Horticultural environment system and method

Abstract

The system includes a controlled environment 10 for plants, e.g. a greenhouse. A first sensor 20 monitors an environmental condition of the controlled environment and a second sensor 30 or data sourc

Description

Field of the invention The present invention relates to a horticultural environment system and method that are particularly applicable to tree nurseries. Existing horticultural environmental control systems control the conditions of an internal controlled environment using sensors within the growing environment. They are generally dependent on costly, non-passive, input-intensive equipment in the form of heating, CO2 enrichment, lighting, dehumidification etc to maintain a growing environment suitable for the horticulture being supported. The horticultural industry has dramatically improved the yield of various food crops while reducing the inputs required in recent decades. Despite this progress, it is responsible for a significant proportion of energy consumption, particularly in controlled environments. With the increase in energy prices and growing scarcity of freshwater reserves, existing horticultural systems such as heated glasshouses and energy-intensive vertical farming models have become increasingly uneconomic and wasteful. It is therefore essential to transition to production systems that are significantly more water and energy efficient. Although there are similarities, there are often significant differences. For example, trees have different propagation needs to other vegetation such as flowers and vegetables. It is desirable to produce and maintain horticulture as efficiently and economically as possible whilst accommodating needs of the particular crops. Statement of Invention According to an aspect of the present invention, there is provided a horticultural environment system comprising: a controlled environment for accommodating plants; a first sensor configured to monitor an environmental condition of the controlled environment; a second sensor configured to monitor an environmental condition of an external environment comprising an environment external to the controlled environment; an actuator operable to open or close the controlled environment, to the environmental condition of the external environment; and, a control system configured to receive the sensor data from the first and second sensors, to identify a first difference in the environmental condition between the controlled environment and a predetermined setpoint from the sensor data, wherein upon the first difference being greater than a predetermined amount, the control system is configured to determine, from the sensor data from the second sensor, a change to the first difference upon the controlled environment being opened to the environmental condition of the external environment, wherein upon the control system determining the change reduces the first difference, the control system is configured to trigger operation of the actuator to open the controlled environment to the external environment. Preferably, the control system is configured to predict future values of the environmental condition from the sensor data from the second sensor. This may be based on recordai of prior trends, cross-reference to an external source of predicted values or trends or some other mechanism. For example, in the case of sunlight the control system might take the measured value and cross-reference sunset time to calculate how long the external environment can be relied upon before it needs to switch to artificial source. A similar approach may be taken for temperature or precipitation, for example. Alternatively, or in addition, the second sensor may be a virtual sensor or a data source of sensor readings or predictions from an external party. Unlike flowers and vegetables that never see the outdoors or are only be expected to last a season before being harvested or replaced, trees produced for woodland creation need to be "hardened off" before they leave the controlled growing environment to ensure they survive when they are planted in new woodlands. This process requires a controlled transition from optimal growing conditions to ambient external conditions to both maximise yield and survival potential once planted. embodiments moderate that exposure so that trees are exposed to extremes in a limited fashion and / or extremes are avoided, at least until a predetermined time point in the trees growth, or some other measurable threshold such as root baII size exceeding a predetermined threshold. The control system can be local and / or remote to the controlled environment, and includes setpoints from which the environmental controls are configured. These setpoints define environmental conditions for the production of crops (temperature ranges, moisture ranges, period of time to be exposed to light etc) and link to the control of the actuators (timing for opening vents, turning on and off lighting etc). The control system preferably includes a data store, which has the potential to record camera imagery related to the health and growth of crops. This can be used to optimise the growing conditions within the controlled environment as more data is collected for specific species. The data repository may encode setpoints on environmental factors for growing the trees. It may be comprehensive or