Systems and methods for optimizing local lighting in a horticulture production facility by controlled exploitation of shade avoidance syndrome

Abstract

A system for providing horticulture lighting for a crop in a horticulture production facility is provided, including light sources, sensors, and a controller. The light sources include red and far-red light sources, and generate local light illuminating a plant canopy of the crop. The controller (1) periodically captures, via the sensors, imaging and climate data between a first and second date; (2) generates, via a plant growth model, an estimated plant canopy at a future date based on the imaging and climate data; (3) receives a light reception map of the plant canopy; (4) generates, based on the light reception map and the estimated plant canopy, a growth inducing target map; (5) generates, based on the growth inducing target map, a growth inducing lighting recipe including an optimized red to far-red light ratio; (6) adjusts, via the light sources, the local light based on the growth inducing lighting recipe.

Description

[0001] Systems and methods for optimizing local lighting in a horticulture production facility by controlled exploitation of shade avoidance syndrome

[0002] FIELD OF THE DISCLOSURE

[0003] The present disclosure is generally directed to providing horticulture lighting for a crop in a horticulture production facility, and, more specifically, to optimizing local lighting in a horticulture production facility by controlled exploitation of shade avoidance syndrome (SAS).

[0004] BACKGROUND

[0005] Generally, light limitation presents a clear threat to plant survival. Accordingly, this threat has driven an evolution of highly adaptive strategies to tolerate and / or avoid shading by neighboring vegetation. Shade avoidance is a set of responses that plants display when they are subjected to the shade of another plant. It often includes elongation, altered flowering time, increased apical dominance and altered partitioning of resources.

[0006] Increasing energy prices are a major concern for growers operating horticulture production facilities. Horticulture production facilities include greenhouses and plant factories practicing indoor agriculture and / or vertical farming. While many growers have considered reducing intensity or even eliminating (where possible) local lighting, both options may result in serious adverse impacts on yield totals and plant quality, especially during sunlight-deprived seasons. Existing solutions to reduce energy consumption while providing sufficient light include dynamic dimming, spectral dimming, spatial dimming, and more.

[0007] There remains a need in the art for systems and methods to reduce energy consumption while providing sufficient local light to a plant canopy in a horticulture production facility, while taking advantage of the plant’s natural response to reduced lighting conditions.

[0008] SUMMARY OF THE DISCLOSURE The present disclosure is generally directed to optimizing local lighting energy in a horticulture production facility by controlled exploitation of shade avoidance syndrome (SAS). Broadly, the system identifies portions of a plant canopy of a crop grown in the facility that will not receive sufficient local light when one or more light sources within the facility environment operate with reduced light intensity. The system then determines a growth inducing lighting recipe and applies this lighting recipe to the horticulture production facility. The growth inducing light recipe uses an optimized red light to far-red light ratio for SAS-induced improved plant growth despite an overall reduction in light intensity and reduced power consumption.

[0009] When subject to vegetational shading, plants are exposed to a variety of informational signals, which include altered light quality and a reduction in light quantity. These informational signals indicate a decrease in a ratio of red to far-red wavelengths (low R:FR ratio), and are detected by the phytochrome family of plant photoreceptors. Monitoring an R:FR ratio of light incident upon a plant can provide an early and unambiguous warning of the presence of competing vegetation, thereby evoking escape responses before the plant is actually shaded. The molecular mechanisms underlying physiological responses to alterations in light quality have now started to emerge, with major roles suggested for the phytochrome interacting factor (PIF) and DELLA families of transcriptional regulators. Such studies suggest a complex interplay between endogenous and exogenous signals mediated by multiple photoreceptors. The phenotypic similarities between physiological responses, habitually referred to as “shade avoidance syndrome,” and other abiotic stress responses suggest plants may integrate common signaling mechanisms to respond to multiple perturbations in their natural environment.

[0010] An equation for R:FR ratio is shown below as Equation 1 :

[0011] As shown in Equation 1, R:FR ratio is defined as ratio of irradiance between red (660 nm and 670 nm) and far-red (725 nm and 735 nm). In sunlight, the R:FR ratio is low (about 0.6) at the beginning and the end of the solar day. By comparison, the R:FR ratio at solar noon is about 1.0 to 1.3. In plant canopies, the R:FR ratio perceived by plant organs varies spatiotemporally in a range within which slight R:FR variation causes large variation in phytochrome photo-equilibrium. Phytochromes regulate different processes through the plant life cycle, including induction of seed germination, seedling de-etiolation, flowering time, fruit quality, root elongation, and tolerance to biotic and abiotic stressors. Red light, far-red light, and the R:FR ratio regulate a large range of processes throughout plant life. Previous work in the art has shown that, under blue light, exposing plants to a lower R:FR ratio promotes: (1) rapid elongation of stems and leaves and an upward reorientation of leaves (leaf hyponasty) in dicotyledonous and ornamental species for elevating leaves within the canopy to enhance light-foraging capacity in dense stands and enable plants to overtop competing vegetation; (2) accelerated flowering for promoting seed set and enhancing the probability of reproductive success if the reduced R:FR ratio signal persists and the plant is unable to overtop competing vegetation; and (3) higher dry matter content in tomatoes, cucumber and lettuce (lactuca sativa), mostly from stem parts.

[0012] Generally, the system disclosed herein employs light sources, imaging sensors, climate sensors, and a controller. The light sources are arranged to provide local light to a crop of plants being grown within a horticulture production facility. The light sources include at least one red light source and at least one far-red light source to generate local light based on a growth inducing lighting recipe incorporating an optimized red light to far-red light ratio. The imaging sensors, such as red-green-blue (RGB) cameras, thermal cameras, and / or infrared (IR) sensors, and the climate sensors, such as temperature sensors and / or humidity sensors, are arranged to capture imaging data and climate data regarding the crop.

[0013] The imaging and climate data is provided to a pre-trained plant growth model executed by a processor of the controller. The plant growth model may be a recurrent neural network (RNN) trained by historical imaging data and historical climate data corresponding to both the crop and the horticultural production facility. The plant growth model uses this information to generate an estimated plant canopy at a future date.

