EP-4734752-A1 - METHOD FOR CONTROLLING THE PLANT GROWTH DURING A PLANT DAY

Abstract

1) Method for controlling the plant growth at an indoor cultivation area, wherein the method comprising the following steps: A Provision of data about the changes of at least three parameters, that change over the course of 24 hours day cycle at an outdoor cultivation of plants, wherein said parameters related to: i) a first parameter related to light ii) a second parameter related to nutrients iii) a third parameter related to the atmosphere and/or humidity B controlling of the conditions of the plant growth such that B1 a change of at least two of the parameters wherein the third param- eter remains constant and/or B2 a change of only the second parameter whereas the first parameter remains constant to less than 40% of the average value for a maximum of said first parameter over the sequence of a day, and wherein said change over sequence of a day in step B1 or step B2 is con- trolled with the data of step A.

Inventors

• CIRILLO, FABIO
• RUTZ, Benjamin

Assignees

• Cirillo, Fabio
• Rutz, Benjamin

Dates

Publication Date

20260506

Application Date

20240614

Claims (1)

1. Claims 1 ) Method for controlling the plant growth at an indoor cultivation area, wherein the method is characterized by the following steps: A Provision of data about the changes of at least three parameters, that change over the course of 24 hours day cycle at an outdoor cultivation of plants, wherein said parameters related to: i) a first parameter related to light ii) a second parameter related to nutrients iii) a third parameter related to the atmosphere and/or humidity B controlling of the conditions of the plant growth such that there is B1 a change of at least two of the parameters wherein the third parameter remains constant and/or B2 a change of only the second parameter whereas the first parameter remains constant to less than 40% of the average value for a maximum of said first parameter over the sequence of a day, and wherein said changes of said one or more parameters over sequence of a day in step B1 or step B2 are controlled on the basis of the data of step A. 2) Method according to claim 1 , characterized in that in step A said data about the changes of said at least three parameters is provided with at least four periods of time, which represent the change of the first, second and third parameter at night time, sunrise, day time and sunset which is the sequence of a day. 3) Method according to claim 2, characterized in that said night time, sunrise, day time and sunset correspond with the global average amount of time of each period over a time of 24h at an outdoor cultivation area, wherein the repetition of the sequence of said periods, representing a plant day, is at least one hour more or less than 24h. 4) Method according to claim 1 or 2, characterized in that the repetition of the sequence of night time, sunrise, day time and sunset of the method is less than 20 h. 5) Method according to claim 2, characterized in that during night time or day time the first parameter remains constant and that during sunrise or sunset said first parameter change. 6) Method according to claim 2, characterized in that the first parameter remains at less than 5%, preferably less than 2%, of the average value for the maximum of said first value. 7) Method according to one of the preceding claims, characterized in that said first parameter is the light intensity and/or the change of the spectrum of light. 8) Method according to one of the preceding claims, characterized in that said second parameter is the concentration of nutrition in aqueous solution and/or nutrient intake of the plant that change over the sequence of a day. 9) Method according to one of the preceding claims, characterized in that said third parameter is the average amount of wind, Temperature change, CO2-Con- centration, O2-Concentration, air humidity and/or soil humidity over the sequence of a day. 10)Method according to one of the preceding claims, characterized in that allowing the day/night cycle simulation being able to be extended by preparatory, harvest and/or post-harvest segments. 11 )Method according to one of the preceding claims, characterized in that said data in step A are provided by a determination of the outdoor cultivation of plants at different outdoor growing areas at different location and/or at different seasons of the year. 12)Method according to one of the preceding claims, characterized in that step B can be further controlled by measurement, preferably optical measurement, of the plant growth and data analysis by means of statistical and non-statistical procedures using data of said measurement. 13)Method according to one of the preceding claims, characterized in that in step B the third parameter remain constant over the sequence of a day. 14)Programmable system (1 ) for the performance of a method according to one of the preceding claims.

