Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claims 1-13 are pending, of which claims 1 and 12 are independent claims.
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55 for Application No. KR 10-2022-032648 filed on October 14, 2022 and KR 10-2023-0067404 filed on May 25, 2023.
Information Disclosure Statement
The references cited in the information disclosure statements (IDS) submitted on October 12, 2023 and June 3, 2025 have been considered by the examiner.
Claim Objections
The following claims are objected to for lack of antecedent support or for redundancies. The Examiner recommends the following changes:
Claim 1, line 2, replace “the environment” with “an environment”.
Claim 1, line 6, replace “the start” with “a start”.
Claim 1, line 13, replace “the growth” with “a growth”.
Claim 10, line 2, replace “the temperature” with “a temperature”.
Claim 10, line 2, replace “the humidity” with “a humidity”.
Claim 10, line 3, replace “the illuminance” with “an illuminance”.
Claim 12, line 1, replace “the environment” with “an environment”.
Claim 12, line 5, replace “the start” with “a start”.
Appropriate correction is respectfully requested.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-13 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception without significantly more.
Independent claim 1 recites, “...calculating, by the cultivation server, the growth time of the roughage based on the request for the start of growing the roughage and the alarm about the start of harvesting the roughage; determining, by the cultivation server, a cultivation phase in which the roughage is based on the growth time; ... calculating, by the cultivation server, a cultivation environment adjustment value for the roughage based on the environmental state value and the environmental target;…”
Under its broadest reasonable interpretation, if a claim limitation covers performance that can be executed in the human mind, but for the recitation of generic electronic devices or generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Under their broadest reasonable interpretation and based on the description provided in the Specification, such as paragraphs [0066]-[0086], for instance, the calculating limitations and the determine limitation are mental processes that can be performed through observation, evaluation and judgement. In the alternative, as described in at least the referred portions of the specification, the calculating limitations are processes that entails purely mathematical relationships, mathematical formulas or equations, and mathematical calculations. Therefore, a person may perform, through observation, evaluation and judgement, the features enunciated above.
Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, claim 1 recites the additional elements of, “receiving, by the cultivation server, cultivation information including a cultivation environment mode, a grower's manual environmental target, a request for a start of growing the roughage, and an alarm about the start of harvesting the roughage from the cultivator console; receiving, by the cultivation server, information about an environmental state of the cultivation space and information about an operating state of the cultivation apparatus from the cultivation apparatus; generating, by the cultivation server, an environmental state value based on the information about the environmental state; … generating, by the cultivation server, an environmental target for the roughage based on the cultivation phase; … transmitting, by the cultivation server, the cultivation environment adjustment value to the cultivation apparatus; and adjusting, by the cultivation apparatus, the environment of the cultivation space based on the cultivation environment adjustment value”.
The receiving limitations are insignificant extra-solution activities under MPEP 2106.05(g), without imposing meaningful limits. The limitation amounts to necessary data gathering. (i.e., all uses of the recited judicial exception require such data gathering or data output). See Mayo, 566 U.S. at 79, 101 USPQ2d at 1968. In accord with MPEP 2105(g), “An example of pre-solution activity is a step of gathering data for use in a claimed process, e.g., a step of obtaining information about credit card transactions, which is recited as part of a claimed process of analyzing and manipulating the gathered information by a series of steps in order to detect whether the transactions were fraudulent.”
The generating limitations of the environmental state value and an environmental target and the transmitting limitations are post-solution activity that does not integrate the abstract idea into a practical application and it is an insignificant extra-solution activity to the judicial exception MPEP 2106.05(g).
The adjusting limitation amounts to no more than mere instructions to apply an exception on a cultivation apparatus because it amounts to no more than an idea of a solution or outcome and does not recite details of how a solution to a problem is accomplished; see MPEP 2106.05(f)(1)- “The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words “apply it”. See Electric Power Group, LLC v. Alstom, S.A., 830 F.3d 1350, 1356, 119 USPQ2d 1739, 1743-44 (Fed. Cir. 2016); Intellectual Ventures I v. Symantec, 838 F.3d 1307, 1327, 120 USPQ2d 1353, 1366 (Fed. Cir. 2016); Internet Patents Corp. v. Active Network, Inc., 790 F.3d 1343, 1348, 115 USPQ2d 1414, 1417 (Fed. Cir. 2015).”
The additional features including “a cultivator console” and “a cultivation server”, as recited in the claim that are configured to carry out the additional and abstract idea limitations may be tools that are used as recited in claim 1, but recited so generically that they represent no more than mere instructions “to apply” the judicial exceptions on or using generic electronic or computer components. Implementing an abstract idea on generic electronic or computer components as tools to perform an abstract idea is not indicative of integration into a practical application.
In view of the foregoing, the additional limitations, individually or combined, are not sufficient to demonstrate integration of a judicial exception into a practical application.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
The receive limitations are functions that are recognized as well-understood, routine, and conventional and amount to no more than insignificant pre-activity of receiving data, as demonstrated in US Patent Publication No. 2023/0143014 A1 to Nguyen et al. (Paragraphs [0034], [0035], and [0040]); US Patent Publication No. 2023/0177622 A1 to Bull et al. (Paragraphs [0062], [0068], [0081], and [0082]); and US Patent Publication No. 2017/0161560 A1 to Itzhaky et al. (Paragraphs [0033]-[0034] and [0051]) .
The generating limitations of the environmental state value and an environmental target, the transmitting limitations, and the adjusting limitation amount to no more than mere instructions to apply an exception on a computer, such as a cultivation server or a cultivation apparatus, because they amount to no more than an idea of a solution or outcome and does not recite details of how a solution to a problem is accomplished; see MPEP 2106.05(f)(1)- “The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words “apply it”. See Electric Power Group, LLC v. Alstom, S.A., 830 F.3d 1350, 1356, 119 USPQ2d 1739, 1743-44 (Fed. Cir. 2016); Intellectual Ventures I v. Symantec, 838 F.3d 1307, 1327, 120 USPQ2d 1353, 1366 (Fed. Cir. 2016); Internet Patents Corp. v. Active Network, Inc., 790 F.3d 1343, 1348, 115 USPQ2d 1414, 1417 (Fed. Cir. 2015).”
The additional features including “a cultivator console” and “a cultivation server”, as recited in the claim that are configured to carry out the additional and abstract idea limitations may be tools that are used for the functions recited in claim 1, but recited so generically that they represent no more than mere instructions “to apply” the judicial exceptions on or using a generic electronic or computer component. See MPEP 2106.05(f) Implementing an abstract idea on generic electronic or computer components as tools to perform an abstract idea does not amount to significantly more. See Elec. Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1355 (Fed. Cir. 2016) (“Nothing in the claims, understood in light of the specification, requires anything other than off-the-shelf, conventional computer, network, and display technology for gathering, sending, and presenting the desired information.”)
Therefore, the additional claimed features, individually or combined, do not amount to significantly more and the claim is not patent eligible.
Regarding claim 2, this claim is further defining the cultivation space recited in claim 1 without integrating the abstract ideas identified in claim 1 into a practical application and without amounting to significantly more. Thus, claim 2 is not patent eligible.