[0014] Further, the system generates a light reception map indicative of how plant canopy receives the local light. The light reception map can be generated by temporarily reducing the intensity of the local light and analyzing data captured by the image sensors and / or photosynthetically active radiation (PAR) sensors. The intensity of the local light may be reduced according to an energy savings target.

[0015] The controller then processes the light reception map and the estimated plant canopy to generate a growth inducing target map to identify which portions of the plant canopy will require SAS-induced growth to compensate for reduced local lighting. The growth inducing target map is then translated into a growth inducing lighting recipe incorporating an optimized red light to far-red light ratio. The controller then actuates the light sources to generate local light based on the growth inducing lighting recipe according to a lighting optimization schedule. When the growth inducing lighting recipe is not implemented during the lighting optimization schedule, the light sources will generate local light according to the reduced intensity corresponding to the energy savings target.

[0016] Generally, in one aspect, a system for providing horticulture lighting for a crop in a horticulture production facility is provided. The system includes a plurality of light sources. In various embodiments of the invention, the light sources employ one or more lightemitting diodes (LEDs). The plurality of light sources includes at least one red light source and at least one far red-light source. The plurality of light sources generates local light. The local light illuminates at least a portion of a plant canopy of the crop.

[0017] As used herein for purposes of the present disclosure, the term “LED” should be understood to include any electroluminescent diode or other type of carrier injection / juncti on-based system that is capable of generating radiation in response to an electric signal. Thus, the term LED includes, but is not limited to, various semiconductorbased structures that emit light in response to current, light emitting polymers, organic light emitting diodes (OLEDs), electroluminescent strips, and the like. In particular, the term LED refers to light emitting diodes of all types (including semi-conductor and organic light emitting diodes) that may be configured to generate radiation in one or more of the infrared spectrum, ultraviolet spectrum, and various portions of the visible spectrum (generally including radiation wavelengths from approximately 400 nanometers to approximately 700 nanometers). Some examples of LEDs include, but are not limited to, various types of infrared LEDs, ultraviolet LEDs, red LEDs, blue LEDs, green LEDs, yellow LEDs, amber LEDs, orange LEDs, and white LEDs. It also should be appreciated that LEDs may be configured and / or controlled to generate radiation having various bandwidths (e.g., full widths at half maximum, or FWHM) for a given spectrum (e.g., narrow bandwidth, broad bandwidth), and a variety of dominant wavelengths within a given general color categorization.

[0018] It should also be understood that the term LED does not limit the physical and / or electrical package type of an LED. For example, as discussed above, an LED may refer to a single light emitting device having multiple dies that are configured to respectively emit different spectra of radiation (e.g., that may or may not be individually controllable). Also, an LED may be associated with a phosphor that is considered as an integral part of the LED (e.g., some types of white LEDs). In general, the term LED may refer to packaged LEDs, non-packaged LEDs, surface mount LEDs, chip-on-board LEDs, T-package mount LEDs, radial package LEDs, power package LEDs, LEDs including some type of encasement and / or optical element (e.g., a diffusing lens), etc. The term “light source” should be understood to refer to any one or more of a variety of radiation sources, including, but not limited to, LED-based sources (including one or more LEDs as defined above). A given light source may be configured to generate electromagnetic radiation within the visible spectrum, outside the visible spectrum, or a combination of both. Hence, the terms “light” and “radiation” are used interchangeably herein. Additionally, a light source may include as an integral component one or more filters (e.g., color filters), lenses, or other optical components.

[0019] The term “spectrum” should be understood to refer to any one or more frequencies (or wavelengths) of radiation produced by one or more light sources. A given spectrum may have a relatively narrow bandwidth (e.g., a FWHM having essentially few frequency or wavelength components) or a relatively wide bandwidth (several frequency or wavelength components having various relative strengths). It should also be appreciated that a given spectrum may be the result of a mixing of two or more other spectra (e.g., mixing radiation respectively emitted from multiple light sources). For purposes of this disclosure, the term “color” is used interchangeably with the term “spectrum.” However, the term “color” generally is used to refer primarily to a property of radiation that is perceivable by an observer (although this usage is not intended to limit the scope of this term). Accordingly, the terms “different colors” implicitly refer to multiple spectra having different wavelength components and / or bandwidths. It also should be appreciated that the term “color” may be used in connection with both white and non-white light.

[0020] The system further includes one or more imaging sensors. The one or more imaging sensors are configured to capture imaging data. The imaging data corresponds to the plant canopy. At least one of the one or more imaging sensors may be an RGB camera, a thermal camera, and / or an IR sensor.

[0021] The system further includes one or more climate sensors. The one or more climate sensors are arranged to capture climate data. The climate data corresponds to the plant canopy. At least one of the one or more climate sensors may be a temperature sensor and / or a humidity sensor.

[0022] The system further includes a controller. The controller is communicatively coupled to the plurality of light sources, the one or more imaging sensors, and the one or more climate sensors, and is configured to periodically capture, via the one or more imaging sensors and the one or more climate sensors, the imaging data and the climate data between a first date and a second date. According to an example, the second date is at least seven days after the first date. The controller is further configured to generate, via a plant growth model, an estimated plant canopy. The estimated plant canopy corresponds to a future date. The estimated plant canopy is generated based on the imaging data and the climate data.

[0023] The controller is further configured to receive a light reception map of the plant canopy of the local light at a reduced lighting intensity level.

[0024] The controller is further configured to generate, based on the light reception map and the estimated plant canopy, a growth inducing target map. The growth inducing target map corresponds to the future date.

[0025] The controller is further configured to generate, based on the growth inducing target map, a growth inducing lighting recipe. The growth inducing lighting recipe includes an optimized red light to far-red light ratio to be applied to the plant canopy between the second date and the future date.

