Abstract: Systems and methods described herein can non-destructively determine current produce quality. An evaluation system can, at a first time, receive image data of produce and identify a type of the produce using machine learning techniques. The produce can be sent to an end-consumer retail environment. A quality assessment system can, at a second time, receive, from a user device in the retail environment, a request for a current quality of a particular produce that includes scanned data of that produce. The quality assessment system can identify that produce, retrieve, from a data store, machine learning trained models for identifying quality features of that produce, determine, based on applying the models to the scanned data, a current quality of that produce, and transmit, to the user device, the current quality. The produce's price can also be dynamically adjusted based on the current quality of that produce.

Abstract: This disclosure is directed to systems and methods for assessing quality characteristics of food items based on analyzing volatiles outgassed by them. The quality characteristics can include presence of infection, ripeness stage, flavor, taste, and smell. Determining quality characteristics can be advantageous to make supply chain modifications that optimize on quality and reduce food-based waste. A tube having a sorbent material can be placed in an environment containing the food items. Volatiles outgassed by the food items can collect on the sorbent material. A computing system can receive the volatiles presence and concentration data and can apply a machine learning model to the data to determine quality characteristics of the food items. The model can be trained using human observations of quality characteristics, historic supply chain information, and processed volatiles data associated with other food items, wherein the other food items are a same type as the food items.

Abstract: Described herein are compositions from refined oil from plant matter, and in particular from seed, bean, nut, kernel, or pulp (e.g., wood pulp) material of virgin and/or non-virgin plant matter, and methods of forming those compositions. The methods typically include the steps of (i) at least partially separating the seed, bean, nut, kernel, or pulp material from other portions of the plant matter; (ii) extracting an oil comprising one or more triglycerides from the seed, bean, nut, kernel, or pulp material; (iii) refining the oil to remove one or more impurity components; and (iv) chemically or physically modifying the refined oil.

Abstract: Apparatus for obtaining the gas-phase electromagnetic radiation spectrum of a liquid sample, including an analysis chamber having an inlet and an outlet, wherein the inlet and analysis chamber are such that, in use, liquid sample is drawn into the inlet through capillary action and vaporized therein. The vaporized liquid sample is maintained in the gas-phase within the inlet and the analysis chamber.

Abstract: A method and apparatus for obtaining the gas-phase electromagnetic radiation spectrum of a liquid sample, which apparatus comprises an analysis chamber having an inlet and an outlet, wherein the inlet and analysis chamber are adapted such that, in use, liquid sample is drawn into the inlet through capillary action and vapourised therein, the vapourised liquid sample remaining in the gas phase within the inlet and the analysis chamber The apparatus may be attached to a process conduit or vessel containing a source of the liquid for analysis, making it suitable for collecting on-line spectra.