Regarding claim 3, this claim recites, in part, “storing, by the cultivation server, a cultivation environment data set including a current time, the growth time, the cultivation phase, the environmental target, and the environmental state value for each cultivation space”, which does not integrate the abstract idea into a practical application and is an insignificant extra-solution activity to the judicial exceptions, and is merely nominal or tangential additions to the claim. See MPEP 2106.05(g). In addition, this limitation does not amount to significantly more because it is an example of an activity that the courts have found to be well-understood, routine, and conventional activities when claimed in a generic manner. See Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93 (storing and retrieving information in memory). Claim 3 further recites “transmitting, by the cultivation server, the information about the operating state and the cultivation environment data set corresponding to the cultivation information to the cultivator console; receiving, by the cultivator console, the cultivation environment data set corresponding to cultivation information and outputting information on the environmental state of the cultivation space to the user interface; and receiving, by the cultivator console, a command for a remote cultivation control from a grower.” For similar reasons as those explained in claim 1, the transmitting limitation and the receiving limitations are not functions that are integrating the judicial exceptions into a practical application and do not amount to significantly more. Thus, claim 3 is not patent eligible.
Regarding claims 4 and 5, these claims are further defining the abstract idea of calculating as recited in independent claim 1. There are no additional limitations in the claim to apply, rely on, or use the judicial exception in a manner that would impose a meaningful limitation on the judicial exception. The claims are not more than a drafting effort designed to monopolize the exception. The claims also do not include additional elements that integrate the judicial exception into a practical application and that would be sufficient to amount to significantly more than the judicial exception. Thus, claims 4 and 5 are not patent eligible.
Regarding claims 6 and 7, these claims are further defining the abstract idea of determining as recited in independent claim 1. There are no additional limitations in the claim to apply, rely on, or use the judicial exception in a manner that would impose a meaningful limitation on the judicial exception. The claims are not more than a drafting effort designed to monopolize the exception. The claims also do not include additional elements that integrate the judicial exceptions into a practical application and that would be sufficient to amount to significantly more than the judicial exceptions. Thus, claims 6 and 7 are not patent eligible.
Regarding claims 8 and 9, claim 8 is further defining the generating limitation of independent claim 1 and claim 9 is further defining the receiving limitation of independent claim 1. However, there are no additional limitations in the claim to apply, rely on, or use the judicial exception in a manner that would impose a meaningful limitation on the judicial exception. The claims also do not include additional elements that integrate the judicial exceptions into a practical application and that would be sufficient to amount to significantly more than the judicial exceptions. Thus, claims 8 and 9 are not patent eligible.
Regarding claims 10 and 11, these claims are further defining the information recited in claim 1 without integrating the abstract ideas identified in claim 1 into a practical application and without amounting to significantly more. The claims also do not include additional elements that integrate the judicial exception into a practical application and that would be sufficient to amount to significantly more than the judicial exception. Thus, claims 10 and 11 are not patent eligible.
The functions of independent claim 12 are implemented by similar functions as those of the method of claim 1 with substantially the same limitations. Therefore, the rejection applied to independent claim 1 above also applies to independent claim 12. In addition, independent claim 12 recites “store a cultivation environment data set including a current time, the growth time, the cultivation phase, the environment target, and the environmental state value for each cultivation space”. However, this storing function does not integrate the abstract idea into a practical application and is an insignificant extra-solution activity to the judicial exceptions, and is merely nominal or tangential additions to the claim. See MPEP 2106.05(g). In addition, this limitation does not amount to significantly more because it is an example of an activity that the courts have found to be well-understood, routine, and conventional activities when claimed in a generic manner. See Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93 (storing and retrieving information in memory). In view of the foregoing, independent claim 12 is not deemed patent eligible.
The functions of claim 13 is implemented by similar functions as those of the method of claim 2 with substantially the same limitations. Therefore, the rejections applied to claim 2 above also applies to claim 13. Claim 3 is not deemed patent eligible.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1, 3, 9, 10, and 12 are rejected under 35 U.S.C. 103 as being unpatentable over Nguyen et al. (US Patent Publication No. 2023/0143014 A1) (“Nguyen”) in view of Bull et al. (US Patent Publication No. 2023/0177622 A1) (“Bull”).
Regarding independent claim 1, Nguyen teaches:
A method for cultivating roughage based on a cultivator console and a cultivation server, with a cultivation apparatus for controlling the environment of a cultivation space for cultivating the roughage, the method comprising: Nguyen: Paragraph [0037] (“An exemplary control unit may include a processor and memory and may be implemented in a cloud computing environment which may be remotely operable, adjustable, or monitorable by a user.”) Nguyen: Paragraph [0074] (“The AI may implement computer vision and/or other sensors to analyze plants in the various phases. In or after the greenhouse phase, the AI may control or operate a robotic system for harvesting the plants from the greenhouse(s) they are disposed in in the greenhouse phase. Thus, it may be contemplated that an exemplary embodiment is fully autonomous. In a fully autonomous exemplary embodiment, seedlings may be planted in a germination phase by a robot, and then may be moved to each of the subsequent phases using additional robotics which are autonomously controlled by the AI. Robotics may also be used for propagation of plants from existing material instead of germination. A further embodiment may harvest and prepare the plants for shipping using the robotics and AI. It may be contemplated that the AI is configured to receive instructions from an external machine, such as a web server, and to then operate the robotics to plant the seeds or seedlings based on the received instructions. The instructions may include a plant type and quantity, a desired size, a desired age, and a shipping address, for example. The AI system may then plant and grow one or more plants according to the instructions.”) Nguyen: Paragraph [0067] (“Each of the greenhouse zones may be monitored by their own individual sensors. Environmental parameters may be autonomously controlled by their own individual controllers which may drive various systems. In an exemplary embodiment, the AI may monitor the greenhouse zone and autonomously control the environmental parameters. In one embodiment, the controllers may be, for example, programmable logic controllers.”) [The plant type reads on “roughage”.]
…
receiving, by the cultivation server, information about an environmental state of the cultivation space and information about an operating state of the cultivation apparatus from the cultivation apparatus; Nguyen: Paragraph [0034] (“A method for optimizing plant growth in a hybrid growing environment may be shown and described. Growth may be optimized using, for example, a control system. A control unit may control various parameters or variables based on an identification of multiple dependent variables. Dependent variables may include, for example, plant weight, plant leaf growth, root growth, plant diameter, plant health, an identification of pests, mold, mildew, or rejected plants, growth cycle DLI, vapor pressure deficit (VPD) within a specified tolerance range, or the temperature within a specified tolerance range, electricity usage, watering periodicity, the time in an environment or phase, the nutrient concentration, or the soil moisture content. Rate of development, and the quality and presence of abiotic or biotic-induced abnormalities may also be measured. Independent variables may include, for example, dry bulb temperature, wet bulb temperature, relative humidity, plant surface temperature, vapor pressure deficit (VPD), the lighting intensity and/or period, light spectrum wavelengths, amount of nutrients applied or retained by a plant, the CO2 concentration, water temperature, water pH, water conductivity, amount of dissolved oxygen, the amount or presence of pesticides, water usage, CO2 assimilation, chlorophyll fluorescence, chlorophyll concentration, and microbial levels in nutrient solutions.”) Nguyen: Paragraph [0035] (“Growing conditions and growing duration may be changed based on target dependent variables in the growing process. The independent variables may be adjusted based on progress and the targeted durations. The targeted duration may be dynamically adjusted based on a real-time growing stage of the plants. Variables may be adjusted based on a prediction of the difference in the variables in future environments for the plants. For example, a phase, such as a nursery phase or a greenhouse phase, may include associated target dependent variables. An embodiment may adjust the independent variables to reach the target dependent variables within that phase or in anticipation of a subsequent phase or phases... Additionally, it may be contemplated that some days, months, or seasons may provide more natural light from the sun. Thus, during the time periods where more natural light can be obtained from the sun, variables such as the artificial lighting level may be adjusted to compensate for the extra sun. For example, the artificial lighting level may be reduced in order to reduce electricity usage in anticipation of an abundance of natural light at a future time.”) Nguyen: Paragraph [0040] (“For example, an exemplary embodiment may initially define an optimal growing temperature for a plant varietal. Then, in some embodiments, the control unit may alter the temperature to slightly above and/or slightly below the optimal growing temperature for that varietal, or for a portion of the total plants of that varietal.”) Nguyen: Paragraph [0009] (“… during the greenhouse phase, the plants receive sunlight, and or supplementary lighting; …”) [The environment information, such as, time periods reads on “receiving… information about an environmental state of the cultivation space”. The information such as the adjusted artificial lighting level and altered temperature by the control unit read on “information about an operating state of the cultivation apparatus”]
generating, by the cultivation server, an environmental state value based on the information about the environmental state; Nguyen: Paragraphs [0034], [0035], and [0040] [As described above.] [The identification of the dependent variables read on “generating…an environmental state value based on the information about the environmental state”.]
