Real-Time Monitoring System for Shelf Life Estimation of Fruit and Vegetables

Recent advances in artificial intelligence towards the sustainable future of agri-food industry

Artificial intelligence has the potential to alter the agricultural and food processing industries, with significant ramifications for sustainability and global food security. The integration of artificial intelligence in agriculture has witnessed a significant uptick in recent years. Therefore, comprehensive understanding of these techniques is needed to broaden its application in agri-food supply chain. In this review, we explored cutting-edge artificial intelligence methodologies with a focus on machine learning, neural networks, and deep learning. The application of artificial intelligence in agri-food industry and their quality assurance throughout the production process is thoroughly discussed with an emphasis on the current scientific knowledge and future perspective. Artificial intelligence has played a significant role in transforming agri-food systems by enhancing efficiency, sustainability, and productivity. Many food industries are implementing the artificial intelligence in modelling, prediction, control tool, sensory evaluation, quality control, and tackling complicated challenges in food processing. Similarly, artificial intelligence applied in agriculture to improve the entire farming process, such as crop yield optimization, use of herbicides, weeds identification, and harvesting of fruits. In summary, the integration of artificial intelligence in agri-food systems offers the potential to address key challenges in agriculture, enhance sustainability, and contribute to global food security.

Enhancement of Strawberry Shelf Life via a Multisystem Coating Based on Lippia graveolens Essential Oil Loaded in Polymeric Nanocapsules

Strawberries (Fragaria xannanasa) are susceptible to mechanical, physical, and physiological damage, which increases their incidence of rot during storage. Therefore, a method of protection is necessary in order to minimize quality losses. One way to achieve this is by applying polymer coatings. In this study, multisystem coatings were created based on polymer nanocapsules loaded with Lippia graveolens essential oil, and it was found to have excellent optical, mechanical, and water vapor barrier properties compared to the control (coating formed with alginate and with nanoparticles without the essential oil). As for the strawberries coated with the multisystem formed from the polymer nanocapsules loaded with the essential oil of Lippia graveolens, these did not present microbial growth and only had a loss of firmness of 17.02% after 10 days of storage compared to their initial value. This study demonstrated that the multisystem coating formed from the polymer nanocapsules loaded with the essential oil of Lippia graveolens could be a viable alternative to preserve horticultural products for longer storage periods.

Advancement of non-destructive spectral measurements for the quality of major tropical fruits and vegetables: a review

The quality of tropical fruits and vegetables and the expanding global interest in eating healthy foods have resulted in the continual development of reliable, quick, and cost-effective quality assurance methods. The present review discusses the advancement of non-destructive spectral measurements for evaluating the quality of major tropical fruits and vegetables. Fourier transform infrared (FTIR), Near-infrared (NIR), Raman spectroscopy, and hyperspectral imaging (HSI) were used to monitor the external and internal parameters of papaya, pineapple, avocado, mango, and banana. The ability of HSI to detect both spectral and spatial dimensions proved its efficiency in measuring external qualities such as grading 516 bananas, and defects in 10 mangoes and 10 avocados with 98.45%, 97.95%, and 99.9%, respectively. All of the techniques effectively assessed internal characteristics such as total soluble solids (TSS), soluble solid content (SSC), and moisture content (MC), with the exception of NIR, which was found to have limited penetration depth for fruits and vegetables with thick rinds or skins, including avocado, pineapple, and banana. The appropriate selection of NIR optical geometry and wavelength range can help to improve the prediction accuracy of these crops. The advancement of spectral measurements combined with machine learning and deep learning technologies have increased the efficiency of estimating the six maturity stages of papaya fruit, from the unripe to the overripe stages, with F1 scores of up to 0.90 by feature concatenation of data developed by HSI and visible light. The presented findings in the technological advancements of non-destructive spectral measurements offer promising quality assurance for tropical fruits and vegetables.

Colorimetric Paper Sensor for Food Spoilage Based on Biogenic Amine Monitoring

Biogenic amines (BAs), nitrogenous molecules usually present in different foods, can be considered an indicator of freshness and food quality since their amount increases during food spoilage. Their detection, possibly in real time via the use of smart packaging, is therefore of crucial importance to ensure food safety and to fulfill consumers' demand. To this end, colorimetric sensors are considered one of the most feasible solutions. Here, we report a user-friendly colorimetric sensing paper able to detect BAs via the naked eye. The sensing molecule is the aglycone genipin, a natural cross-linking agent extracted from gardenia fruit, able to bind BAs producing water-soluble blue pigments. The paper sensor was applied to chicken meat quality monitoring and a quantitative analysis was performed with image acquisition via a smartphone camera, achieving a limit of detection equivalent to 0.1 mM of putrescine. The suitability of the BA sensing paper was assessed by integrating the sensor into smart packaging and analyzing commercial chicken meat samples stored at different temperatures; the results of the sensor paralleled the "best before date" indicated on the label, confirming the potential applicability of the sensor as a smart label.

