Precise canopy management is critical in vineyards for premium wine production because maximum crop load does not guarantee the best economic return for wine producers. The growers keep track of the number of grape bunches during the entire growing season for optimizing crop load per vine. Manual counting of grape bunches can be highly labor-intensive and error prone. Thus, an integrated, novel detection model, Swin-transformer-YOLOv5, was proposed for real-time wine grape bunch detection. The research was conducted on two varieties of Chardonnay and Merlot from July to September 2019. The performance of Swin-T-YOLOv5 was compared against commonly used detectors. All models were comprehensively tested under different conditions, including two weather conditions, two berry maturity stages, and three sunlight intensities. The proposed Swin-T-YOLOv5 outperformed others for grape bunch detection, with mean average precision (mAP) of up to 97% and F1-score of 0.89 on cloudy days. This mAP was ~44%, 18%, 14%, and 4% greater than Faster R-CNN, YOLOv3, YOLOv4, and YOLOv5, respectively. Swin-T-YOLOv5 achieved an R² of 0.91 and RMSE of 2.4 (number of grape bunches) compared with the ground truth on Chardonnay. Swin-T-YOLOv5 can serve as a reliable digital tool to help growers perform precision canopy management in vineyards.

Fish and fishery products are among the most important sources of nutritional components for human health, including high-quality proteins, essential vitamins, minerals, and healthy polyunsaturated fatty acids. Fish farming and processing technologies are continuously evolving to improve and enhance the appearance, yield, and quality of fish and fish products from farm to fork throughout the fish supply chain, including growth, postharvest, treatment, storage, transportation, and distribution. Processing of fish involves a period of food withdrawal, collection and transportation, the process of stunning, bleeding, chilling, cutting, packaging, and byproduct recycling. Cutting is a set of crucial operations in fish processing to divide the whole fish into smaller pieces for producing fish products (e.g., fish fillets, steaks, etc.). Various techniques and machinery have been introduced in the field to advance and automate cutting operations. This review aims to provide a comprehensive review of fish cutting techniques, machine vision and artificial intelligence applications, and future directions in fish industries. This paper is expected to stimulate research on enhancing fish cutting yield, product diversity, safety and quality, as well as providing advanced solutions for engineering problems encountered in the fish industry.

As a relatively new material deployed in additive manufacturing (AM), silicone and its composites have the potential to realize tunable functionality and heterogeneous, architected properties for a number of applications requiring low modulus, elastic materials. Continuous fiber reinforced composites have been developed for AM to achieve various complex structures that are lightweight with high mechanical properties. AM of silicone‐based composites with direct ink writing (DIW) technology has potential application in medical devices, gasket components, flexible soft electronics, and food packaging. However, DIW printed materials have mechanical anisotropy since the extrusion‐based printing process creates small changes in geometry during the material deposition process. In addition, silicone elastomers are relatively low modulus in tension and can be reinforced with woven cloth or fibers. In this work, a continuous fiber AM machine is developed to manufacture silicone composite structures with continuous fiber reinforcing the printed silicone. Tensile tests show that the anisotropic property of the perpendicular printed specimens, relative to the tension direction, has been significantly improved by continuous carbon fiber reinforcements. This continuous fiber silicone reinforcement printing technique can be applied to tune fiber volume ratios and orientations for different silicone composite structures to meet the desired strength and stiffness.

Additive manufacturing (AM) is a disruptive manufacturing process that gives designers freedom to create highly complex shapes through free‐form fabrication. The majority of polymers used in extrusion AM are thermoplastics because they are easy to process in affordable machines. While there are a number of moderate modulus thermoplastics in regular use in AM, thermoplastics are known to weaken with increases in temperature or exposure to solvents and many commodity thermoplastics used in AM are brittle. On the other hand, there are few elastomers, and even fewer elastomer reinforcement schemes, that are accessible using standard AM technologies. In this work, we report a novel dual extrusion process that integrates elastomeric silicone with reinforcing thermoplastic. By developing and demonstrating a dual extrusion 3D printer that can process common thermoplastics with commercially available thermosetting silicones, new types of composite elastomers are reported with good mechanical performance. The 0°/20°/−20° grid pattern thermoplastic reinforced samples achieved 2.5 MPa tensile strength in low extension region (0.5 strain), which improves the initial stiffness of the composite component. Desired mechanical responses of composite structures can be realized by tuning the reinforcement volume ratio and infill percentages, and applying various types of reinforcement mesh patterns and thermoplastics. Highlights: A dual extrusion process integrates fus filament fabrication and direct ink writing technologies. Thermoplastic reinforced silicone composite with stiff/soft properties. Tunable volume ratio, infill percentage, mesh pattern, and material option.

Additive manufacturing (AM) methods such as fused filament fabrication (FFF) and direct ink writing (DIW) enable the free-form design and printing of complex architectures using a range of materials. Compared with traditional manufacturing technologies, AM methods are highly automated to reduce waste, assembly costs, and processing errors. By combining different AM deposition methods, we can fabricate composite materials with desired spatial arrangements and anisotropies to meet unique design requirements and to produce integrated multi-material components that are not easily manufactured by traditional strategies. To address a wide variety of mechanical performance requirements, developing hybrid AM technologies into a low-cost, fully-automated manufacturing process can realize a number of new types of elastomer composite architectures. In this work, FFF and DIW methods have been combined to fabricate thermoplastic polyurethane (TPU) reinforced silicone composite materials. Several specimens with different silicone and TPU infill patterns have been designed to characterize the mechanical compression responses of these structures. With 40–80% infill percentages of silicone and 20–60% infill percentages of TPU, composites specimens can be designed to get any specified compression response between 600 N and 9000 N. This TPU-reinforced silicone printing technique can be applied for silicone composite architecture design in a wide range of applications that require tunable elastic responses.