calculating, by the cultivation server, the growth time of the roughage based on the request for the start of growing the roughage and the alarm about the start of harvesting the roughage; Nguyen: Paragraph [0038] (“An intensity or a magnitude of the independent variables may be altered according to growth progress or real-time measured dependent variables. Independent variables may be altered in order to obtain a desired growth time or in order to alter the date at which the plants may be harvested.”) Nguyen: Paragraph [0039] (“The improved efficiency and optimization may be used to determine target weight and height, to efficiently reach a target harvest date, and to maximize a success rate of survivability and achieving the target. The optimization may occur in each phase, including one or more nursery phases and greenhouse phase. An artificial intelligence or AI program may be implemented to control and identify how to optimize crop growth.”)
determining, by the cultivation server, a cultivation phase in which the roughage is based on the growth time; Nguyen: Paragraph [0008] (“For example, an exemplary embodiment may identify a plant with a plant diameter that is below an optimal level, and may thus determine that the identified plant requires additional nutrients, water, and/or light based on the measurement and the plant type. Historical plant records and data may be recorded and referenced to identify optimal dependent variables for each plant at each stage of growth. Each stage or phase may refer to a growing environment, a time spent in a growing environment, or a time spent since germination, for example.”) Nguyen: Paragraph [0040] (“An exemplary control unit may track and control the various independent and dependent variables in real time. For example, if an exemplary embodiment determines that a specific plant is growing at a slower rate or is smaller than average at a given time, it may determine that more water or nutrients are needed and may then direct a boom or other source to water or provide nutrients to that plant. Further, an exemplary embodiment may track the association between the independent and dependent variables over time for each plant varietal in a historical plant database.”) [A stage of growth of each plant reads on “determining…a cultivation phase” and the time spent since germination reads on “the growth time”.]
generating, by the cultivation server, an environmental target for the roughage based on the cultivation phase; Nguyen: Paragraph [0040] (“An exemplary control unit may track and control the various independent and dependent variables in real time. For example, if an exemplary embodiment determines that a specific plant is growing at a slower rate or is smaller than average at a given time, it may determine that more water or nutrients are needed and may then direct a boom or other source to water or provide nutrients to that plant. Further, an exemplary embodiment may track the association between the independent and dependent variables over time for each plant varietal in a historical plant database. Measurements may be compared to the historical plant data in order to identify optimal independent variable settings to obtain a targeted size, weight, shape, or harvest date. An exemplary embodiment may be configured to slightly alter various independent variables in order to identify an optimal value for each variable. For example, an exemplary embodiment may initially define an optimal growing temperature for a plant varietal. Then, in some embodiments, the control unit may alter the temperature to slightly above and/or slightly below the optimal growing temperature for that varietal, or for a portion of the total plants of that varietal.”) Nguyen: Paragraph [0041] (“… the control unit may then implement the slightly higher temperature in order to expedite the growth of that varietal in future growth cycles. Alternatively, if an exemplary embodiment determines that the slightly lower temperature slows down the growth, that lower temperature may be implemented when the market demand for the plant is low and the target harvest date is delayed. It may be contemplated that any variable, or a combination of variables, may be similarly optimized, including, but not limited to, plant size, survivability, electricity usage, and the like.”) [Determining independent variables based on factors such as progress in the stage of growth and the target duration reads on “generating… an environmental target for the roughage based on the cultivation phase”.]
calculating, by the cultivation server, a cultivation environment adjustment value for the roughage based on the environmental state value and the environmental target; Nguyen: Paragraphs [0040] and [0041] [As described above.] [The comparing of the historical plant data with the measurements to optimize the independent variable settings reads on “calculating… a cultivation environment adjustment value for the roughage based on the environmental state value and the environmental target”.]
transmitting, by the cultivation server, the cultivation environment adjustment value to the cultivation apparatus; and Nguyen: Paragraphs [0040] and [0041] [As described above.]
adjusting, by the cultivation apparatus, the environment of the cultivation space based on the cultivation environment adjustment value. Nguyen: Paragraphs [0040] and [0041] [As described above.] Nguyen: Paragraph [0043] (“The various phases of the cycle may be customized for different species and or varietals and may be adjusted over time. The phases may be customized for optimal time on a final hydroponic system or phase, which may be a natural or artificial system and may include a greenhouse, a deep-water agriculture location, a body of water or any combination thereof. The number of phases, including nursery phases and the specific indexing may all be adjusted as necessary to optimize the process. Different species or varietals may use any number of nurseries and associated nursery phases.”) [Dynamically adjusting independent variables based on real time growing stage of the plants reads on “adjusting…the environment of the cultivation space based on the cultivation environment adjustment value”.]
Although Nguyen lists a number of dependent and independent variables processed during plant cultivation, the reference does not teach that a server or a controller receives the particular cultivation information recited. However, Bull describes a method for optimizing plant growth in a hybrid growing environment may implement artificial intelligence to measure and alter plant biometrics. Bull teaches:
receiving, by the cultivation server, cultivation information including a cultivation environment mode, a grower's manual environmental target, Bull: Paragraph [0081] (“…a mobile computer application 200 comprises account, fields, data ingestion, sharing instructions 202 which are programmed to receive, translate, and ingest field data from third party systems via manual upload or APIs. Data types may include field boundaries, yield maps, as-planted maps, soil test results, as-applied maps, and/or management zones, among others.”) Bull: Paragraph [0082] (“In one embodiment, seeds and planting instructions 208 are programmed to provide tools for seed selection, hybrid placement, and script creation, including variable rate (VR) script creation, based upon scientific models and empirical data. This enables growers to maximize yield or return on investment through optimized seed purchase, placement and population.”) a request for a start of growing the roughage, and an alarm about the start of harvesting the roughage from the cultivator console; Bull: Paragraph [0062] (“Presentation layer 134 may be programmed or configured to generate a graphical user interface (GUI) to be displayed on field manager computing device 104, cab computer 115 or other computers that are coupled to the system 130 through the network 109. The GUI may comprise controls for inputting data to be sent to agricultural intelligence computer system 130, generating requests for models and/or recommendations, and/or displaying recommendations, notifications, models, and other field data.”) Bull: Paragraph [0059] (“Agricultural intelligence computer system 130 is programmed or configured to receive field data 106 from field manager computing device 104, external data 110 from external data server computer 108, and sensor data from remote sensor 112. Agricultural intelligence computer system 130 may be further configured to host, use or execute one or more computer programs, other software elements, digitally programmed logic such as FPGAs or ASICs, or any combination thereof to perform translation and storage of data values, construction of digital models of one or more crops on one or more fields, generation of recommendations and notifications, and generation and sending of scripts to application controller 114,…”) Bull: Paragraph [0068] (“FIG. 5 depicts an example embodiment of a timeline view for data entry. Using the display depicted in FIG. 5, a user computer can input a selection of a particular field and a particular date for the addition of event. Events depicted at the top of the timeline may include Nitrogen, Planting, Practices, and Soil. To add a nitrogen application event, a user computer may provide input to select the nitrogen tab. The user computer may then select a location on the timeline for a particular field in order to indicate an application of nitrogen on the selected field. In response to receiving a selection of a location on the timeline for a particular field, the data manager may display a data entry overlay, allowing the user computer to input data pertaining to nitrogen applications, planting procedures, soil application, tillage procedures, irrigation practices, or other information relating to the particular field.”) Bull: Paragraph [0054] (“Examples of field data 106 include (a) identification data (for example, acreage, field name, field identifiers, geographic identifiers, boundary identifiers, crop identifiers, and any other suitable data that may be used to identify farm land, such as a common land unit (CLU), lot and block number, a parcel number, geographic coordinates and boundaries, Farm Serial Number (FSN), farm number, tract number, field number, section, township, and/or range), (b) harvest data (for example, crop type, crop variety, … harvest date, Actual Production History (APH), expected yield, yield, crop price, crop revenue, grain moisture, tillage practice, and previous growing season information)… [The input for a particular date to plant, such as a corn plant, reads on “a request to start growing roughage”. The notification associated with the field data including harvest reads on “alarm about the start of harvesting the roughage”.]
Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having the teachings of Nguyen and Bull before them, to receiving, by the cultivation server, cultivation information including a cultivation environment mode, a grower's manual environmental target, a request for a start of growing the roughage, and an alarm about the start of harvesting the roughage from the cultivator console because the references are in the same field of endeavor as the claimed invention and they are focused on cultivating plants including corn (roughage).
One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to do this modification so that growing conditions and growing duration may be changed based on target dependent variables in the growing process and reduce risk of crop failure, improve product flexibility, and improve mechanical dependence. Bull Paragraphs [0003]-[0004].
Regarding claim 3, Nguyen and Bull teach all the claimed features of claim 1, from which claim 3 depends. Nguyen further teaches:
The method of claim 1, further comprising: storing, by the cultivation server, a cultivation environment data set including a current time, the growth time, the cultivation phase, the environmental target, and the environmental state value for each cultivation space; Nguyen: Paragraph [0034] and [0035] [As described above.] Nguyen: Abstract (“A historical database may store data regarding the variables and may be referenced and updated by an exemplary embodiment.”) Nguyen: Paragraph [0007] (“Growing conditions and growing duration may be changed based on target dependent variables in the growing process.”) Nguyen: Paragraph [0041] (“Plants growing under the altered conditions may be monitored and their growth data may be stored. If, for example, the slightly higher temperature increases the growth rate, that information may be stored. Finally, the control unit may then implement the slightly higher temperature in order to expedite the growth of that varietal in future growth cycles. Alternatively, if an exemplary embodiment determines that the slightly lower temperature slows down the growth, that lower temperature may be implemented when the market demand for the plant is low and the target harvest date is delayed. It may be contemplated that any variable, or a combination of variables, may be similarly optimized, including, but not limited to, plant size, survivability, electricity usage, and the like. Further, the control unit may optimize different variables according to different phases. For example, the root size or length may be optimized in a nursery phase, while the leaf size may be optimized in the greenhouse phase.”) Nguyen: Paragraph [0086] (“As independent variables are adjusted, an exemplary control unit may record and monitor dependent variables to identify a result or effect of the adjustment, and the data model may be updated dynamically and autonomously. An exemplary embodiment may store one or more control data models.”)
transmitting, by the cultivation server, the information about the operating state and the cultivation environment data set corresponding to the cultivation information to the cultivator console; receiving, by the cultivator console, the cultivation environment data set corresponding to cultivation information and … Nguyen: Paragraphs [0034], [0035], [0067], and [0074] [As described in claim 1.] Nguyen: Paragraphs [0047] and [0086] [As described above.]
…
receiving, by the cultivator console, a command for a remote cultivation control from a grower. Nguyen: Paragraph [0037] (“An exemplary control unit may include a processor and memory and may be implemented in a cloud computing environment which may be remotely operable, adjustable, or monitorable by a user.”)
Nguyen does not expressly describe outputting information on the environmental state of the cultivation space to the user interface. However, Bull teaches:
… outputting information on the environmental state of the cultivation space to the user interface; and… Bull: Paragraph [0065] (“In an example embodiment, the agricultural intelligence computer system 130 is programmed to generate and cause displaying a graphical user interface comprising a data manager for data input. After one or more fields have been identified using the methods described above, the data manager may provide one or more graphical user interface widgets which when selected can identify changes to the field, soil, crops, tillage, or nutrient practices. The data manager may include a timeline view, a spreadsheet view, and/or one or more editable programs.”) Bull: Paragraph [0064] (“… the user may be prompted via one or more user interfaces on the user device (served by the agricultural intelligence computer system) to input such information. In an example embodiment, the user may specify identification data by accessing a map on the user device (served by the agricultural intelligence computer system) and selecting specific CLUs that have been graphically shown on the map. In an alternative embodiment, the user 102 may specify identification data by accessing a map on the user device (served by the agricultural intelligence computer system 130) and drawing boundaries of the field over the map. Such CLU selection or map drawings represent geographic identifiers. In alternative embodiments, the user may specify identification data by accessing field identification data (provided as shape files or in a similar format) from the U. S. Department of Agriculture Farm Service Agency or other source via the user device and providing such field identification data to the agricultural intelligence computer system.”)
The motivation to combine Nguyen and Bull as provided in independent claim 1 is incorporated herein.
Regarding claim 9, Nguyen and Bull teach all the claimed features of claim 3, from which claim 9 depends. Bull further teaches:
The method of claim 3, wherein the receiving of the command for the remote cultivation control include receiving, by the cultivator console, the cultivation environment mode, the grower’s environmental target, the request for the start of growing the roughage, and the alarm about the start of harvesting the roughage from the grower who monitors the environmental state of the cultivation space. Bull: Paragraphs [0054], [0059], [0062], [0068], [0081], and [0082] [As described in claim 1.]
The motivation to combine Nguyen and Bull as provided in independent claim 1 is incorporated herein.
Regarding claim 10, Nguyen and Bull teach all the claimed features of claim 1, from which claim 10 depends. Nguyen further teaches:
The method of claim 1, wherein the information about the environmental state includes information about at least one of the temperature inside the cultivation space, the humidity inside the cultivation space, the illuminance inside the cultivation space, or whether a nutrient solution supplied to the cultivation tray disposed in the cultivation space leaks. Nguyen: Paragraph [0015] (“Different plants may be grown in different nurseries or greenhouses, and the system may optimize each plant's environmental parameters individually, since some plants may require or flourish under different conditions than others…LIDAR (light detection and ranging) may be implemented in order to determine factors such as moisture content, size of the plant, diseases, pathogens, stress, and even pest detection.”) Nguyen: Paragraph [0035] (“For example, a phase, such as a nursery phase or a greenhouse phase, may include associated target dependent variables.”) Nguyen: Paragraph [0034] (“Dependent variables may include, for example, plant weight, plant leaf growth, root growth, plant diameter, plant health, an identification of pests, mold, mildew, or rejected plants, growth cycle DLI, vapor pressure deficit (VPD) within a specified tolerance range, or the temperature within a specified tolerance range, electricity usage, watering periodicity, the time in an environment or phase, the nutrient concentration, or the soil moisture content.”)