Description

METHOD FOR CONTROLLING THE PLANT GROWTH DURING A PLANT DAY The current invention relates to a method for controlling the plant growth of a plant during a plant day. A plant has no specific time control. Thus, a plant day can be different to a normal day having 24h. The invention uses this approach for the development of the current invention. With growing pollution of soil, water, and air, modem farms try to reduce the contamination of plants with polluted air, water, and soil by using clean water, artificial light, standardized soil alternatives, or even aqua- or aeroponic installations. These modern farms, whether they are called vertical farms or indoor farms, control parameters mostly as isolated parameters or bundled in a farming system. US10765069B2 is for non-confined systems and more specifically, CN113342036A and CN109115268A use manned or unmanned aerial vehicles for data retrieval of plants’ growth status. US2017035002A1 uses an apparatus and US2020110933A1 specific sensors for plant growth optimization, whereas the herein-described invention is an apparatus- and sensor-agnostic programmable system. Further, the herein-described invention can but does not necessarily need to rely on loT, as described in US10803312B2, and is for a single confined farm and not for multiple farms as described in JP2021093971A, allowing, however, to compare data from multiple farms. CN106886187A describes a monitoring system. Monitoring systems, whatsoever, lack the possibility to actively control parameters by either following a recipe or by closed- loop intelligence rendering such systems weak when applying such systems to automated farms. Similarly, EP3996012A1 lacks the possibility to apply it to fully automated farming systems as instructions to workers for on-site manipulation are given for plant growth parameters. US2013006401 describes a system that controls and optimizes plant growth according to a formula, however, for regulated industries, such as pharmaceutical, cosmetical, and supplements, recipes are more common and work with statistical tolerances and confidence intervals in regards to boundaries rather than calculations based on formulas. WO2021251969A1 utilizes Al and/or machine-learning algorithms to optimize plant growth. However, machine learning, neuronal networks, and Al lack the ability to calculate statistical significance as specifically with Al, the output is calculated de-novo based on input data and/or results from previous outputs and thus, cannot be used for Quality by Design (QbD), tolerance analysis, and other statistical solid methods to prove by objective evidence the correctness and robustness of the results. In a similar way, US2022338421A1 makes use of machine learning algorithms to determine health predictors. Whatsoever, these predictors are not validated nor verified whereas biomarkers are specific and proven for a biochemical reaction and pathway leading to a plant-specific outcome. None of these methods describe a controlled environment control system, as a programmable system, for controlling a plant day and utilizing the data with machine learning, Al, or neural networks for trends analysis and/or biomarker, digital biomarker determination only that are subject to separate statistical significance tests. All of these methods can more or less control the parameters over time but lack internal checks, calibrations, growth protocol segmentation, and plant feedback as closed-loop or intelligent closed loops, such as with statistical sound methods and significance and/or trend analysis with machine learning, neuronal networks, or artificial intelligence for determining potential biomarkers or digital biomarkers. All of these systems, in addition, do only parametrize the growth protocol but are not sophisticated enough to mimic a day or a plant day alone or in response to the plant and the parametrized environmental factors. It is thus the object of the invention to provide a method with an optimized plant day for more enhanced growing condition of a plant. The object is achieved by a method with the subject-matter of claim 1 . An inventive method for controlling the plant growth at an indoor cultivation area is characterized by the following steps: A Provision of data about the changes of at least three parameters, that change over the course of 24 hours day cycle at an outdoor cultivation of plants, wherein said parameters related to: i) a first parameter related to light ii) a second parameter related to nutrients iii) a third parameter related to the atmosphere and/or humidity All three parameters normally change over the course of a normal 24h-day-sequence during outdoor farming. While it might be logic that the light change from day to night, also the nutrients are changing. Some nutrients such as CO2 depend on photosynthesis. Other plants, such as tomatoes, accumulate nutrients during the day and mainly grow over night. Further to this with enhanced temperatures due to