[0026] The controller is further configured to adjust, via the plurality of light sources, the local light based on the growth inducing lighting recipe. The local light may be adjusted based on the growth inducing lighting recipe according to one or more growth inducing intervals of a lighting optimization schedule. The lighting optimization schedule may reduce an intensity of the local light according to the reduced lighting intensity level outside of the one or more growth inducing intervals. The one or more growth inducing intervals may occur for thirty minutes at a beginning of a lighting day and for thirty minutes immediately prior to an end of the lighting day.

[0027] According to an example, the light reception map is generated by: (1) adjusting the local light according to the reduced lighting intensity level for a reduced lighting intensity period, wherein the reduced lighting intensity level corresponds to an energy saving target; (2) capturing, via the one or more imaging sensors and / or one or more photosynthetically active radiation (PAR) sensors, reduced lighting intensity sensor data; and (3) generating the light reception map based on the reduced lighting intensity sensor data. The reduced lighting intensity period for capturing the reduced lighting intensity sensor data may be approximately 15 seconds. The energy savings target may be approximately 20 percent.

[0028] According to an example, the plant growth model may be an RNN model corresponding to both the horticultural production facility and the crop. The plant growth model may be trained based on a plurality of training pairs of historical imaging data and historical climate data. The historical imaging data and the historical climate data may correspond to both the horticultural production facility and the crop. Each of the plurality of training pairs may correspond to both a calendar time stamp and a plant age time stamp.

[0029] According to an example, the estimated plant canopy and the growth inducing target map may correspond to a two-dimensional plane or a three-dimensional volume of the plant canopy.

[0030] Generally, in another aspect, a method for providing horticulture lighting for a crop in a horticulture production facility is provided. The method includes periodically capturing, via one or more imaging sensors and one or more climate sensors, imaging data and climate data between a first date and a second date, wherein the imaging data and the climate data corresponds to a plant canopy of the crop. The method further includes generating, via a plant growth model executed by a controller, an estimated plant canopy corresponding to a future date based on the imaging data and the climate data. The method further includes receiving, via the controller, a light reception map of the plant canopy receiving a local light at a reduced lighting intensity level. The method further includes generating, via the controller, based on the light reception map and the estimated plant canopy, a growth inducing target map corresponding to the future date. The method further includes generating, via the controller, based on the growth inducing target map, a growth inducing lighting recipe, wherein the growth inducing lighting recipe includes an optimized red light to far-red light ratio to be applied to the plant canopy between the second date and the future date. The method further includes adjusting, via a plurality of light sources, the local light based on the growth inducing lighting recipe.

[0031] In various implementations, a processor or controller can be associated with one or more storage media (generically referred to herein as “memory,” e.g., volatile and non-volatile computer memory such as ROM, RAM, PROM, EPROM, and EEPROM, floppy disks, compact disks, optical disks, magnetic tape, Flash, OTP -ROM, SSD, HDD, etc.). In some implementations, the storage media can be encoded with one or more programs that, when executed on one or more processors and / or controllers, perform at least some of the functions discussed herein. Various storage media can be fixed within a processor or controller or can be transportable, such that the one or more programs stored thereon can be loaded into a processor or controller so as to implement various aspects as discussed herein. The terms “program” or “computer program” are used herein in a generic sense to refer to any type of computer code (e.g., software, firmware, or microcode) that can be employed to program one or more processors or controllers. It should be appreciated that all combinations of the foregoing concepts and additional concepts discussed in greater detail below (provided such concepts are not mutually inconsistent) are contemplated as being part of the inventive subject matter disclosed herein. In particular, all combinations of claimed subject matter appearing at the end of this disclosure are contemplated as being part of the inventive subject matter disclosed herein. It should also be appreciated that terminology explicitly employed herein that also may appear in any disclosure incorporated by reference should be accorded a meaning most consistent with the particular concepts disclosed herein.

[0032] These and other aspects of the various embodiments will be apparent from and elucidated with reference to the embodiment s) described hereinafter.

[0033] BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In the drawings, like reference characters generally refer to the same parts throughout the different views. Also, the drawings are not necessarily to scale, emphasis instead generally being placed upon illustrating the principles of the various embodiments.

[0035] Fig. l is a schematic diagram of a system for providing horticultural lighting to a crop in a horticultural production facility, according to aspects of the present disclosure.

[0036] Fig. 2A is an illustration of an observed plant canopy at a first date, according to aspects of the present disclosure.

[0037] Fig. 2B is an illustration of an observed plant canopy at a second date, according to aspects of the present disclosure.

[0038] Fig. 3 is an illustration of an estimated plant canopy, according to aspects of the present disclosure.

[0039] Fig. 4A is an illustration of a light reception map, according to aspects of the present disclosure.

[0040] Fig. 4B is an illustration of a growth inducing target map, according to aspects of the present disclosure.

[0041] Fig. 5 is an illustration of light sources implementing a growth inducing lighting recipe, according to aspects of the present disclosure.

[0042] Fig. 6 is an illustration of plants experiencing growth inducement via shade avoidance syndrome, according to aspects of the present disclosure.

[0043] Fig. 7 is a schematic illustration of a controller of a system for providing horticultural lighting for a crop in a horticulture production facility, according to aspects of the present disclosure. Fig. 8 is a flowchart of a method for providing horticulture lighting for a crop in a horticulture production facility, according to aspects of the present disclosure.

[0044] DETAILED DESCRIPTION OF EMBODIMENTS

[0045] The present disclosure is generally directed to optimizing local lighting energy in a horticulture production facility by controlled exploitation of shade avoidance syndrome (SAS). Broadly, the system identifies portions of a plant canopy of a crop grown in the facility that will not receive sufficient grow light at when one or more light sources within the facility environment operate with reduced light intensity. The system then determines a growth inducing lighting recipe and applies this lighting recipe to the horticulture production facility. The growth inducing light recipe uses an optimized red light to far-red light ratio for SAS-induced improved plant growth despite an overall reduction in light intensity and reduced power consumption.