Regarding independent claim 12, Nguyen teaches:
A system for cultivating roughage having a cultivation apparatus for controlling the environment of a cultivation space for cultivating the roughage, the system comprising: Nguyen: Paragraph [0037] (“An exemplary control unit may include a processor and memory and may be implemented in a cloud computing environment which may be remotely operable, adjustable, or monitorable by a user.”) Nguyen: Paragraph [0074] (“It may be contemplated that the AI is configured to receive instructions from an external machine, such as a web server, and to then operate the robotics to plant the seeds or seedlings based on the received instructions. The instructions may include a plant type and quantity, a desired size, a desired age, and a shipping address, for example. The AI system may then plant and grow one or more plants according to the instructions.”) Nguyen: Paragraph [0067] (“Each of the greenhouse zones may be monitored by their own individual sensors. Environmental parameters may be autonomously controlled by their own individual controllers which may drive various systems. In an exemplary embodiment, the AI may monitor the greenhouse zone and autonomously control the environmental parameters. In one embodiment, the controllers may be, for example, programmable logic controllers.”) [The plant type reads on “roughage”.]
a cultivator console Nguyen: Paragraphs [0037], [0074], and [0067] …
a cultivation server configured to: receive the cultivation information from the cultivator console; receive information about the environmental state of the cultivation space and information about operating state of the cultivation apparatus from the cultivation apparatus; Nguyen: Paragraph [0034] (“A method for optimizing plant growth in a hybrid growing environment may be shown and described. Growth may be optimized using, for example, a control system. A control unit may control various parameters or variables based on an identification of multiple dependent variables. Dependent variables may include, for example, plant weight, plant leaf growth, root growth, plant diameter, plant health, an identification of pests, mold, mildew, or rejected plants, growth cycle DLI, vapor pressure deficit (VPD) within a specified tolerance range, or the temperature within a specified tolerance range, electricity usage, watering periodicity, the time in an environment or phase, the nutrient concentration, or the soil moisture content. Rate of development, and the quality and presence of abiotic or biotic-induced abnormalities may also be measured. Independent variables may include, for example, dry bulb temperature, wet bulb temperature, relative humidity, plant surface temperature, vapor pressure deficit (VPD), the lighting intensity and/or period, light spectrum wavelengths, amount of nutrients applied or retained by a plant, the CO2 concentration, water temperature, water pH, water conductivity, amount of dissolved oxygen, the amount or presence of pesticides, water usage, CO2 assimilation, chlorophyll fluorescence, chlorophyll concentration, and microbial levels in nutrient solutions.”) Nguyen: Paragraph [0035] (“Growing conditions and growing duration may be changed based on target dependent variables in the growing process. The independent variables may be adjusted based on progress and the targeted durations. The targeted duration may be dynamically adjusted based on a real-time growing stage of the plants. Variables may be adjusted based on a prediction of the difference in the variables in future environments for the plants. For example, a phase, such as a nursery phase or a greenhouse phase, may include associated target dependent variables. An embodiment may adjust the independent variables to reach the target dependent variables within that phase or in anticipation of a subsequent phase or phases... Additionally, it may be contemplated that some days, months, or seasons may provide more natural light from the sun. Thus, during the time periods where more natural light can be obtained from the sun, variables such as the artificial lighting level may be adjusted to compensate for the extra sun. For example, the artificial lighting level may be reduced in order to reduce electricity usage in anticipation of an abundance of natural light at a future time.”) Nguyen: Paragraph [0040] (“For example, an exemplary embodiment may initially define an optimal growing temperature for a plant varietal. Then, in some embodiments, the control unit may alter the temperature to slightly above and/or slightly below the optimal growing temperature for that varietal, or for a portion of the total plants of that varietal.”) Nguyen: Paragraph [0009] (“… during the greenhouse phase, the plants receive sunlight, and or supplementary lighting; …”) [The environment information, such as, time periods reads on “receive information about an environmental state of the cultivation space”. The information such as the adjusted artificial lighting level and altered temperature by the control unit read on “information about an operating state of the cultivation apparatus”]
generate an environmental state value based on the information about the environmental state; Nguyen: Paragraphs [0034], [0035], and [0040] [As described above.] [The identification of the dependent variables read on “generate an environmental state value based on the information about the environmental state”.]
calculate a growth time of the roughage based on the request for the start of growing the roughage and the alarm about the start of harvesting the roughage; Nguyen: Paragraph [0038] (“An intensity or a magnitude of the independent variables may be altered according to growth progress or real-time measured dependent variables. Independent variables may be altered in order to obtain a desired growth time or in order to alter the date at which the plants may be harvested.”) Nguyen: Paragraph [0039] (“The improved efficiency and optimization may be used to determine target weight and height, to efficiently reach a target harvest date, and to maximize a success rate of survivability and achieving the target. The optimization may occur in each phase, including one or more nursery phases and greenhouse phase. An artificial intelligence or AI program may be implemented to control and identify how to optimize crop growth.”)
determine a cultivation phase in which the roughage is based on the growth time; Nguyen: Paragraph [0008] (“For example, an exemplary embodiment may identify a plant with a plant diameter that is below an optimal level, and may thus determine that the identified plant requires additional nutrients, water, and/or light based on the measurement and the plant type. Historical plant records and data may be recorded and referenced to identify optimal dependent variables for each plant at each stage of growth. Each stage or phase may refer to a growing environment, a time spent in a growing environment, or a time spent since germination, for example.”) Nguyen: Paragraph [0040] (“An exemplary control unit may track and control the various independent and dependent variables in real time. For example, if an exemplary embodiment determines that a specific plant is growing at a slower rate or is smaller than average at a given time, it may determine that more water or nutrients are needed and may then direct a boom or other source to water or provide nutrients to that plant. Further, an exemplary embodiment may track the association between the independent and dependent variables over time for each plant varietal in a historical plant database.”) [A stage of growth of each plant reads on “determine…a cultivation phase” and the time spent since germination reads on “the growth time”.]
generate an environmental target for the roughage based on the cultivation phase; Nguyen: Paragraph [0040] (“An exemplary control unit may track and control the various independent and dependent variables in real time. For example, if an exemplary embodiment determines that a specific plant is growing at a slower rate or is smaller than average at a given time, it may determine that more water or nutrients are needed and may then direct a boom or other source to water or provide nutrients to that plant. Further, an exemplary embodiment may track the association between the independent and dependent variables over time for each plant varietal in a historical plant database. Measurements may be compared to the historical plant data in order to identify optimal independent variable settings to obtain a targeted size, weight, shape, or harvest date. An exemplary embodiment may be configured to slightly alter various independent variables in order to identify an optimal value for each variable. For example, an exemplary embodiment may initially define an optimal growing temperature for a plant varietal. Then, in some embodiments, the control unit may alter the temperature to slightly above and/or slightly below the optimal growing temperature for that varietal, or for a portion of the total plants of that varietal.”) Nguyen: Paragraph [0041] (“… the control unit may then implement the slightly higher temperature in order to expedite the growth of that varietal in future growth cycles. Alternatively, if an exemplary embodiment determines that the slightly lower temperature slows down the growth, that lower temperature may be implemented when the market demand for the plant is low and the target harvest date is delayed. It may be contemplated that any variable, or a combination of variables, may be similarly optimized, including, but not limited to, plant size, survivability, electricity usage, and the like.”) [Determining independent variables based on factors such as progress in the stage of growth and the target duration reads on “generate an environmental target for the roughage based on the cultivation phase”.]
