The present invention relates to methods for controlling or preventing infestation of a plant by a phytopathogenic microorganism of the genus Macrophomina spp., comprising applying to a crop of plants, the locus thereof, or propagation material thereof, a compound according to formula (I), wherein R1, R2, R3, R4, R5, Y, A, B are as defined herein.

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The invention provides seed and plants of the bean line designated SV3902GA. The invention thus relates to the plants, seeds and tissue cultures of bean line SV3902GA, and to methods for producing a bean plant produced by crossing a plant of bean line SV3902GA with itself or with another bean plant, such as a plant of another line. The invention further relates to seeds and plants produced by such crossing. The invention further relates to parts of a plant of bean line SV3902GA, including the pods and gametes of such plants.

A computing system includes a processor and a non-transitory, computer-readable media including instructions that, when executed by the one or more processors, cause the computing system to access an initial machine data set; label the machine data set; process the labeled machine data set; and modify one or more parameters of the machine-learned model. A method includes accessing an initial machine data set; labeling the machine data set; processing the labeled machine data set; and modifying one or more parameters of the machine-learned model. A computing system for predicting a variety profile index includes a processor; and a non-transitory, computer-readable media including a trained machine-learned model; and instructions that, when executed by the one or more processors, cause the computing system to process a second machine data set to generate one or more predicted variety profile index values; and provide the one or more predicted variety profile index values.

A computing system includes a processor and a non-transitory, computer-readable media including instructions that, when executed by the one or more processors, cause the computing system to access an initial machine data set; label the machine data set; process the labeled machine data set; and modify one or more parameters of the machine-learned model. A method includes accessing an initial machine data set; labeling the machine data set; processing the labeled machine data set; and modifying one or more parameters of the machine-learned model. A computing system for predicting a variety profile index includes a processor; and a non-transitory, computer-readable media including a trained machine-learned model; and instructions that, when executed by the one or more processors, cause the computing system to process a second machine data set to generate one or more predicted variety profile index values; and provide the one or more predicted variety profile index values.

An object of the present invention is to provide a method that can effectively/efficiently increase the amount of a phenolic compound such as a polyphenol. The invention provides a method for increasing an amount of a phenolic compound in a plant, or a method for producing a plant containing an increased amount of a phenolic compound, the method comprising irradiating the/a plant with ultraviolet light, wherein a fluence at wavelengths of 270 to 290 nm is 1500 to 50000 μmol/m.sup.2 and a fluence at wavelengths of 310 to 400 nm is less than 50% of that at wavelengths of 270 to 290 nm.

A computing system includes a processor and a non-transitory, computer-readable medium including instructions that, when executed by the processor, causes the computing system to receive a machine data set; process the machine data set using a trained machine-learned model to generate predicted variety profile index values, and transmit the variety profile index values to a client computing device. A computer-implemented method includes receiving a machine data set; processing the machine data set using a trained machine-learned model to generate predicted variety profile index values, and transmitting the variety profile index values to a client computing device. A non-transitory computer-readable medium includes instructions stored thereon that, when executed by one or more processors, cause a computer to receive a machine data set; process the machine data set using a trained machine-learned model to generate predicted variety profile index values, and transmit the variety profile index values to a client computing device.

A system includes one or more processors; and one or more non-transitory, computer-readable media including instructions that, when executed by the one or more processors, cause the computing system to: receive a machine data set; process the machine data set with a trained machine-learned model to generate predicted variety profile index values; and cause a visualization to be displayed. A computer-implemented method includes receiving a machine data set; processing the machine data set with a trained machine-learned model to generate predicted variety profile index values; and causing a visualization to be displayed. A non-transitory computer-readable medium includes computer-executable instructions that, when executed by one or more processors, cause a computer to: receive a machine data set; process the machine data set with a trained machine-learned model to generate predicted variety profile index values; and cause a visualization to be displayed.

A method for removing organic pollutants from water bodies by activating persulfate with nutrient-enhanced soybean sprout-based biochar involves a method for removing organic pollutants from water bodies by activating persulfate with biochar. The invention is intended to solve the technical problems that existing biochar materials show poor catalytic activity when used for activating persulfate and requires the addition of a large amount of modifiers, which easily leads to secondary pollution to the environment, and the existing biochar materials are susceptible to interference from halogen ions, oxoanions, and natural organic matters in a persulfate system. The raw material of a catalyst used in the invention is soybean, and has an activation process mainly based on non-radical activation, exhibiting high reaction rate and saving persulfate. With the addition of 0.2 g/L catalyst and 0.5 mM potassium persulfate, the degradation efficiency against 10 mg/L phenol can reach 100% within 10 min.

A method for removing organic pollutants from water bodies by activating persulfate with nutrient-enhanced soybean sprout-based biochar involves a method for removing organic pollutants from water bodies by activating persulfate with biochar. The invention is intended to solve the technical problems that existing biochar materials show poor catalytic activity when used for activating persulfate and requires the addition of a large amount of modifiers, which easily leads to secondary pollution to the environment, and the existing biochar materials are susceptible to interference from halogen ions, oxoanions, and natural organic matters in a persulfate system. The raw material of a catalyst used in the invention is soybean, and has an activation process mainly based on non-radical activation, exhibiting high reaction rate and saving persulfate. With the addition of 0.2 g/L catalyst and 0.5 mM potassium persulfate, the degradation efficiency against 10 mg/L phenol can reach 100% within 10 min.

Provided herein are compositions and methods for producing milk proteins in plants, which allow for safe, sustainable and humane production of milk proteins for commercial use, such as use in food compositions. The disclosure provides recombinant fusion proteins comprising a milk protein, or fragment thereof and a structured mammalian, avian, plant, or fungal protein, or fragment thereof. The disclosure also provides methods for producing the recombinant fusions proteins, and food compositions comprising the same.