[0046] FIG. 1 is a schematic diagram of a system 10 for providing horticultural lighting to a crop C in a horticulture production facility HPF, according to various embodiments of the invention. The horticulture production facility HPF may be any variety of enclosed or partially enclosed cultivation environment, such as a greenhouse, plant factory, indoor vertical farm, etc. In some instances, such as in the example of a greenhouse, the horticulture production facility HPF allows for sunlight to pass through one or more walls or panels of the horticulture production facility HPF to reach the crop C. The crop C may be any variety of plant or vegetation capable of being grown within a horticulture production facility and may be defined by a plant canopy PC (see FIGS. 2 A and 2B) corresponding to the above-ground or exposed portions of the crop C. Subsequent analysis of the crop C may be performed in terms of a two-dimensional plane 2DP or a three-dimensional volume 3DV of the plant canopy PC.

[0047] As shown in FIG. 1, in various embodiments, the system 10 includes a controller 100, a plurality of light sources 200, and a variety of sensors 300, 400, 500. Broadly, with additional reference to FIG. 7, the controller 100 includes a memory 125, a processor 175, and a transceiver 195. The controller 100 stores and processes data captured by the sensors 300, 400, 500 to program the light sources 200 to improve crop growth within the horticulture production facility HPF. The controller 100 may be communicatively coupled to the light sources 200 and the sensors 300, 400, 500 via wired or wireless connection. The transceiver 195 of the controller 100 may be used to implement the wireless connection via any applicable protocol, such as Bluetooth, Wi-Fi, Zigbee, ultrawideband, etc. In some examples, the controller 100 may be arranged within the horticulture production facility HPF, such as within a control panel. In other examples, the controller may be outside of the horticulture production facility HPF, such as within an external office, control room, wiring closet, equipment room, or server room.

[0048] The light sources 200 are arranged within the horticulture production facility HPF to provide local light 202 to aid the plant canopy PC. In this example, local light 202 refers to light generated by the system 10 within the horticulture production facility HPF, rather than natural sunlight entering the horticulture production facility HPF via one or more windows configured to permit natural light penetration (such as in a greenhouse configuration). The local light 202 may also be referred to as supplemental light. The primary purpose of the local light 202 is to aid in the growth of the crop C.

[0049] In various embodiments of the invention, the light sources 200 employ one or more LEDs configured and controllable to emit light within a desired range of wavelengths. In the example of FIG. 1, the plurality of light sources 200 include red light sources 200R1, 200R2, far-red light sources 200FR1, 200FR2, and a blue light source 200B1. However, a real-world system would likely include many more light sources 200 than those shown in FIG. 1. The red light sources 200R1, 200R2 generate red local light 202R1, 202 R2 having wavelengths between 660 nanometers and 670 nanometers. The far-red light sources 200FR1, 200FR2 generate far red local light 202FR1, 202FR2 having wavelengths between 725 nanometers and 735 nanometers. The blue light source 200B1 generates blue local light 202B1 having wavelengths between 450 nanometers and 495 nanometers. The red light sources 200R1, 200R2 and the far-red light sources 200F1, 200F2 may be used to implement a growth inducing lighting recipe 118 within the horticulture production facility HPF. The growth inducing lighting recipe 118 utilizes an optimized red light to far-red (R:FR) light ratio 120 to induce SAS-based plant growth in certain portions of the plant canopy PC. As will be described in further detail, the growth inducing lighting recipe 118 is generated based on data collected by the sensors 300, 400, 500. In some examples, combinations of the light sources 200 may be installed in bundles. For example, a bundle could package together one red light source 200R, one far-red light source 200FR, and one blue light source 200B. The controller 100 may then individually control the three light sources 200R, 200FR, 200B to generate the desired local light 202.

[0050] The sensors 300, 400, 500 are arranged within the horticulture production facility HPF to capture data related to the plant canopy PC of the crop C. The example of FIG. 1 includes two imaging sensors 300a, 300b, two climate sensors 400a, 400b, and a photosynthetically active radiation (PAR) sensor 500. The imaging sensors 300a, 300b capture imaging data 302a, 302b corresponding to the plant canopy PC. In some examples, the imaging data 302a, 302b may be two dimensional and correspond to the two-dimensional plane 2DP of the plant canopy PC. In other examples, the imaging data 302a, 302b may be three dimensional and correspond to the three-dimensional volume 3DV of the plant canopy PC. In some examples, at least one of the imaging sensors 300a, 300b may be a red-green- blue (RGB) camera, a thermal camera, or an infrared (IR) camera. The imaging data 302a, 302b captured by the imaging sensors 300a, 300b may be used for at least two primary purposes. First, the imaging data 302a, 302b may be used to track the growth of the plant canopy PC over time, such that a plant growth model 106 may be used to project the growth of the plant canopy PC at a future date 110. Second, the imaging data 302a, 302b may be used to evaluate the local light 202 received at different sections of the plant canopy PC. In some examples, the imaging sensors 300a, 300b may be bundled or packaged with one or more of the light sources 200.

[0051] The climate sensors 400a, 400b capture climate data 402a, 402b corresponding to the environment within horticulture production facility HPF. In some examples, at least one of the climate sensors 400a, 400b may be a temperature sensor or a humidity sensor. The climate data 402a, 402b captured by the climate sensors 400a, 400b is primarily used by the plant growth model 106 to project the growth of the plant canopy PC at a future date 110. In some examples, the climate sensors 400a, 400b may be bundled or packaged with one or more of the light sources 200 and / or one or more of the imaging sensors 300a, 300b.

[0052] The PAR sensor 500 captures PAR data 502 corresponding to the plant canopy PC. In particular, the PAR data 502 represents the intensity of light upon the plant canopy PC at wavelengths associated with photosynthesis, such as from 400 nanometers to 700 nanometers. As with the imaging data 302, the PAR data 502 may be used to evaluate the local light 202 received at different sections of the plant canopy PC.

