Provided herein are methods and systems for monitoring plants. A QR code can be associated with a plant, wherein a static QR code can be associated with a plant. The static QR code can be dynamically scanned and encoded with data that identifies the plant and contains information about the plant. The information may include geolocation information and/or image files that monitor the developmental stages of the plant. The encoded data may then be transmitted over a network to retrievable storage.

One variation of a method for identifying stressors in crops based on fluorescence of sensor plants includes: accessing a set of spectral images of a sensor plant sown in a crop, the sensor plant of a sensor plant type including a set of promoters and a set of reporters configured to signal a set of stressors present at the sensor plant, the set of promoters and set of reporters forming a set of promoter-reporter pairs; accessing a reporter model linking characteristics extracted from the set of spectral images of the sensor plant to the set of stressors based on signals generated by the set of promoter-reporter pairs in the sensor plant type; and identifying a first stressor, in the set of stressors, present at the sensor plant based on the reporter model and characteristics extracted from the set of spectral images.

A method for building a farmland ecosystem with multiple mutual-benefit species in multiple habitats is provided. The method includes: marking out an ecological field plot for planting crops in a farmland, arranging one to three earthworm breeding strip stack(s) at equal intervals, and marking out different planting areas; digging an ecological field ditch surrounding a periphery of the ecological field plot, and planting aquatic plants and breeding aquatic animals in the ecological field ditch; surrounding a periphery of the ecological field ditch with an ecological wide ridge, planting forage plants on a ridge surface of the ecological wide ridge, and planting arbors on an outer side of the ecological wide ridge; and arranging an ecological pond on a drainage side of a hole, wherein aquatic plants are planted in the ecological pond, and crustaceans are bred in the ecological pond.

A method for building a farmland ecosystem with multiple mutual-benefit species in multiple habitats is provided. The method includes: marking out an ecological field plot for planting crops in a farmland, arranging one to three earthworm breeding strip stack(s) at equal intervals, and marking out different planting areas; digging an ecological field ditch surrounding a periphery of the ecological field plot, and planting aquatic plants and breeding aquatic animals in the ecological field ditch; surrounding a periphery of the ecological field ditch with an ecological wide ridge, planting forage plants on a ridge surface of the ecological wide ridge, and planting arbors on an outer side of the ecological wide ridge; and arranging an ecological pond on a drainage side of a hole, wherein aquatic plants are planted in the ecological pond, and crustaceans are bred in the ecological pond.

A solution for controlling mildew in a cultivated area is described. The solution can include a set of ultraviolet sources that are configured to emit ultraviolet and/or blue-ultraviolet radiation to harm mildew present on a plant or ground surface. A set of sensors can be utilized to acquire plant data for at least one plant surface of a plant, which can be processed to determine a presence of mildew on the at least one plant surface. Additional features can be included to further affect the growth environment for the plant. A feedback process can be implemented to improve one or more aspects of the growth environment.

A method for obtaining new plant growth data according to an experimentation objective, the method including defining an experimentation objective; defining a set of experimentation alternatives; obtaining a data set of experimentation alternative conditions; obtaining a trained plant growth model including plant growth model parameters; defining an experimental design utility function based on the experimentation objective; selecting an experimentation plan from the set of experimentation alternatives by using the trained plant growth model, the experimental design utility function, and the data set of experimentation alternative conditions; and performing the selected experimentation plan to obtain new plant growth data.

A model generation apparatus according to one or more embodiments may include: a generating unit that generates data using a generation model; a transmitting unit that transmits the generated data to a plurality of trained identification models that each have acquired, by machine learning using local learning data, a capability of identifying whether given data is the local learning data, and causes the identification models to perform an identification on the data; a receiving unit that receives results of identification with respect to the transmitted data executed by the identification models; and a learning processing unit that trains the generation model to generate data that causes identification performance of at least one of the plurality of identification models to be degraded, by performing machine learning using the received results of identification.

An apparatus for providing an optimal pest control recipe depending on a progress of disease and pest damages and a method thereof are provided. The apparatus for providing an optimal pest control recipe depending on a progress of disease and pest damages, in which the apparatus is connected with an photographing device and a user terminal, may include: an input module configured to receive image data of crops from the photographing device; a diagnosis module configured to analyze the image data to determine a type and progress of the disease and pest damages; a prescription module configured to generate a pest control recipe according to the determined progress of the disease and pest damages; and a communication module configured to transmit the pest control recipe to the user terminal.

An apparatus for providing an optimal pest control recipe depending on a progress of disease and pest damages and a method thereof are provided. The apparatus for providing an optimal pest control recipe depending on a progress of disease and pest damages, in which the apparatus is connected with an photographing device and a user terminal, may include: an input module configured to receive image data of crops from the photographing device; a diagnosis module configured to analyze the image data to determine a type and progress of the disease and pest damages; a prescription module configured to generate a pest control recipe according to the determined progress of the disease and pest damages; and a communication module configured to transmit the pest control recipe to the user terminal.

An integrated multi-scale modeling platform is utilized to assess agricultural productivity and sustainability. The model is used to assess the environmental impacts of agricultural management from individual fields to watershed/basin to continental scales. In addition, an integrated irrigation system is developed using data and a machine-learning model that includes weather forecast and soil moisture simulation to determine an irrigation amount for farmers. Next, crop cover classification prediction can be established for an ongoing growing system using a machine learning or statistical model to predict the planted crop type in an area. Finally, a method of predicting key phenology dates of crops for individual field parcels, farms, or parts of a field parcel, in a growing season, can be established.