calculate a cultivation environment adjustment value for the roughage based on the environmental state value and the environmental target; Nguyen: Paragraphs [0040] and [0041] [As described above.] [The comparing of the historical plant data with the measurements to optimize the independent variable settings reads on “calculate a cultivation environment adjustment value for the roughage based on the environmental state value and the environmental target”.]
store a cultivation environment data set including a current time, the growth time, the cultivation phase, the environmental target, and the environmental state value for each cultivation space; and Nguyen: Paragraph [0034] and [0035] [As described above.] Nguyen: Abstract (“A historical database may store data regarding the variables and may be referenced and updated by an exemplary embodiment.”) Nguyen: Paragraph [0007] (“Growing conditions and growing duration may be changed based on target dependent variables in the growing process.”) Nguyen: Paragraph [0041] (“Plants growing under the altered conditions may be monitored and their growth data may be stored. If, for example, the slightly higher temperature increases the growth rate, that information may be stored. Finally, the control unit may then implement the slightly higher temperature in order to expedite the growth of that varietal in future growth cycles. Alternatively, if an exemplary embodiment determines that the slightly lower temperature slows down the growth, that lower temperature may be implemented when the market demand for the plant is low and the target harvest date is delayed. It may be contemplated that any variable, or a combination of variables, may be similarly optimized, including, but not limited to, plant size, survivability, electricity usage, and the like. Further, the control unit may optimize different variables according to different phases. For example, the root size or length may be optimized in a nursery phase, while the leaf size may be optimized in the greenhouse phase.”) Nguyen: Paragraph [0086] (“As independent variables are adjusted, an exemplary control unit may record and monitor dependent variables to identify a result or effect of the adjustment, and the data model may be updated dynamically and autonomously. An exemplary embodiment may store one or more control data models.”)
transmit the cultivation environment adjustment value to the cultivation apparatus and transmits the information about the operating state of the cultivation apparatus and the cultivation environment data set corresponding to cultivation information to the cultivator console in order to remotely control the cultivation apparatus. Nguyen: Paragraphs [0040] and [0041] [As described above.] Nguyen: Paragraphs [0040] and [0041] [As described above.] Nguyen: Paragraph [0043] (“The various phases of the cycle may be customized for different species and or varietals and may be adjusted over time. The phases may be customized for optimal time on a final hydroponic system or phase, which may be a natural or artificial system and may include a greenhouse, a deep-water agriculture location, a body of water or any combination thereof. The number of phases, including nursery phases and the specific indexing may all be adjusted as necessary to optimize the process. Different species or varietals may use any number of nurseries and associated nursery phases.”)
Although Nguyen lists a number of dependent and independent variables processed during plant cultivation, the reference does not teach that a server or a controller receives the particular cultivation information recited. However, Bull describes a method for optimizing plant growth in a hybrid growing environment may implement artificial intelligence to measure and alter plant biometrics. Bull teaches:
a cultivator console configured to transmit cultivation information including a cultivation environment mode, a grower's environmental target, a request for the start of growing the roughage, and an alarm about the start of harvesting the roughage; and Bull: Paragraph [0081] (“…a mobile computer application 200 comprises account, fields, data ingestion, sharing instructions 202 which are programmed to receive, translate, and ingest field data from third party systems via manual upload or APIs. Data types may include field boundaries, yield maps, as-planted maps, soil test results, as-applied maps, and/or management zones, among others.”) Bull: Paragraph [0082] (“In one embodiment, seeds and planting instructions 208 are programmed to provide tools for seed selection, hybrid placement, and script creation, including variable rate (VR) script creation, based upon scientific models and empirical data. This enables growers to maximize yield or return on investment through optimized seed purchase, placement and population.”) Bull: Paragraph [0062] (“Presentation layer 134 may be programmed or configured to generate a graphical user interface (GUI) to be displayed on field manager computing device 104, cab computer 115 or other computers that are coupled to the system 130 through the network 109. The GUI may comprise controls for inputting data to be sent to agricultural intelligence computer system 130, generating requests for models and/or recommendations, and/or displaying recommendations, notifications, models, and other field data.”) Bull: Paragraph [0059] (“Agricultural intelligence computer system 130 is programmed or configured to receive field data 106 from field manager computing device 104, external data 110 from external data server computer 108, and sensor data from remote sensor 112. Agricultural intelligence computer system 130 may be further configured to host, use or execute one or more computer programs, other software elements, digitally programmed logic such as FPGAs or ASICs, or any combination thereof to perform translation and storage of data values, construction of digital models of one or more crops on one or more fields, generation of recommendations and notifications, and generation and sending of scripts to application controller 114,…”) Bull: Paragraph [0068] (“FIG. 5 depicts an example embodiment of a timeline view for data entry. Using the display depicted in FIG. 5, a user computer can input a selection of a particular field and a particular date for the addition of event. Events depicted at the top of the timeline may include Nitrogen, Planting, Practices, and Soil. To add a nitrogen application event, a user computer may provide input to select the nitrogen tab. The user computer may then select a location on the timeline for a particular field in order to indicate an application of nitrogen on the selected field. In response to receiving a selection of a location on the timeline for a particular field, the data manager may display a data entry overlay, allowing the user computer to input data pertaining to nitrogen applications, planting procedures, soil application, tillage procedures, irrigation practices, or other information relating to the particular field.”) Bull: Paragraph [0054] (“Examples of field data 106 include (a) identification data (for example, acreage, field name, field identifiers, geographic identifiers, boundary identifiers, crop identifiers, and any other suitable data that may be used to identify farm land, such as a common land unit (CLU), lot and block number, a parcel number, geographic coordinates and boundaries, Farm Serial Number (FSN), farm number, tract number, field number, section, township, and/or range), (b) harvest data (for example, crop type, crop variety, … harvest date, Actual Production History (APH), expected yield, yield, crop price, crop revenue, grain moisture, tillage practice, and previous growing season information)… [The input for a particular date to plant, such as a corn plant, reads on “a request to start growing roughage”. The notification associated with the field data including harvest reads on “alarm about the start of harvesting the roughage”.]
Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having the teachings of Nguyen and Bull before them, to transmit cultivation information including a cultivation environment mode, a grower's environmental target, a request for the start of growing the roughage, and an alarm about the start of harvesting the roughage because the references are in the same field of endeavor as the claimed invention and they are focused on cultivating plants including corn (roughage).
One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to do this modification so that growing conditions and growing duration may be changed based on target dependent variables in the growing process and reduce risk of crop failure, improve product flexibility, and improve mechanical dependence. Bull Paragraphs [0003]-[0004].
Claims 2 and 13 are rejected under 35 U.S.C. 103 as being unpatentable over Nguyen, in view of Bull, and further in view of Tewari et al. (US Patent Publication No. 2021/0235612 A1) (“Tewari”).