[0053] FIG. 2A illustrates a top view of an image of an example plant canopy PC at a first date 102, while FIG. 2B illustrates a top view of the same plant canopy PC at a second date 104 (see FIG. 7). The images may be composites of imaging data 202 captured on the first and second dates 102, 104. In one example, the second date 104 may be seven day after the first date 102. As shown, and with further reference to FIGS. 1 and 7, the crop C of the plant canopy PC has slightly grown in the period between the first date 102 and the second date 104. FIG. 3 is an illustration of an estimated plant canopy 108 at a future date 110 (see FIG. 7). In some examples, the future date 110 may be twenty-one days after the second date 104 (see FIG. 7). The estimated plant canopy 108 is generated based on imaging data 302 and climate data 402 periodically collected between the first date 102 and the second date 104. With further reference to FIG. 1, while the estimated plant canopy 108 of FIG. 3 corresponds to a two-dimensional plane 2DP of the plant canopy PC, in other examples, the estimated plant canopy 108 may correspond to a three-dimensional volume 3DV of the plant canopy PC.

[0054] With further reference to FIG. 7, the estimated plant canopy 108 is generated by a plant growth model 106 executed by a processor 125 of a controller 100. The plant growth model 106 may be a pre-trained neural network model, such as a recurrent neural network (RNN) model. The plant growth model 106 is trained based on data corresponding to both the horticulture production facility HPF (see FIG. 1) and the specific crop C (see FIG. 1) being grown. For example, a memory 175 of the controller 100 may store growth model training data 140 corresponding to both the horticulture production facility HPF and the specific crop C. In other examples, the growth model training data 140 may be provided from an external source via transceiver 195, such as a centralized control station. The growth model training data 140 includes a series of training pairs 132 of historical imaging data 134 (visual representations of the plant canopy PC) and historical climate data 136 (statistical representations of the environment within the horticulture production facility HPF). Each training pair 132 may correspond to a calendar time stamp 138 representing the date and / or time the training data 132 was captured. Each training pair 132 may also correspond to a plant age time stamp 140 representing the age of the plant when the training data 132 was captured. Once trained with the growth model training data 140, the plant growth model 106 may be able to correlate the captured imaging data 302 and climate data 402 of the current plant canopy PC with previously observed growth patterns to generate the estimated plant canopy 108 at a future date 110.

[0055] FIG. 4A illustrates an example light reception map 114. A light reception map 114 represents the local light 202 (see FIG. 1) generated by light sources 200 (see FIG. 1) and received by the plant canopy PC (see FIG. 1) at a certain point in time. The values of the light reception map 114 may be impacted by a variety of factors, such as intensity of the local light 202 and shading within the horticultural production facility HPF. The shading may be caused by other plants of the plant canopy PC, or by other aspects of the horticulture production facility HPF. In the light reception map 114, empty boxes represent portions of the plant canopy PC receiving full light, hatched boxes represent portions of the plant canopy PC receiving partial light, and cross-hatched boxes represent portions of the plant canopy PC receiving little-to-no light.

[0056] In the example of FIG. 4 A, the light reception map 114 corresponds to the light sources 200 producing local light 202 at a reduced lighting intensity level 204. For example, the reduced lighting intensity level 204 may be 25%, 50%, or 75% of full intensity. The reduced lighting intensity level 204 may correspond to an energy savings target 114 (see FIG. 7). A user of the system 10 (see FIG. 1) may implement an energy savings target 114 to reduce energy usage and costs required for operating the light sources 200 or the horticulture production facility HPF as a whole. Accordingly, the energy savings target 114 may be represented as a reduction in energy consumed in energy-based units (such as watts) or a reduction in costs in currency units (such as dollars). In some examples, the energy savings target 114 may be programmed via a user input into a user interface integrated with and / or communicatively coupled to the controller 100 (see FIG. 1).

[0057] Upon receiving the energy savings target 114, the controller 100 reduces the intensity of the local light 202 according to the energy savings target 114 for a reduced lighting intensity period 206 (see FIG. 7). For example, if the energy savings target 114 is 25%, the intensity of the local light 202 may be reduced to 75% of full intensity for 15 seconds. During this brief reduced lighting intensity period 206, the system 10 captures reduced intensity sensor data 304 (see FIG. 7) representative of the local light 202 incident upon different portions of the plant canopy PC. In some examples, the reduced intensity sensor data 304 is captured by one or more imaging sensors 300 (see FIG. 1), such as RGB cameras, thermal cameras, and / or IR sensors. In other examples, the reduced intensity sensor data 304 is captured by one or more PAR sensors 500. The processor 125 then synthesizes the reduced intensity sensor data 304 in the light reception map 114 shown in FIG. 4 A.

[0058] FIG. 4B illustrates a growth inducing target map 116. The growth inducing target map 116 represents the effect of the reduced lighting intensity level 204 (represented by the light reception map 112 of FIG. 4 A) upon the estimated plant canopy 108 at a future date 110, as shown in FIG. 3. Accordingly, the growth inducing target map 116 indicates the portions of the plant canopy PC which will require local light 202 implementing an optimized R:FR light ratio 120 (see FIG. 7) to induce SAS-based plant growth. Similarly to the light reception map 114 of FIG. 4 A, in the growth inducing target map 116 empty boxes represent portions of the plant canopy PC which do not require SAS-based inducement, the hatched boxes represent portions of the plant canopy PC which require a low degree of SAS-based inducement, and cross-hatched boxes represent portions of the plant canopy PC which require a high degree of SAS-based inducement. The variations in hatching and crosshatching between the light reception map 114 and the growth inducing target map 116 may be due to the estimated plant canopy 108 showing some plants of the estimated future plant canopy PC crowding or shading others. While the growth inducing target map 116 of FIG. 4B corresponds to a two-dimensional plane 2DP (see FIG. 1) of the plant canopy PC (see FIG. 1), in other examples, the growth inducing target map 116 may correspond to a three- dimensional volume 3DV (see FIG. 1) of the plant canopy PC.

[0059] Once the growth inducing target map 116 has been generated, the controller 100 then translates the growth inducing target map 116 into a growth inducing lighting recipe 118. The growth inducing lighting recipe 118 is generated by converting the growth inducing target map 116 into a lighting scheme capable of being implemented by the light sources 200 of the system. The growth inducing lighting recipe 118 determines which aspects of the light sources 200 will be configured to generate local light 200 according to an optimized R:FR light ratio 120 (see FIG. 7) to induce SAS-based growth.