limited to trees or other crops being propagated. The setpoints define environmental conditions for propagation of the trees either in direct terms (temperature ranges, moisture ranges, period of time to be exposed to light etc) and / or linked to conditions and the actuators (timing for opening vents, turning on an off lighting etc). Sensor data received from the sensors is indicative of the controlled and external environment ~ preferably the external environment may be that in which the tree will eventually be planted, in which case the control system may default to exposing the tree to as much of the normal environmental conditions as it can (for example, it may act as a buffer during initial propagation and not expose the tree to excesses in temperature cold, moisture, wind etc). Alternatively, the control system may utilise the external environment during periods where it coincides (within a predefined tolerance range) to setpoints defined in the data repository for the tree (so the actuators may be opened to the external environment during periods where the environment coincides with the setpoints set for the tree at that stage in the tree's development). Preferably, the control system and sensors integrate soil moisture, humidity, wet bulb, temperature, CO? and light readings inside and outside the growing area to automatically adjust controllable components in the glasshouse including fans, vents, irrigation, lights and screens to create the optimal growing conditions for the species growing. Brief Description of Embodiments of the present invention will now be described by way of example only with reference to the accompanying drawings in which: Figure 1 is a schematic diagram of a horticultural environment system according to an embodiment; Figure 2 is a schematic diagram of aspects of a horticulture I environment system according to an embodiment. Detailed Description Figure 1 is a schematic diagram of a horticultural environment system according to an embodiment. The system includes: a controlled environment 10 for accommodating plants; a first sensor configured 20 to monitor an environmental condition of the controlled environment 10; a second sensor 30 configured to monitor the environmental condition of an external environment 15 comprising an environment external to the controlled environment; an actuator 4G operable to open or close the controlled environment to the environmental condition of the external environment; and, a control system 50 configured to receive the sensor data for the environmental condition from the first and second sensors, to identify a first difference in the environmental condition between the controlled environment and a predetermined setpoint and determine, from the sensor data from the second sensor, a change to the first difference leeward side will open rather than the windward side to prevent damage. A similar approach with machine learning and artificial intelligence techniques, leveraging indices such as the Normalized Difference Vegetation index (NDVI) and Normalized Red Edge Index (NDRE). NDVI and similar indices are to assess and predict crop quality by providing a quantifiable measure of crop / tree hea I th. As well as assessing crop quality this can also be used for the early detection of disease within crops, allowing for pre-emptive action as trees are transferred from inside the controlled environment to outside. This results in potentially mitigated disease spread and the prevention of further crop damage. Through these images and indices, it is possible to better understand the impact of environmental conditions internal to the controlled growing environment on crop performance, integrating both health and quality. These images are preferably recorded in the data repository, and as the dataset grows it allows for greater insight and optimisation of the machine learning model(s). At the most basic level, this is understanding crop establishment based on the success rate of crop based on initial sowing. The data encompasses environmental conditions both inside and outside the growing environment and the analysis of crop images. By correlating images of crops with environmental conditions, it's possible to determine the influence of these conditions on crop quality. Understanding the relationship between environmental conditions and crop quality enables the prediction of crop performance. This knowledge forms the basis for optimizing growing conditions overtime, aiming to enhance crop quality, establishment, and overall health. Given the emphasis on growing conditions as a determinant for crop quality and health, it's possible to further explore how specific environmental variables—such as temperature, humidity, light intensity, and CG2 levels—affect different crop species. Through this, deeper insight can be achieved, allowing for increasingly optimised controlled growing environments ensuring maximum crop yield and quality. Embodiments of the present invention can be used in any geography to propagate trees or other horticulture or crops more efficiently. Further, this technology can be used to create any preferred internal environment for propagation of any crop. The use of the controlled environment and control system reduces inputs dramatically which does the following: Reduces cost Reduces Labour Improves the efficiency of material input usage Reduces the