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It is our pleasure to present this Special Issue of Molecules entitled “Food Processing and Its Impact on Phenolic and other Bioactive Constituents in Food”. Bioactive compounds including phenolic ingredients have long been used as important constituents of a healthy diet. As a result, consumer awareness about the important role of high-quality products rich in bioactive compounds—especially phenolic compounds—in human nutrition, health, and prevention against diseases has increased. Additionally, methods for food processing, regardless of the technology used, have a huge impact on the quality of the final products. Therefore, the big challenges for scientists lie in the monitoring of changes during food processing and the optimization of technology to achieve the minimal degradation of nutrients (including phenolic compounds). Thus, for this Special Issue, I encourage you to read some interesting papers aimed at bringing the latest scientific news, insights, and advances in the field of food processing and its impact on bioactive constituents in food, especially phenolic compounds. The information presented will certainly arouse considerable interest among a large group of our readers from different disciplines and research fields.

apple --- phenolic compounds --- genetic resources --- HPLC-DAD --- thyme --- oregano --- dry herbs --- polyphenols --- chlorophyll --- carotenoids --- microbial --- cytotoxicity --- dissolution test --- functional food --- innovative food --- drying --- natural food --- Helianthus tuberosus --- pro-healthy properties --- plant polyphenols --- food processing --- phenolic content --- bioavailability --- bioaccessibility --- coffee Arabica --- roasting process --- brewing methods --- antioxidant activity --- flavonoids --- caffeine --- pH of infusions --- tannins --- snack --- baking --- carotenoids content --- chlorophyll content --- total polyphenols content --- calorific value --- sensory properties --- sourdough fermentation --- inoculation --- lactic acid bacteria --- FODMAP --- fructans --- antioxidants --- chocolate --- free radical scavenging activity --- reducing power --- functionalization of food --- electronic nose analysis --- isoflavone conversion --- thermal process --- immature seeds --- mature seeds --- internal water content --- konjac --- linseed flour --- fat substitute --- volatile compounds --- lipid oxidation --- encapsulation --- Mauritia flexuosa (aguaje) --- controlled dehydration

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Unmanned aerial vehicles (UAVs) are new platforms that have been increasingly used in the last few years for forestry applications that benefit from the added value of flexibility, low cost, reliability, autonomy, and capability of timely provision of high-resolution data. The main adopted image-based technologies are RGB, multispectral, and thermal infrared. LiDAR sensors are becoming commonly used to improve the estimation of relevant plant traits. In comparison with other permanent ecosystems, forests are particularly affected by climatic changes due to the longevity of the trees, and the primary objective is the conservation and protection of forests. Nevertheless, forestry and agriculture involve the cultivation of renewable raw materials, with the difference that forestry is less tied to economic aspects and this is reflected by the delay in using new monitoring technologies. The main forestry applications are aimed toward inventory of resources, map diseases, species classification, fire monitoring, and spatial gap estimation. This Special Issue focuses on new technologies (UAV and sensors) and innovative data elaboration methodologies (object recognition and machine vision) for applications in forestry.

unmanned aerial vehicles --- seedling detection --- forest regeneration --- reforestation --- establishment survey --- machine learning --- multispectral classification --- UAV photogrammetry --- forest modeling --- ancient trees measurement --- tree age prediction --- Mauritia flexuosa --- semantic segmentation --- end-to-end learning --- convolutional neural network --- forest inventory --- Unmanned Aerial Systems (UAS) --- structure from motion (SfM) --- Unmanned Aerial Vehicles (UAV) --- Photogrammetry --- Thematic Mapping --- Accuracy Assessment --- Reference Data --- Forest Sampling --- Remote Sensing --- Robinia pseudoacacia L. --- reproduction --- spreading --- short rotation coppice --- unmanned aerial system (UAS) --- object-based image analysis (OBIA) --- convolutional neural network (CNN) --- juniper woodlands --- ecohydrology --- remote sensing --- unmanned aerial systems --- central Oregon --- rangelands --- seedling stand inventorying --- photogrammetric point clouds --- hyperspectral imagery --- leaf-off --- leaf-on --- UAV --- multispectral image --- forest fire --- burn severity --- classification --- precision agriculture --- biomass evaluation --- image processing --- Castanea sativa --- unmanned aerial vehicles (UAV) --- precision forestry --- forestry applications --- RGB imagery

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• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Unmanned aerial vehicles (UAVs) are new platforms that have been increasingly used in the last few years for forestry applications that benefit from the added value of flexibility, low cost, reliability, autonomy, and capability of timely provision of high-resolution data. The main adopted image-based technologies are RGB, multispectral, and thermal infrared. LiDAR sensors are becoming commonly used to improve the estimation of relevant plant traits. In comparison with other permanent ecosystems, forests are particularly affected by climatic changes due to the longevity of the trees, and the primary objective is the conservation and protection of forests. Nevertheless, forestry and agriculture involve the cultivation of renewable raw materials, with the difference that forestry is less tied to economic aspects and this is reflected by the delay in using new monitoring technologies. The main forestry applications are aimed toward inventory of resources, map diseases, species classification, fire monitoring, and spatial gap estimation. This Special Issue focuses on new technologies (UAV and sensors) and innovative data elaboration methodologies (object recognition and machine vision) for applications in forestry.

Research & information: general --- Biology, life sciences --- Forestry & related industries --- unmanned aerial vehicles --- seedling detection --- forest regeneration --- reforestation --- establishment survey --- machine learning --- multispectral classification --- UAV photogrammetry --- forest modeling --- ancient trees measurement --- tree age prediction --- Mauritia flexuosa --- semantic segmentation --- end-to-end learning --- convolutional neural network --- forest inventory --- Unmanned Aerial Systems (UAS) --- structure from motion (SfM) --- Unmanned Aerial Vehicles (UAV) --- Photogrammetry --- Thematic Mapping --- Accuracy Assessment --- Reference Data --- Forest Sampling --- Remote Sensing --- Robinia pseudoacacia L. --- reproduction --- spreading --- short rotation coppice --- unmanned aerial system (UAS) --- object-based image analysis (OBIA) --- convolutional neural network (CNN) --- juniper woodlands --- ecohydrology --- remote sensing --- unmanned aerial systems --- central Oregon --- rangelands --- seedling stand inventorying --- photogrammetric point clouds --- hyperspectral imagery --- leaf-off --- leaf-on --- UAV --- multispectral image --- forest fire --- burn severity --- classification --- precision agriculture --- biomass evaluation --- image processing --- Castanea sativa --- unmanned aerial vehicles (UAV) --- precision forestry --- forestry applications --- RGB imagery