[0060] The values of the optimized R:FR light ratio 120 is crop-specific and timedependent. The value chosen is based on the crop’s C historical responses (during previous cultivation cycles implementing an energy savings target 114), the current response of the plant canopy PC, and the growth target for the crop C at a future date 110 (see FIG. 7). In one example, a value of 0.6 may be suitable for crops C that respond to shading and other occlusions during sunrise and sunset due to differences in the angle of incident light and the shadows of neighboring plants. The overall intensity of the local light 202 produced by the growth inducing lighting recipe 118 may be greater than or less than the reduced lighting intensity level 204 derived from the energy savings target 114.

[0061] FIG. 5 illustrates three lighting units 600a-c arranged over a two-dimensional plane 2DP of a plant canopy PC. Each lighting unit 600a-c includes five rows of ten light sources 200. The lighting units 600a-c are in wired or wireless communication with the controller 100. With the knowledge of the arrangement of the three lighting units 600a-c, the controller 100 generates the growth inducing lighting recipe 118, and provides the relevant aspects of the growth inducing lighting recipe 118a-c to the three lighting units 600a-c. In the example of FIG. 5, the growth inducing lighting recipe 118 causes some of the light sources 200 (depicted as empty boxes) to produce local light 202 (see FIG. 1) at a reduced lighting intensity level 204 (see FIG. 7). The other light sources 200 (depicted as black boxes) produce local light 202 according to the optimized R:FR light ratio 120. FIG. 6 (with further reference to FIG. 7) illustrates the result of implementing the growth inducing lighting recipe 118, according to a lighting optimization schedule 122. As can be seen, the growth inducing lighting recipe 118 has induced the interior plants of the crop C to grow taller (due to extended stems and stretched leaves) than the exterior plants. Thus, desired crop C growth can be achieved despite implementation of an energy savings target 114. In some examples, a lighting optimization schedule 122 implements the growth inducing lighting recipe 118 during growth inducing intervals 124. In one example, the growth inducing intervals 124 last for thirty minutes at a beginning 128 of a lighting day 126 and at an end 130 of the lighting day 130. During these growth inducing intervals 124, the growth inducing lighting recipe 118 is implemented.

[0062] Outside of the growth inducing intervals 124, the light sources 200 (see FIG. 1) produce local light 202 (see FIG. 1) at a reduced lighting intensity level 204 based on the energy savings target 114. The length and timing of the growth inducing intervals 124 may be adjusted during the growth process. In some cases, the growth inducing intervals 124 may be longer than 30 minutes, such as the entire lighting day 126.

[0063] Once the future date 110 is reached, the system 10 may compare the estimated plant canopy 108 to the actual plant canopy PC growth at the future date 110. The plant growth model 106 may be modified to correct for any error between the estimated plant canopy 108 and the actual plant canopy PC via a feedback mechanism. Once the plant growth model 106 is updated, the system may begin the aforementioned process again to refine and optimize the growth inducing lighting recipe 118.

[0064] FIG. 7 is a schematic illustration of a controller 100 of a system 10 (see FIG. 1) for providing horticultural lighting for a crop C (see FIG. 1) in a horticulture production facility HPF (see FIG. 1). Generally, the controller 100 includes a processor 125, a memory 175, and a transceiver 195.

[0065] The processor 125 is configured to execute a plant growth model 106 to generate an estimated plant canopy 108 at a future date 110. The processor 125 may also be configured to generate other types of data, such as, but not limited to, a light reception map 112, a growth inducing target map 116, a growth lighting recipe 118, and / or a lighting optimization schedule 122.

[0066] The memory 175 is configured to store a wide array of data captured by and / or generated by the system 10. The memory 175 may store imaging data 302 and / or climate data 402 periodically captured between a first date 102 and a second date 104. The memory 175 may also store an estimated plant canopy 108, generated by the processor 125, corresponding to a future date 110.

[0067] The memory 175 may be further configured to store an energy savings target 114. The energy savings target 114 may be received by a user interface of the system. The memory 175 may further store a reduced light intensity level 204 derived from the energy savings target 114, as well as a reduced lighting intensity period 206, and reduced lighting intensity sensor data 304. The reduced lighting intensity sensor data 304 is used to generate a light reception map 112, also stored in the memory 175.

[0068] The memory 175 also stores a growth inducing target map 116 generated based on the estimated plant canopy 108 and the light reception map 112. The memory 175 also stores a growth inducing lighting recipe 118 generated based on the growth inducing target map 116. An optimized R:FR light ratio 120 is incorporated into the growth inducing target map 116.

[0069] The memory 175 also includes a lighting optimization schedule 122 configured to implement the growth inducing lighting recipe 118 in the system 10. The lighting optimization schedule 122 may define one or more growth inducing intervals 124. The lighting optimization schedule may also define a lighting day 126 having a beginning 128 and an end 130.

[0070] The transceiver 195 is configured to wirelessly transmit data between the controller 100 and other aspects of the system 10, such as the sensors 300, 400, 500 (see FIG. 1), the light sources 200 (see FIG. 1), and / or a user interface. In some examples, this data may be transmitted via wired communication where practical.

[0071] FIG. 8 is a flowchart of a method 900 for providing horticulture lighting for a crop in a horticulture production facility, according to various embodiments of the invention. The method 900 includes periodically capturing 902, via one or more imaging sensors and one or more climate sensors, imaging data and climate data between a first date and a second date, wherein the imaging data and the climate data corresponds to a plant canopy of the crop. The method 900 further includes generating 904, via a plant growth model executed by a controller, an estimated plant canopy corresponding to a future date based on the imaging data and the climate data. The method 900 further includes receiving 906, via the controller, a light reception map of the plant canopy receiving a local light at a reduced lighting intensity level. The method 900 further includes generating 908, via the controller, based on the light reception map and the estimated plant canopy, a growth inducing target map corresponding to the future date. The method 900 further includes generating 910, via the controller, based on the growth inducing target map, a growth inducing lighting recipe, wherein the growth inducing lighting recipe includes an optimized red light to far-red light ratio to be applied to the plant canopy between the second date and the future date. The method 900 further includes adjusting 912, via a plurality of light sources, the local light based on the growth inducing lighting recipe.