area needed to produce the same output of trees Uses natural light, heat and CO2 more efficiently without the need to enrich these elements it improves the quality of the trees It leads to better root development Which in turn leads to more resilient trees that can withstand a changing climate This means a lower cost of replacing losses once they are planted It also leads to higher early-stage growth in the trees or yield Additional features include: The control systems is extensible. Any sensors can be added and linked to any elements of the glasshouse, whether in a 1:1 relationship or in combination, with control actions being determined by the control system based on individual or collective sensor readings (for example weighted or subject to some threshold at which point particular sensor readings may take priority on a control action) In one embodiment, 5 temperature, humidity and wet bulbs are used inside the glasshouse, 1 temperature, humidity and wet bulb outside the glasshouse, 2 light sensors (photosynthetically active radiation (PAR)), lx CO2 sensor (Parts per million (PPM)), an external weather station giving wind direction, solar radiation and a second temperature and humidity reading with precipitation in mm of rainfall. 6 soil moisture sensors are used in one example for irrigation automation. Cameras may be mounted in the glasshouse for assessing plant health. To illustrate the utility of the environmental control system we can consider the setpoints for tree propagation in two different geographies: 1) Downy Birch / Betula Pubescens (Grown in the Northern Europe) Soil Moisture: 50% (20% tolerance) Light (pmol m-2 s-1): 500 PAR Temperature: 25°c (5°c tolerance) Carbon Dioxide: 600 ppm Air Humidity: 65% (20% tolerance) Daylight hours: 16 2) African baobab / Adansonia digitata (Grown in Southern Africa) Soil Moisture: 20% (20% tolerance) Light (pmol m-2 s-1): 1,000 PAR Temperature: 27.5°c (5°c tolerance) Carbon Dioxide: 600 ppm Air Humidity: 50% (20% tolerance) Daylight hours: 16 Examples of sensors used in control system: Weather device (Wind speed, wind direction, temperature, humidity, air pressure, rainfall, global radiation) Soil Moisture Carbon Dioxide Humidity Temperature Light Multispectral camera This list of sensors is not exhaustive, and subject to change based on the specific geography and requirements but provides an example of the types of sensors being used. Example 1 - High temperatures forecasted We're currently growing Downy Birch / Betula Pubescens with a target temperature range of 22.5-27.5°c Time is currently 11:00 Internal temperature sensor is at 25°c External temperature sensor is currently at 23°c Forecast is for sunshine all day Data suggests temperature will exceed 30°c by 12:00 Action: Open vents partially to allow airflow, reducing temperature in glasshouse Close screens to shade crop and prevent increase in temperature Example 2 - Preparation of transfer of crop from inside to outside controlled environment The forecast for the next week is an average of 19°c daytime temperature, with full sun. Crop will be transplanted in one week, and so to prepare crop vents and screens are opened automatically allowing the crop to acclimatise to the natural conditions outside the controlled environment. Example 3 - High winds and high temperature High winds are forecasted for the next 2 days. As well as this, the temperature will be high outside the controlled environment. The system accounts for this, and only opens the west facing vents thus preventing damage to the equipment due to the high winds. Set points vary per species but as an example for Betula Pubescens (Downy Birch) would be: Soil moisture 40% Light 500 pmol m-2 s-1 (PAR) Temperature 25 degrees Carbon Dioxide 600 parts per million Air humidity 65% Daylight hours 16 It is to be appreciated that certain embodiments of the invention as discussed below may be incorporated as code (e.g., a software algorithm or program) residing in firmware and / or on computer useable medium having control logic for enabling execution on a computer system having a computer processor. Such a computer system typically includes memory storage configured to provide output from execution of the code which configures a processor in accordance with the execution. The code can be arranged as firmware or software, and can be organized as a set of modules such as discrete code modules, function calls, procedure calls or objects in an object-oriented programming environment. If implemented using modules, the code can comprise a single module or a plurality of modules that operate in cooperation with one another. Optional embodiments of the invention can be understood as including the parts, elements and features referred to or indicated herein, individually or collectively, in any or all combinations of two or more of the parts, elements or features, and wherein specific integers are mentioned herein which have known equivalents in the art to which the invention relates, such known equivalents are deemed to be incorporated herein as if individually set forth. Although illustrated embodiments of the present invention have been described, it should be understood that various changes, substitutions, and alterations can be made by one of ordinary skill in the art without departing from the present invention.

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