the greenhouse climate and irrigation In modern greenhouses a process control computer takes care of the integrated control of installations for irrigation as well may help growers to optimize crop growth and yields as well as save energy. A greenhouse process computer has...

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Real-time comparison of measured and simulated crop transpiration in greenhouse process control Implementation in process control computers which was running through a separate controller in the process control system. The script controller was able to transfer data In the present study data were obtained from two commercial greenhouses; one located in Pijnacker (The Netherlands) and The programming language Python 3.3.5 was used to implement the described mathematical algorithms in a script file, the other in Texas (USA). The growers provided historical data for calibration and validation of...

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Real-time comparison of measured and simulated crop transpiration in greenhouse process control Results Validation of transpiration model The validation and the calibration of the transpiration model were carried out with historical data from April and May 2014, from greenhouse A in The Netherlands. Firstly, the model was calibrated for the characteristics of a tomato crop by adjusting a crop specific parameter in the model (Tsafaras and De Koning, in preparation). Then, the model was tested over a wide range of the climatic variables. During the simulated days the daily radiation sum varied...

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Real-time comparison of measured and simulated crop transpiration in greenhouse process control Without adjusting parameters the model predicted the transpiration of the tomato crop very well under different climatic conditions as well for different cultivars. Therefore the transpiration model seems robust for general application in tomato. Implemented in the greenhouse process computer at commercial nurseries, when a difference was noticed between predicted and measured transpiration, the computer warned the grower for unexpected behavior of his crop. Due to the architecture of the greenhouse...

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Ridder ProDrain

Ridder ProDrain

Catalog excerpts

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