[0072] All definitions, as defined and used herein, should be understood to control over dictionary definitions, definitions in documents incorporated by reference, and / or ordinary meanings of the defined terms.

[0073] The indefinite articles “a” and “an,” as used herein in the specification and in the claims, unless clearly indicated to the contrary, should be understood to mean “at least one.”

[0074] The phrase “and / or,” as used herein in the specification and in the claims, should be understood to mean “either or both” of the elements so conjoined, i.e., elements that are conjunctively present in some cases and disjunctively present in other cases. Multiple elements listed with “and / or” should be construed in the same fashion, i.e., “one or more” of the elements so conjoined. Other elements can optionally be present other than the elements specifically identified by the “and / or” clause, whether related or unrelated to those elements specifically identified.

[0075] As used herein in the specification and in the claims, “or” should be understood to have the same meaning as “and / or” as defined above. For example, when separating items in a list, “or” or “and / or” shall be interpreted as being inclusive, i.e., the inclusion of at least one, but also including more than one, of a number or list of elements, and, optionally, additional unlisted items. Only terms clearly indicated to the contrary, such as “only one of’ or “exactly one of,” or, when used in the claims, “consisting of,” will refer to the inclusion of exactly one element of a number or list of elements. In general, the term “or” as used herein shall only be interpreted as indicating exclusive alternatives (i.e. “one or the other but not both”) when preceded by terms of exclusivity, such as “either,” “one of,” “only one of,” or “exactly one of.”

[0076] As used herein in the specification and in the claims, the phrase “at least one,” in reference to a list of one or more elements, should be understood to mean at least one element selected from any one or more of the elements in the list of elements, but not necessarily including at least one of each and every element specifically listed within the list of elements and not excluding any combinations of elements in the list of elements. This definition also allows that elements can optionally be present other than the elements specifically identified within the list of elements to which the phrase “at least one” refers, whether related or unrelated to those elements specifically identified.

[0077] It should also be understood that, unless clearly indicated to the contrary, in any methods claimed herein that include more than one step or act, the order of the steps or acts of the method is not necessarily limited to the order in which the steps or acts of the method are recited.

[0078] In the claims, as well as in the specification above, all transitional phrases such as “comprising,” “including,” “carrying,” “having,” “containing,” “involving,” “holding,” “composed of,” and the like are to be understood to be open-ended, i.e., to mean including but not limited to. Only the transitional phrases “consisting of’ and “consisting essentially of’ shall be closed or semi-closed transitional phrases, respectively.

[0079] The above-described examples of the described subject matter can be implemented in any of numerous ways. For example, some aspects can be implemented using hardware, software, or a combination thereof. When any aspect is implemented at least in part in software, the software code can be executed on any suitable processor or collection of processors, whether provided in a single device or computer or distributed among multiple devices / computers.

[0080] The present disclosure can be implemented as a system, a method, and / or a computer program product at any possible technical detail level of integration. The computer program product can include a computer readable storage medium (or media) having computer readable program instructions thereon for causing a processor to carry out aspects of the present disclosure.

[0081] The computer readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device. The computer readable storage medium can be, for example, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. A non- exhaustive list of more specific examples of the computer readable storage medium includes the following: a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanically encoded device such as punch-cards or raised structures in a groove having instructions recorded thereon, and any suitable combination of the foregoing. A computer readable storage medium, as used herein, is not to be construed as being transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media (e.g., light pulses passing through a fiber-optic cable), or electrical signals transmitted through a wire.

[0082] Computer readable program instructions described herein can be downloaded to respective computing / processing devices from a computer readable storage medium or to an external computer or external storage device via a network, for example, the Internet, a local area network, a wide area network and / or a wireless network. The network can comprise copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers and / or edge servers. A network adapter card or network interface in each computing / processing device receives computer readable program instructions from the network and forwards the computer readable program instructions for storage in a computer readable storage medium within the respective computing / processing device.

[0083] Computer readable program instructions for carrying out operations of the present disclosure can be assembler instructions, instruction-set-architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state-setting data, configuration data for integrated circuitry, or either source code or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C++, or the like, and procedural programming languages, such as the “C” programming language or similar programming languages. The computer readable program instructions can execute entirely on the user’s computer, partly on the user's computer, as a stand-alone software package, partly on the user’ s computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computer (for example, through the Internet using an Internet Service Provider). In some examples, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate arrays (FPGA), or programmable logic arrays (PLA) can execute the computer readable program instructions by utilizing state information of the computer readable program instructions to personalize the electronic circuitry, in order to perform aspects of the present disclosure.

[0084] Aspects of the present disclosure are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to examples of the disclosure. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer readable program instructions.

[0085] The computer readable program instructions can be provided to a processor of a, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks. These computer readable program instructions can also be stored in a computer readable storage medium that can direct a computer, a programmable data processing apparatus, and / or other devices to function in a particular manner, such that the computer readable storage medium having instructions stored therein comprises an article of manufacture including instructions which implement aspects of the function / act specified in the flowchart and / or block diagram or blocks.

[0086] The computer readable program instructions can also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus, or other device to produce a computer implemented process, such that the instructions which execute on the computer, other programmable apparatus, or other device implement the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0087] The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various examples of the present disclosure. In this regard, each block in the flowchart or block diagrams can represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the blocks can occur out of the order noted in the Figures. For example, two blocks shown in succession can, in fact, be executed substantially concurrently, or the blocks can sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and / or flowchart illustration, and combinations of blocks in the block diagrams and / or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts or carry out combinations of special purpose hardware and computer instructions. Other implementations are within the scope of the following claims and other claims to which the applicant can be entitled.