Sustainable food cold chain logistics: From microenvironmental monitoring to global impact

Food cold chain logistics (FCCL) is a systematic engineering process involving the use of a low-temperature environment to maintain the quality and safety of perishable food and reduce food loss and waste (FLW). From a mechanism perspective, FCCL must balance resource costs for a required level of food quality and safety with the costs of greenhouse gas (GHG) emissions. In the context of global warming, the sustainability trade-off between FLW and environmental impact has recently become an important topic in research on efficient, green FCCL. This is mainly reflected in technological innovation, management optimization, and policy responses. With a focus on three levels (micro, meso, macro), this review analyzes current research areas and the gaps and challenges of FCCL in microenvironmental monitoring, life cycle assessment (LCA), and global impact. Future trends pertaining to FCCL in technology, management, and industry and sustainable development are also summarized. Future trends involving sustainable FCCL must be intelligent, systematic, and low carbon. Industry empowerment through next-generation information technologies (e.g., IoT, AI, big data, blockchain) will promote the multidimensional perception, real-time information transmission, and sustainable control of microenvironmental monitoring, as well as support LCA management transformation from fragmentation to system integration. From a macro level, due to the serious global loss of perishable food, the FCCL scale demand is growing greatly, causing a huge environmental burden. Global cooperation, low-carbon consensus, and appropriate policies will become the basis for promoting sustainable FCCL development.

Ambient Parameter Monitoring in Fresh Fruit and Vegetable Supply Chains Using Internet of Things-Enabled Sensor and Communication Technology

Up to half of the global fruit and vegetable production is wasted or lost along the supply chain, causing wastage of resources and economic losses. Ambient parameters strongly influence quality and shelf life of fresh fruit and vegetables. Monitoring these parameters by using Internet of things (IoT)-enabled sensor and communication technology in supply chains can help to optimize product qualities and hence reduce product rejections and losses. Various corresponding technical solutions are available, but the diverse characteristics of fresh plant-based produce impede establishing valuable applications. Therefore, the aim of this review is to give an overview of IoT-enabled sensor and communication technology in relation to the specific quality and spoilage characteristics of fresh fruit and vegetables. Temperature, relative humidity (RH), O₂, CO₂ and vibration/shock are ambient parameters that provide most added value regarding product quality optimization, and can be monitored by current IoT-enabled sensor technology. Several wireless communication technologies are available for real-time data exchange and subsequent data processing and usage. Although many studies investigate the general possibility of monitoring systems using IoT-enabled technology, large-scale implementation in fresh fruit and vegetable supply chains is still hindered by unsolved challenges.

Postharvest UV-B and Photoperiod with Blue + Red LEDs as Strategies to Stimulate Carotenogenesis in Bell Peppers

Background: Our objective was to evaluate carotenoid accumulation in bell peppers during shelf life under different light conditions. Methods: Fruit stored for 6 d at 7 °C received a 9 kJ m−2 UV-B treatment, while non-UV-treated were used as control (CTRL). Subsequently, all peppers were disposed for a retail sale period of 4 d at 20 °C with a photoperiod of 14 h under fluorescent light (FL) + 10 h under darkness (D), FL, or blue + red LEDs (BR LED). Results: Total antioxidant capacity (TAC) was increased by the UV-B treatment and the photoperiods supplemented with FL and BR LED, which was directly related to the carotenoid content. In fact, CTRL peppers (225 mg β-carotene kg−1) under FL+BR LED showed an increase of ~33% of 13-cis-β-carotene, ~24% of all-trans-β-carotene, and ~27.5% of 9-cis-β-carotene compared to FL + D and FL + FL. Capsaicinoids showed an increase by ~22%, ~38%, and ~27% in the content of capsanthin, capsanthin laurate, and capsanthin esters, respectively, after the UV-B treatment, which was even enhanced after the LED-supplemented photoperiod by ~18% compared to FL+D. Conclusions: Illumination with BR LEDs + UV-B during the retail sale period nights is recommended to increase the bioactive content of bell peppers via carotenoid accumulation to 270 mg β-carotene kg−1.