Potato protein: current review of structure, technological properties, and potential application on spray drying microencapsulation.

Studies regarding spray drying microencapsulation are aplenty available; especially focusing on processing parameters, microparticle characteristics and encapsulation efficiency. Hence, there is a rising interest in tailoring wall materials aiming to improve the process's effectiveness. Reflecting a market trend in the food industry, plant-based proteins are emerging as alternative protein sources, and their application adaptability is an increasing research of interest related to consumers' demand for healthy food, product innovation, and sustainability. This review presents a perspective on the investigation of potato protein as a technological ingredient, considering it a nonconventional source obtained as by-product from starch industry. Furthermore, this piece emphasizes the potential application of potato protein as wall material in spray drying encapsulation, considering that this purpose is still limited for this ingredient. The literature reports that vegetal-based proteins might present compromised functionality due to processing conditions, impairing its technological application. Structural modification can offer a potential approach to modify potato protein configuration aiming to improve its utilization. Studies reported that modified proteins can perform as better emulsifiers and antioxidant agents compared to intact proteins. Hence, it is expected that their use in microencapsulation would improve process efficiency and protection of the core material, consequently delivering superior encapsulation performance.

Automated Machine Learning: A Case Study of Genomic "Image-Based" Prediction in Maize Hybrids.

Machine learning methods such as multilayer perceptrons (MLP) and Convolutional Neural Networks (CNN) have emerged as promising methods for genomic prediction (GP). In this context, we assess the performance of MLP and CNN on regression and classification tasks in a case study with maize hybrids. The genomic information was provided to the MLP as a relationship matrix and to the CNN as "genomic images." In the regression task, the machine learning models were compared along with GBLUP. Under the classification task, MLP and CNN were compared. In this case, the traits (plant height and grain yield) were discretized in such a way to create balanced (moderate selection intensity) and unbalanced (extreme selection intensity) datasets for further evaluations. An automatic hyperparameter search for MLP and CNN was performed, and the best models were reported. For both task types, several metrics were calculated under a validation scheme to assess the effect of the prediction method and other variables. Overall, MLP and CNN presented competitive results to GBLUP. Also, we bring new insights on automated machine learning for genomic prediction and its implications to plant breeding.

Impact of capsaicin on aroma release: in vitro and in vivo analysis.

Capsaicin is the main bioactive compound in chili pepper that leads to the perception of "spiciness". However, the effect of capsaicin on aroma release in the nose remains unexplained. This is the first study designed to measure capsaicin's impact on aroma release during consumption. In vitro studies, using static headspace analysis by atmospheric pressure chemical ionization-mass spectrometry (APCI-MS), showed no impact of capsaicin (5 ppm) on the gas-liquid partitioning equilibria of a range of aroma compounds. However, a significant reduction in aroma release was observed in vivo, during oral melting of a model ice cube system (p < 0.05) included 5 ppm capsaicin. The total release of aroma into the nasal cavity was decreased, such that only 49% of 3-methylbutanal, 60% of 1-octen-3-ol and 83% of linalool was released. This is the first evidence of capsaicin's reduction effect on aroma release during consumption. It was also found that 5 ppm capsaicin increased saliva secretion by 75%, which may have led to the dilution of aroma compounds in the mouth and directly impacted the aroma release into the nasal cavity. The most hydrophilic compound (3-methylbutanal) was affected by capsaicin to a greater extent than the hydrophobic compound (linalool), the solvent effect of the additional saliva may explain this.