There is achieved short-time measurement of a measurement target such as a farm field with high accuracy. Therefore, processing is performed on a sampling image obtained by the imaging of a part of a range as a measurement target with a multi spectrum camera that performs imaging to capture images in a plurality of different wavelength bands. Then, arithmetic processing is performed on the sampling image as a processing target to generate a calculation result image serving as evaluation information for the entire measurement target.

The present invention is directed to computerized agricultural systems and methods for controlling and managing plant development, from seeding through harvest, in greenhouses and other agricultural production facilities.

The accuracy of an index indicating growth conditions of a crop obtained from a shot image is improved, while reducing the flight time of an aircraft shooting the crop. Crop image acquisition unit acquires an image of a crop region shot by drone. Index calculation unit calculates an index indicating growth conditions of a crop shot in the image based on the acquired image of the crop region. Flight instruction unit instructs, if a portion (low index region) regarding which the calculated index is less than a predetermined index threshold is present in the crop region, drone to shoot the low index region while increasing the resolution of the image. Specifically, flight instruction unit makes an instruction to shoot the portion while performing a low-altitude flight at an altitude lower than that when the image regarding which the index of the low index region has been calculated has been shot.

The accuracy of an index indicating growth conditions of a crop obtained from a shot image is improved, while reducing the flight time of an aircraft shooting the crop. Crop image acquisition unit acquires an image of a crop region shot by drone. Index calculation unit calculates an index indicating growth conditions of a crop shot in the image based on the acquired image of the crop region. Flight instruction unit instructs, if a portion (low index region) regarding which the calculated index is less than a predetermined index threshold is present in the crop region, drone to shoot the low index region while increasing the resolution of the image. Specifically, flight instruction unit makes an instruction to shoot the portion while performing a low-altitude flight at an altitude lower than that when the image regarding which the index of the low index region has been calculated has been shot.

Methods, apparatus, systems and processor-readable storage media for distributed farming are provided herein. A computer-implemented method includes facilitating transfer of produce, at approximately a given stage of a growth cycle of the produce, from a first location to a remote growing unit; analyzing data, captured via multiple sensors within the remote growing unit, wherein the analyzing is carried out by a centralized server communicatively linked to the remote growing unit; and transmitting, via the centralized server to the remote growing unit, instructions pertaining to an adjustment to at least one growing parameter within the remote growing unit, wherein the transmitting is based at least in part on the analyzing of the data, and wherein the transmitting occurs during one or more stages of the growth cycle that is between the given stage and completion of the growth cycle.

Methods, apparatus, systems and processor-readable storage media for distributed farming are provided herein. A computer-implemented method includes facilitating transfer of produce, at approximately a given stage of a growth cycle of the produce, from a first location to a remote growing unit; analyzing data, captured via multiple sensors within the remote growing unit, wherein the analyzing is carried out by a centralized server communicatively linked to the remote growing unit; and transmitting, via the centralized server to the remote growing unit, instructions pertaining to an adjustment to at least one growing parameter within the remote growing unit, wherein the transmitting is based at least in part on the analyzing of the data, and wherein the transmitting occurs during one or more stages of the growth cycle that is between the given stage and completion of the growth cycle.

A server of a crop growth stage determination system includes a processor. The processor inputs first images obtained by image capturing crops in a manner such that crop shapes are extractable. The Processor inputs growth stages each indicating a level of physiological growth of the crops for each of the first images. The processor constructs a learned model by performing deep learning to associate images of the crops and growth stages of the crops based on the input first images and the input growth stage. The processor inputs a second image obtained by image capturing crops a growth stage of which is unknown, in a manner such that crop-shapes are extractable. The processor determines the growth stage for the input second image based on the learned model. The processor outputs the determined growth stage.

The present invention concerns a method for culturing a plant, said method comprising a culture step wherein said plant is submitted to repeated thermal cycles, wherein, for each thermal cycle, cool temperature and warm temperature are alternately artificially applied to all or a part of said plant, over a period shorter than natural seasons.

The present invention also concerns a method for producing natural rubber from latex-producing plants, said method comprising the steps of (a) culturing the latex-producing plant by implementing the method of culture of the invention, (b) harvesting part or all of root part of said plant, and (c) extracting natural rubber from the root part harvested at step b).

The present disclosure describes a system, method, and non-transitory computer readable medium for analyzing soil samples. Accordingly, soil sample units may be obtained and provided to a server that generates raw data. The raw data is sent to a database, where it is downloaded. The raw data is subsequently organized into a sub-report for each nutrient or variable contained in the raw data. An average for each nutrient in the raw data and a number of additional factors related to the raw data may be calculated. The average and additional factors are used to determine bulk recommendations by comparing target data to an exchangeable measured value. Additionally, the factors are also used to determine challenges and solutions by comparing the average data to the target data for each nutrient. The system compares the raw data to the measured values and mathematically adjusts the compared values to compute an optimal treatment algorithm.

The present disclosure describes a system, method, and non-transitory computer readable medium for analyzing soil samples. Accordingly, soil sample units may be obtained and provided to a server that generates raw data. The raw data is sent to a database, where it is downloaded. The raw data is subsequently organized into a sub-report for each nutrient or variable contained in the raw data. An average for each nutrient in the raw data and a number of additional factors related to the raw data may be calculated. The average and additional factors are used to determine bulk recommendations by comparing target data to an exchangeable measured value. Additionally, the factors are also used to determine challenges and solutions by comparing the average data to the target data for each nutrient. The system compares the raw data to the measured values and mathematically adjusts the compared values to compute an optimal treatment algorithm.