Abstract: One embodiment provides a method, including: receiving a plurality of consumer feedback comments regarding one of a plurality of agricultural food products, wherein each of the plurality of consumer feedback comments comprises information regarding a characteristic of a given agricultural food product, wherein each of the plurality of agricultural food products corresponds to an agricultural source producing an agricultural food product category; updating a rating of each of the plurality of agricultural food products based upon consumer feedback comments corresponding to a given agricultural food product, wherein the updating comprises aggregating the received consumer feedback comments with previously supplied consumer feedback comments for agricultural food products within the agricultural food product category of a given agricultural source; ranking the plurality of agricultural food products based upon the ratings of the plurality of agricultural food products, wherein the ranking comprises ranking the p

Abstract: Methods, systems, and computer program products for auto-discovery of reasoning knowledge graphs in supply chains are provided herein. A computer-implemented method includes obtaining a spatiotemporal query related to a demand of at least one product in a supply chain; analyzing the spatiotemporal query to identify one or more parameters affecting the demand of the at least one product, wherein the one or more parameters comprise at least one of one or more climate parameters and one or more disruptive event parameters; generating a knowledge graph comprising information indicating an impact on the demand of the at least one product for at least a portion of the one or more parameters; and outputting, to a user interface, an explanation of a predicted demand forecast for the at least one product based at least in part on the knowledge graph.

Abstract: A method, computer system, and a computer program product for improving environmental impact estimations is provided. The present invention may include obtaining data pertaining to an agricultural area. The present invention may include deriving one or more features from the data pertaining to the agricultural area. The present invention may include identifying one or more stubble burning areas within the agricultural areas based on the one or more derived features. The present invention may include determining an environmental impact for each of the one or more stubble burning areas.

Abstract: A method and system generate news headlines from user input parameters. The user input parameters include a specified geographic region of interest and an industry of interest. Climate data and carbon emissions data for the specified geographic region of interest is retrieved. Supply chain dependencies are determined. A machine learning model is generated using the specified geographic region of interest, the industry, the climate data, the carbon emissions data, and the supply chain dependencies. The machine learning model performs an impact analysis on a supply chain based on the climate data and the carbon emissions data. The machine learning model predicts a supply chain performance for the industry based on the impact analysis. A news headline is automatically generated describing the predicted supply chain performance. The news headline includes an underlying basis for the predicted supply chain performance.

Abstract: Methods, systems, and computer program products for generating GHG emissions estimations associated with logistics contexts using machine learning techniques are provided herein.

Abstract: Methods, systems, and computer program products for generating context-aware process-based model determinations for greenhouse gas emissions from agricultural fields are provided herein.

Abstract: Methods, systems, and computer program products for enhancing spatial and temporal resolution of greenhouse gas emission estimates for agricultural fields using cohort analysis techniques are provided herein.

Abstract: Methods, systems, and computer program products for auto-discovery of reasoning knowledge graphs in supply chains are provided herein. A computer-implemented method includes obtaining a spatiotemporal query related to a demand of at least one product in a supply chain; analyzing the spatiotemporal query to identify one or more parameters affecting the demand of the at least one product, wherein the one or more parameters comprise at least one of one or more climate parameters and one or more disruptive event parameters; generating a knowledge graph comprising information indicating an impact on the demand of the at least one product for at least a portion of the one or more parameters; and outputting, to a user interface, an explanation of a predicted demand forecast for the at least one product based at least in part on the knowledge graph.

Abstract: One embodiment provides a method, including: training a plurality of machine-learning models, wherein each of the machine-learning models is trained for a specific farm field region utilizing training data for the plurality of machine-learning models; wherein the utilizing training data includes identifying one of the farm field regions having a similarity to another of the farm field regions and transferring training data; identifying a plurality of types of data needed for updating at least one of the plurality of machine-learning models to address at least one uncertainty; recommending collection of and collecting at least one of the plurality of types of data; and re-training the subset of the plurality of machine-learning models utilizing the at least one of the plurality of types of data, thereby decreasing the cost the of data collection, for example, crowdsourced data, by utilizing data collected from one farm field region in other farm field regions.

Abstract: Methods, systems, and computer program products for dynamic determination of irrigation-related data using machine learning techniques are provided herein.