[0088] While various examples have been described and illustrated herein, those of ordinary skill in the art will readily envision a variety of other means and / or structures for performing the function and / or obtaining the results and / or one or more of the advantages described herein, and each of such variations and / or modifications is deemed to be within the scope of the examples described herein. More generally, those skilled in the art will readily appreciate that all parameters, dimensions, materials, and configurations described herein are meant to be exemplary and that the actual parameters, dimensions, materials, and / or configurations will depend upon the specific application or applications for which the teachings is / are used. Those skilled in the art will recognize or be able to ascertain using no more than routine experimentation, many equivalents to the specific examples described herein. It is, therefore, to be understood that the foregoing examples are presented by way of example only and that, within the scope of the appended claims and equivalents thereto, examples can be practiced otherwise than as specifically described and claimed. Examples of the present disclosure are directed to each individual feature, system, article, material, kit, and / or method described herein. In addition, any combination of two or more such features, systems, articles, materials, kits, and / or methods, if such features, systems, articles, materials, kits, and / or methods are not mutually inconsistent, is included within the scope of the present disclosure.

Claims

CLAIMS:

1. A system (10) for providing horticulture lighting for a crop (C) in a horticulture production facility (HPF), comprising: a plurality of light sources (200) comprising at least one red light source (200R) and at least one far red-light source (200FR), wherein the plurality of light sources (200) generates local light (202) illuminating at least a portion of a plant canopy (PC) of the crop (C); one or more imaging sensors (300) configured to capture imaging data (302) corresponding to the plant canopy (PC); one or more climate sensors (400) arranged to capture climate data (402) corresponding to the plant canopy (PC); a controller (100) communicatively coupled to the plurality of light sources (200), the one or more imaging sensors (300), and the one or more climate sensors (400), wherein the controller (100) is configured to: periodically capture, via the one or more imaging sensors (300) and the one or more climate sensors (400), the imaging data (302) and the climate data (402) between a first date (102) and a second date (104); generate, via a trained plant growth model (106), an estimated plant canopy (108) corresponding to a future date (110) based on the imaging data (302) and the climate data (402); receive a light reception map (112) of the plant canopy (PC) receiving the local light (202) at a reduced lighting intensity level (204); generate, based on the light reception map (112) and the estimated plant canopy (108), a growth inducing target map (116) corresponding to the future date (110); generate, based on the growth inducing target map (116), a growth inducing lighting recipe (118), wherein the growth inducing lighting recipe (118) includes an optimized red light to far-red light ratio (120) to be applied to the plant canopy (PC) between the second date (104) and the future date (110); and adjust, via the plurality of light sources (200), the local light (202) based on the growth inducing lighting recipe (118).

2. The system (10) of claim 1, wherein the second date (104) is at least seven days after the first date (102).

3. The system (10) of claim 1, wherein the light reception map (112) is generated by: adjusting the local light (202) according to the reduced lighting intensity level (204) for a reduced lighting intensity period (206), wherein the reduced lighting intensity level corresponds to an energy saving target (114); capturing, via the one or more imaging sensors (300) and / or one or more photosynthetically active radiation (PAR) sensors (500), reduced lighting intensity sensor data (304); and generating the light reception map (112) based on the reduced lighting intensity sensor data (304).

4. The system (10) of claim 3, wherein the energy savings target (114) is approximately 20 percent.

5. The system (10) of claim 3, wherein the reduced lighting intensity period (206) is approximately 15 seconds.

6. The system (10) of claim 1, wherein at least one of the one or more imaging sensors (300) is a red-green-blue (RGB) camera, a thermal camera, and / or an infrared sensor.

7. The system (10) of claim 1, wherein at least one of the one or more climate sensors (400) is a temperature sensor and / or a humidity sensor.

8. The system (10) of claim 1, wherein the local light (202) is adjusted based on the growth inducing lighting recipe (120) according to one or more growth inducing intervals (124) of a lighting optimization schedule (122).

9. The system (10) of claim 8, wherein the lighting optimization schedule (122) adjusts the local light (202) according to the reduced lighting intensity level (204) outside of the one or more growth inducing intervals (124).

10. The system (10) of claim 8, wherein the one or more growth inducing intervals(118) occur for thirty minutes at a beginning (128) of a lighting day (126) and for thirty minutes immediately prior to an end (130) of the lighting day (126).

11. The system (10) of claim 1, wherein the trained plant growth model (106) is a recurrent neural network (RNN) model corresponding to both the horticultural production facility (HPF) and the crop (C).

12. The system (10) of claim 1, wherein the trained plant growth model (106) is trained based on a plurality of training pairs (132) of historical imaging data (134) and historical climate data (136) corresponding to both the horticultural production facility (HPF) and the crop (C).

13. The system (10) of claim 12, wherein each of the plurality of training pairs (132) corresponds to both a calendar time stamp (138) and a plant age time stamp (142).

14. The system (10) of claim 1, wherein the estimated plant canopy (108) and the growth inducing target map (116) correspond to a two-dimensional plane (2DP) or a three- dimensional volume (3DV) of the plant canopy (PC).

15. A method (900) for providing horticulture lighting for a crop in a horticulture production facility, comprising: periodically capturing (902), via one or more imaging sensors and one or more climate sensors, imaging data and climate data between a first date and a second date, wherein the imaging data and the climate data corresponds to a plant canopy of the crop; generating (904), via a trained plant growth model executed by a controller, an estimated plant canopy corresponding to a future date based on the imaging data and the climate data; receiving (906), via the controller, a light reception map of the plant canopy receiving a local light at a reduced lighting intensity level; generating (908), via the controller, based on the light reception map and the estimated plant canopy, a growth inducing target map corresponding to the future date;generating (910), via the controller, based on the growth inducing target map, a growth inducing lighting recipe, wherein the growth inducing lighting recipe includes an optimized red light to far-red light ratio to be applied to the plant canopy between the second date and the future date; and adjusting (912), via a plurality of light sources, the local light based on the growth inducing lighting recipe.

Images