Regarding claim 2, Nguyen and Bull teach all the claimed features of claim 1, from which claim 2 depends. Nguyen and Bull do not expressly teach the features of claim 2. However, Tewari describes an estimation crop type and/or sowing date. Tewari teaches:
The method of claim 1, wherein the cultivation space is divided based on the sowing time of seeds of the roughage. Tewari: Paragraph [0028] (“Differences in crop growth rates for different crop types result in crop-specific differences in NDVI value changes over the crop cycle. Hence, a NDVI time series over the life cycle of a crop can be used as that crop's signature in identifying crop type, as well as that crop's sowing date.”) Tewari: Paragraph [0100] (“In some embodiments, the area of interest may contain one or more regions (e.g., fields) with different crop types. The matching algorithm may, in accordance with some embodiments, identify these regions using one or more segmentation methods. For example, in some embodiments, the matching algorithm may use a per-pixel approach wherein each pixel is matched and a similarity threshold is applied to determine the boundary of these regions.”) Tewari: Paragraph [0048] (“A matching algorithm may take, as input, the crop-specific parameters (e.g., time series of LAI of crop types sown in the area of interest during one or more previous crop cycles—for instance, a simulated LAI time series for each of the crop types sown in the area of interest during one or more previous crop cycles and a historical LAI time series based on remote sensor data captured from the area of interest during the current crop cycle) and compute the distance between each simulated LAI time series and the historical LAI time series, and then perform a ranking of the computed distances.”)
Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having the teachings of Nguyen, Bull, and Tewari before them, for the cultivation space is divided based on the sowing time of seeds of the roughage because the references are in the same field of endeavor as the claimed invention and they are focused on cultivating plants including corn (roughage).
One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to do this modification to facilitate the determination of derivative information, such as sowing patterns and acreage under multiple crop types at a very early stage in the crop cycle. Tewari Paragraph [0021].
Regarding claim 13, Nguyen and Bull teach all the claimed features of claim 12, from which claim 13 depends. Nguyen and Bull do not expressly teach the features of claim 13. However, Tewari describes an estimation crop type and/or sowing date. Tewari teaches:
The system of claim 12, wherein the cultivation space is divided based on the sowing time of seeds of the roughage. Tewari: Paragraph [0028] (“Differences in crop growth rates for different crop types result in crop-specific differences in NDVI value changes over the crop cycle. Hence, a NDVI time series over the life cycle of a crop can be used as that crop's signature in identifying crop type, as well as that crop's sowing date.”) Tewari: Paragraph [0100] (“In some embodiments, the area of interest may contain one or more regions (e.g., fields) with different crop types. The matching algorithm may, in accordance with some embodiments, identify these regions using one or more segmentation methods. For example, in some embodiments, the matching algorithm may use a per-pixel approach wherein each pixel is matched and a similarity threshold is applied to determine the boundary of these regions.”) Tewari: Paragraph [0048] (“A matching algorithm may take, as input, the crop-specific parameters (e.g., time series of LAI of crop types sown in the area of interest during one or more previous crop cycles—for instance, a simulated LAI time series for each of the crop types sown in the area of interest during one or more previous crop cycles and a historical LAI time series based on remote sensor data captured from the area of interest during the current crop cycle) and compute the distance between each simulated LAI time series and the historical LAI time series, and then perform a ranking of the computed distances.”)
Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having the teachings of Nguyen, Bull, and Tewari before them, for the cultivation space is divided based on the sowing time of seeds of the roughage because the references are in the same field of endeavor as the claimed invention and they are focused on cultivating plants including corn (roughage).
One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to do this modification to facilitate the determination of derivative information, such as sowing patterns and acreage under multiple crop types at a very early stage in the crop cycle. Tewari Paragraph [0021].
Claims 6 and 7 are rejected under 35 U.S.C. 103 as being unpatentable over Nguyen, in view of Bull, and further in view of Xu, J., Meng, J. and Quackenbush, L.J., 2019. Use of remote sensing to predict the optimal harvest date of corn. Field Crops Research, 236, pp.1-13. (“Xu”).
Regarding claim 6, Nguyen and Bull teach all the claimed features of claim 1, from which claim 6 depends. Nguyen and Bull do not expressly teach the features of claim 6. However, Xu describes predicting an optimal harvest date. Xu teaches:
The method of claim 1, wherein the determining of the cultivation phase includes:
determining, by the cultivation server, that the roughage is in a first growth phase when the growth time is less than or equal to a first growth time, and determining, by the cultivation server, that the roughage is in a second growth phase when the growth time is greater than the first growth time and is less than or equal to a second growth time. Xu: Page 1, second column, first full paragraph (“The growth period of corn can be broadly divided into vegetative and reproductive stages. The reproductive stage comprises six sub-stages: silking, blistering, milking, doughing, denting, and physiological maturity (PM).”) Xu: Page 6, section 3.3, second column (“To verify whether the delay in harvest after corn reaches maturity influences the final yield, the temporal variation of one hundred-grain weight and yield was analyzed (Fig. 8, Fig. 9, Fig. 10, Fig. 11). Some studies have indicated that even though summer corn generally stops growing in late September, grain-filling continues (Sun et al., 2007). Our analysis showed that one hundred-grain weight and the yield both had a close relationship with the delay in harvesting, with R2 equal to 0.998 and 0.997 respectively, which indicated that both one hundred-grain weight and yield were significantly correlated with the delayed days after corn reaches maturity. Both one hundred-grain weight and the yield displayed a generally increasing trend over time.”) Xu: Page 7, section 3.4, first column (“Concurrently, the color of the leaves gradually turns to yellow, with a decrease in leaf chlorophyll content and [corn kernel moisture] CKM. Further analysis was conducted to demonstrate the variation of CKM over time (Fig. 12, Fig. 13). CKM data were collected on September 30, October 3, 5, 7, 9 and 11 for exploring the temporal variation of CKM. Fig. 12 shows that CKM displayed a general declining trend over this time period.”) Xu: Page 9, section 3.6, second column (“Based on the CKM calculation from September 30 and October 4, we calculated the change in average CKM over time (Table 4). Assuming a constant variation rate, CKM for October 1 to October 11 was then calculated based on the September 30 CKM value. Similarly, the CKM for October 5 to October 11 was calculated based on the October 4 CKM value. Observations of CKM on October 11 were used for CKM validation; absolute errors between the predicted and measured CKM on October 11 using both starting dates are also shown in Table 4. The average absolute errors indicate that CKM prediction based on September 30 was more accurate than CKM predicted from the October 4 data, which influences the prediction of OHD. However, the predicted OHD for plot 3 based on the September 30 CKM was October 3, while October 6 was more accurately predicted based on the October 4 CKM. This discrepancy may be caused by the temperature, weather or other external factors. Therefore, it is better to choose a basic CKM level closer to the beginning of corn maturity period.”) [The silking growth period reads on “a first growth phase” and any one of the blistering, milking, doughing, or denting reads on “a second growth phase”]
Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having the teachings of Nguyen, Bull, and Xu before them, for the determining, by the cultivation server, that the roughage is in a first growth phase when the growth time is less than or equal to a first growth time, and determining, by the cultivation server, that the roughage is in a second growth phase when the growth time is greater than the first growth time and is less than or equal to a second growth time because the references are in the same field of endeavor as the claimed invention and they are focused on cultivating plants including corn (roughage).
One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to do this modification because using remote sensing technology enables near real-time corn information and provides objective analysis of corn status even when plots are planted on different dates and impacted by many factors during the growing season. This study used only two time-series satellite images close to harvest date to predict the OHD. Second, as mentioned above, 30% CKM was a suitable OHD indicator for Hongxing farm but the approach applied is not limited to this site. If other farms are known to have different level demand, this method can also be adapted to predict the OHD. Xu Page 10, second column, last paragraph.