Abstract: One embodiment provides a method, including: obtaining, for each step in a food supply chain, information corresponding to extraneous factors, wherein the extraneous factors comprise factors that may affect quality of a food product within the food supply chain; generating a rating, for each step in the food supply chain, indicating a level of pollution to which the food product was exposed at the corresponding step, wherein the rating comprises (i) scoring each of the extraneous factors based upon a level of pollution identified from the extraneous factors and (ii) aggregating the scores for the extraneous factors to determining a rating; generating, using the rating for each of the steps, an aggregate food supply chain score for the food product, wherein the aggregate food supply chain indicates an impact of pollution across the food supply chain on the food product; and producing a quality rating for the food product.

Abstract: One embodiment provides a method, including: receiving a plurality of consumer feedback comments regarding one of a plurality of agricultural food products, wherein each of the plurality of consumer feedback comments comprises information regarding a characteristic of a given agricultural food product, wherein each of the plurality of agricultural food products corresponds to an agricultural source producing an agricultural food product category; updating a rating of each of the plurality of agricultural food products based upon consumer feedback comments corresponding to a given agricultural food product, wherein the updating comprises aggregating the received consumer feedback comments with previously supplied consumer feedback comments for agricultural food products within the agricultural food product category of a given agricultural source; ranking the plurality of agricultural food products based upon the ratings of the plurality of agricultural food products, wherein the ranking comprises ranking the p

Abstract: Methods, systems, and computer program products for dynamic determination of irrigation-related data using machine learning techniques are provided herein.

Abstract: Methods, systems, and computer program products for providing energy elasticity services via distributed virtual batteries are provided herein.

Abstract: One embodiment provides a method, including: identifying a target farmer having a farm producing a crop; receiving at least one target farmer input related to at least one of: (i) a growing condition of the crop of the target farmer and (ii) a characteristic of the crop; receiving, from each of the plurality of other farmers, additional input; validating the at least one target farmer input by comparing the at least one target farmer input to the additional inputs; generating a reliability score for the target farmer; and producing a ranking for the target farmer with respect to the plurality of other farmers.

Abstract: One embodiment provides a method, including: obtaining, for each step in a food supply chain, information corresponding to extraneous factors, wherein the extraneous factors comprise factors that may affect quality of a food product within the food supply chain; generating a rating, for each step in the food supply chain, indicating a level of pollution to which the food product was exposed at the corresponding step, wherein the rating comprises (i) scoring each of the extraneous factors based upon a level of pollution identified from the extraneous factors and (ii) aggregating the scores for the extraneous factors to determining a rating; generating, using the rating for each of the steps, an aggregate food supply chain score for the food product, wherein the aggregate food supply chain indicates an impact of pollution across the food supply chain on the food product; and producing a quality rating for the food product.

Abstract: Methods, systems, and computer program products for providing energy elasticity services via distributed virtual batteries are provided herein.

Abstract: One embodiment provides a method, including: executing, using at least one processor, computer readable program code to: identify a plurality of possibilities at the disposal of a data center for changing its energy demand in its role as a consumer of energy, wherein each of the possibilities is associated with: a time interval during which change in energy consumption of the data center is to take place; and an amount of energy to be drawn, during the time interval, by the data center from an electric provider through a connection to a power grid; wherein the plurality of possibilities are different from each other; proactively determine, based on the identified plurality of possibilities, the ability of the data center to change its energy consumption, thereby changing the amount of energy drawn by the data center from the energy provider; and communicate, to a remote device that is in direct communication with an energy supplier, data indicating the ability of the data center to change its energy consumpti

Abstract: One embodiment provides a method, including: executing, using at least one processor, computer readable program code to: identify a plurality of possibilities at the disposal of a data center for changing its energy demand in its role as a consumer of energy, wherein each of the possibilities is associated with: a time interval during which change in energy consumption of the data center is to take place; and an amount of energy to be drawn, during the time interval, by the data center from an electric provider through a connection to a power grid; wherein the plurality of possibilities are different from each other; proactively determine, based on the identified plurality of possibilities, the ability of the data center to change its energy consumption, thereby changing the amount of energy drawn by the data center from the energy provider; and communicate, to a remote device that is in direct communication with an energy supplier, data indicating the ability of the data center to change its energy consumpti