A computer-implemented method for reporting performance of an agricultural input for a plant involves: storing in a computer database a set of agricultural inputs, plants for which the agricultural inputs are used, performance attributes of the agricultural inputs, historical agricultural input performance values, and a relative significance of each of the agricultural inputs for the performance attribute. A computer processor is used to receive a plant selection; receive an attribute to be targeted for the plant selection; identify a plurality of agricultural inputs for affecting the targeted attribute for the plant using the historical agricultural input performance values; rank the plurality of agricultural inputs for affecting the targeted attribute for the selected plant using the relative significance associated therewith; and display the plurality of agricultural inputs and corresponding ranks for the received attribute associated with the selected plant.

The present invention addresses the problem of providing a soil amelioration method that makes it possible to conveniently ameliorate soil. This soil amelioration method involves applying nano-bubble water to soil.

The present invention addresses the problem of providing a soil amelioration method that makes it possible to conveniently ameliorate soil. This soil amelioration method involves applying nano-bubble water to soil.

The invention relates to a handheld device and method for determining a status of one or more plants. The device includes a digital color camera arranged for obtaining a color image of plants within a field of view, a light source arranged for providing broadband illumination to the plants within the field of view, and a processing unit arranged for controlling the camera and the light source for obtaining a first image of the plants while the light source illuminates the plants with broadband illumination, and obtaining a second image of the plants while the light source does not illuminate the plants.

The present technology relates to an information processing device and an information processing method, in which Synecoculture (registered trademark) can be assisted. An ecosystem object indicating an ecosystem constituent configuring an ecosystem of an agricultural field in which a plurality of types of vegetation are mixed up and a task object indicating a task performed with respect to the ecosystem constituent are acquired, and the ecosystem object is subjected to augmented reality (AR) display in a position in a predetermined background space, corresponding to a real position of the ecosystem constituent, and the task object is subjected to AR display in the background space. The present technology, for example, can be applied to a case or the like where information of assisting Synecoculture (registered trademark) is provided.

The present technology relates to an information processing device and an information processing method, in which Synecoculture (registered trademark) can be assisted. An ecosystem object indicating an ecosystem constituent configuring an ecosystem of an agricultural field in which a plurality of types of vegetation are mixed up and a task object indicating a task performed with respect to the ecosystem constituent are acquired, and the ecosystem object is subjected to augmented reality (AR) display in a position in a predetermined background space, corresponding to a real position of the ecosystem constituent, and the task object is subjected to AR display in the background space. The present technology, for example, can be applied to a case or the like where information of assisting Synecoculture (registered trademark) is provided.

The present inventors have recognized that various diseases in plants, such as Phytophthora infestans (late blight) and Alternaria solani (early blight), and/or various stages of such diseases in plants, can be reliably detected by applying measurements from electromagnetic reflections detected from a plant in a model to produce an output indicating a probability of the disease and/or stage. In one aspect, coefficients can be applied to each measurement at each wavelength to emphasize identification of a given disease or stage. In another aspect, an imager can capture images comprising spectral pixels in which each pixel comprises measurements from the electromagnetic reflections for application in a model to identify a given disease or stage.

The present inventors have recognized that various diseases in plants, such as Phytophthora infestans (late blight) and Alternaria solani (early blight), and/or various stages of such diseases in plants, can be reliably detected by applying measurements from electromagnetic reflections detected from a plant in a model to produce an output indicating a probability of the disease and/or stage. In one aspect, coefficients can be applied to each measurement at each wavelength to emphasize identification of a given disease or stage. In another aspect, an imager can capture images comprising spectral pixels in which each pixel comprises measurements from the electromagnetic reflections for application in a model to identify a given disease or stage.

A cultivation-target crop selection assisting apparatus 10 includes: an information collection unit 11 configured to collect information regarding a specific cultivated land; a prediction value calculation unit 12 configured to calculate a prediction value of actual performance of cultivation of one or a plurality of varieties of crops in the specific cultivated land by applying the information collected by the information collection unit 11 to a prediction model 14 created by performing machine learning on a relationship between information regarding a sample cultivated land and actual performance information regarding a crop produced in the sample cultivated land; and a crop selection unit 13 configured to select a crop that is suitable for being cultivated in the specific cultivated land based on the prediction value calculated for the one or plurality of varieties of crops.

A cultivation-target crop selection assisting apparatus 10 includes: an information collection unit 11 configured to collect information regarding a specific cultivated land; a prediction value calculation unit 12 configured to calculate a prediction value of actual performance of cultivation of one or a plurality of varieties of crops in the specific cultivated land by applying the information collected by the information collection unit 11 to a prediction model 14 created by performing machine learning on a relationship between information regarding a sample cultivated land and actual performance information regarding a crop produced in the sample cultivated land; and a crop selection unit 13 configured to select a crop that is suitable for being cultivated in the specific cultivated land based on the prediction value calculated for the one or plurality of varieties of crops.