Regarding claim 7, Nguyen, Bull, and Xu teach all the claimed features of claim 6, from which claim 7 depends. Xu further teaches:
The method of claim 6, wherein the determining of the cultivation phase further includes: determining, by the cultivation server, that the roughage is in a third growth phase when the growth time is greater than the second growth time and is less than or equal to a third growth time, and determining, by the cultivation server, that the roughage is in a harvesting phase when the growth time is greater than the third growth time. Xu: Page 1, second column, first full paragraph; Page 6, section 3.3, second column; and Page 9, section 3.6, second column [As described in claim 6.] [After another of the blistering, milking, doughing, or denting reads on “a third growth phase”. The physiological maturity (PM) time reads on “the roughage is in a harvesting phase when the growth time is greater than the third growth time”.]
The motivation to combine Nguyen, Bull, and Xu as provided in claim 6 is incorporated herein.
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Nguyen, in view of Bull, and further in view of Lei (US Patent Publication No. 2022/0046866 A1) (“Lei”).
Regarding claim 8, Nguyen and Bull teach all the claimed features of claim 1, from which claim 8 depends. Bull further teaches:
The method of claim 1, wherein the generating of the environmental target includes:
…
generating, by the cultivation server, the environmental target according to the grower’s environmental target when the cultivation environment mode is set to a manual mode. Bull: Paragraphs [0081] and [0082] [As described in claim 1.]
The motivation to combine Nguyen and Bull as provided in claim 1 is incorporated herein.
Nguyen and Bull do not expressly teach generating, by the cultivation server, the environmental target corresponding to the cultivation phase when the cultivation environment mode is set to an automatic mode. However, Lei describes a plant factory. Lei teaches:
generating, by the cultivation server, the environmental target corresponding to the cultivation phase when the cultivation environment mode is set to an automatic mode, and… Lei: Paragraph [0019] (“By combining with the growth scheme of different types of plants and adjusting by controlling the light assembly in the present invention, the light assembly emits a wavelength corresponding to the corresponding types of plants at different growth stages, so that the corresponding light requirement of the different types of plants at each growth stage are met, therefore the plants are in the optimal growth state at each of the growth stages and grow in a predetermined manner of meeting the corresponding growth scheme, the corresponding types of plants achieve the growth target set manually or automatically to the plant factory.”)
Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having the teachings of Nguyen, Bull, and Lei before them, for generating, by the cultivation server, the environmental target corresponding to the cultivation phase when the cultivation environment mode is set to an automatic mode because the references are in the same field of endeavor as the claimed invention and they are focused on cultivating plants.
One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to do this modification because it would help the plants achieve the growth target set and achieve a zero inventory objections meeting the production characteristics of the plant factory. Lei Paragraphs [0024] and [0035].
Claim 11 is rejected under 35 U.S.C. 103 as being unpatentable over Nguyen, in view of Bull, and further in view of Luo et al. (US Patent Publication No. 2023/210062A1) (“Luo”).
Regarding claim 11, Nguyen and Bull teach all the claimed features of claim 1, from which claim 11 depends. Nguyen further teaches:
The method of claim 1, wherein the information about the operating state includes information about … an air conditioner, a lighting, and a spray nozzle are operating according to the cultivation environment adjustment value. Nguyen: Paragraph [0012] (“For example, the control system may be implemented to monitor the lifecycle of a plant as well as environmental data, such as light,…”) Nguyen: Paragraph [0068] (“For example, the AI may adjust a control unit set to control a heating or cooling unit, humidifier or dehumidifier, air purifier, water sprayer, nutrient sprayer, or any other contemplated mechanism which changes some environmental parameter.”)
Nguyen and Bull do not expressly teach that the information about the operating state includes information about how a circulation fan and a ventilation fan. However, Luo describes a greenhouse plant growth monitoring system. Luo teaches:
the information about the operating state includes information about how a circulation fan, a ventilation fan,… Luo: Paragraph [0026] (“The master controller 10 determines whether to turn on or off the external circulation device 40 according to the received external environment monitoring signal and the received internal environment monitoring signal. Exemplarily, the external environment monitoring signal output from the external monitoring module 20 is transmitted to the external environment signal input terminal, the internal environment monitoring signal output from the internal monitoring module 30 is transmitted to the internal environment signal output terminal, and the master controller 10 judges whether the external circulation device 40 needs to be turned on. In a case where the external circulation device 40 needs to be turned on, the master controller 10 outputs an external circulation adjustment signal to the control terminal of the external circulation device 40 to turn on the external circulation device 40. The external circulation device 40 includes a ventilation fan 41. The ventilation fan 41 in the external circulation device 40 exchanges air in the plant growth greenhouse with external air so as to achieve the circulation of the air in the greenhouse and the external air.”) Luo: Paragraph [0028] (“The master controller 10 determines whether to turn on or off the internal circulation device 50 according to the output external environment monitoring signal and the output internal environment monitoring signal. The master controller 10 judges whether the internal circulation device 50 needs to be turned on. In a case where the internal circulation device 50 needs to be turned on, the master controller 10 outputs an internal circulation adjustment signal to the control terminal of the internal circulation device 50 to turn on the internal circulation device 50. The internal circulation device 50 includes a circulation fan 51. The circulation fan 51 in the internal circulation device 50 is configured to accelerate airflow circulation in the internal environment.”)
Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having the teachings of Nguyen, Bull, and Luo before them, for the information about the operating state includes information about how a circulation fan and a ventilation fan because the references are in the same field of endeavor as the claimed invention and they are focused on cultivating plants.
One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to do this modification because it would improve the quality, overall yield and profitability of greenhouse plants and achieve the circulation of the air in the greenhouse and the external air. Luo Paragraphs [0005] and [0026].
It is noted that any citations to specific, pages, columns, lines, or figures in the prior art references and any interpretation of the reference should not be considered to be limiting in any way. A reference is relevant for all it contains and may be relied upon for all that it would have reasonably suggested to one having ordinary skill in the art. See MPEP 2123.
Allowable Subject Matter over Prior Art
Pending the non-statutory subject matter rejection, the recitations of claims 4 and 5 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
As allowable subject matter has been indicated, applicant's reply must either comply with all formal requirements or specifically traverse each requirement not complied with. See 37 CFR 1.111(b) and MPEP § 707.07(a).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US Patent Publication No. 2020/0208053 A1to Bonini et al. describes that according to the ACCI (American Association of Cereal Chemists), fibre, also known as roughage, is the edible part of plants or analogous carbohydrates which is resistant to digestion and absorption in the human small intestine with complete or partial fermentation in the large intestine. In the agricultural field, fibre is to be understood as the indigestible part of plants, seeds and grains, which requires a fermentation step prior to its absorption by the plant, and it may also include plant or grain components that have been minimally processed. Dietary fibre usually includes compounds such as polysaccharides, oligosaccharides, lignins, and associated plant substances.
US Patent Publication No. 2021/0378161 A1 to Kerr et al. describes an interface of FIG. 54 may be utilized to initiate, confirm, and/or view harvest operations. The capabilities of user operations using the interface of FIG. 54 may be scheduled according to permissions associated with the user. An operator may indicate they are harvesting a set of plants by interacting with a shelf or tray tag and indicating that the plants on that shelf or tray are being harvested. In an embodiment, the user may be shown the shelf or tray they are harvesting on a user interface. The application may automatically update a database with the detail that the plants are being harvested. Total weight of the harvest may be manually entered or may be automatically entered by using a wirelessly connected scale that feeds data into the application.
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/ALICIA M. CHOI/Primary Patent Examiner, Art Unit 2117