It has been estimated that one-third of global food is lost or wasted, entailing significant environmental, economic, and social costs. The scale and impact of food loss and waste (FLW) has attracted significant interest across sectors, leading to a relatively recent proliferation of publications. This article synthesizes existing knowledge in the literature with a focus on FLW measurement, drivers, and solutions. We apply the widely adopted DPSIR (Driver-Pressure-State-Impact-Response) framework to structure the review. Key takeaways include the following: Existing definitions of FLW are inconsistent and incomplete, significant data gaps remain (by food type, stage of supply chain, and region, especially for developing countries), FLW solutions focus more on proximate causes rather than larger systemic drivers, and effective responses to FLW will require complementary approaches and robust evaluation.

Groundwater is a crucial natural resource that varies in quality and quantity across Bangladesh. Increased population and urbanization place enormous demands on groundwater supplies, reducing both their quality and quantity. This research aimed to delineate the groundwater potential zone in the Gazipur district, Bangladesh, by integrating eleven thematic layers. Data and information were gathered from Landsat 8, the digital elevation model, the google earth engine, and several ancillary sources. A multi-criterion decision-making (MCDM) based analytical hierarchy process (AHP) was used in a GIS platform to estimate the groundwater potential index. The potential index values were finally classified into five sub-groups: very low, low, moderate, high, and very high to generate a groundwater water potential zone (GWPZ) map. The results show that groundwater potential in about 0.002% (0.026 km²) of the area is very low, 3.83% (63.18 km²) of the area is low, 56.2% (927.05 km²) of the area is medium, 39.25% (647.46 km²) of the area is high, and the rest 0.72% (11.82 km²) of the area is very high. The validation of GWPZ maps based on the groundwater level data at 20 observation wells showed an overall accuracy of 80%. In addition, the ROC curve showed 84% accuracy of GWPZ maps when validated with water inventory points across the study region. Overall, this study presents an easy and practical approach for identifying groundwater potential zones, which may help improve planning and sustainable groundwater resource management.

Currently, optical imaging techniques are extensively employed to automatically sort agricultural products based on various quality parameters such as size, shape, color, ripeness, sugar content, and acidity. This methodological review article examined different machine vision techniques, with a specific focus on exploring the potential of fluorescence imaging for non-destructive assessment of agricultural product quality attributes. The article discussed the concepts and methodology of fluorescence, providing a comprehensive understanding of fluorescence spectroscopy and offering a logical approach to determine the optimal wavelength for constructing an optimized fluorescence imaging system. Furthermore, the article showcased the application of fluorescence imaging in detecting peel defects in a diverse range of citrus as an example of this imaging modality. Additionally, the article outlined potential areas for future investigation into fluorescence imaging applications for the quality assessment of agricultural products.

Near-infrared (NIR) spectroscopy has been used to non-destructively and rapidly evaluate the quality of fresh agricultural produce. In this study, two commercially available portable spectrometers (F-750: Felix Instruments, WA, USA; and SCiO: Consumer Physics, Tel Aviv, Israel) were evaluated in the wavelength range between 740 and 1070 nm to non-invasively predict quality attributes, including the dry matter (DM), and total soluble solids (TSS) content of three fresh table grape cultivars (‘Autumn Royal’, ‘Timpson’, and ‘Sweet Scarlet’) and one peach cultivar (‘Cassie’). Prediction models were developed using partial least-square regression (PLSR) to correlate the NIR absorbance spectra with the invasive quality measurements. In regard to grapes, the best DM prediction models yielded an R² of 0.83 and 0.81, a ratio of standard error of performance to standard deviation (RPD) of 2.35 and 2.29, and a root mean square error of prediction (RMSEP) of 1.40 and 1.44; and the best TSS prediction models generated an R² of 0.97 and 0.95, an RPD of 5.95 and 4.48, and an RMSEP of 0.53 and 0.70 for the F-750 and SCiO spectrometers, respectively. Overall, PLSR prediction models using both spectrometers were promising to predict table grape quality attributes. Regarding peach, the PLSR prediction models did not perform as well as in grapes, as DM prediction models resulted in an R² of 0.81 and 0.67, an RPD of 2.24 and 1.74, and an RMSEP of 1.28 and 1.66; and TSS resulted in an R² of 0.62 and 0.55, an RPD of 1.55 and 1.48, and an RMSEP of 1.19 and 1.25 for the F-750 and SCiO spectrometers, respectively. Overall, the F-750 spectrometer prediction models performed better than those generated by using the SCiO spectrometer data.

Introduction. High fiber bakery products can be a healthy snack option for consumers. Our study focused on the effect of replacing wheat flour with okara flour on the physicochemical, nutritional, textural, and sensory attributes of biscuits. Study objects and methods. We used 2, 4, 6, and 8% w/w okara flour to prepare biscuits. Refined wheat flour (control), mixed flour (okara and wheat flour), dough, and biscuits were assessed for physicochemical, textural, and nutritional properties, as well as sensory characteristics. The volume of particles was higher in 8% okara flour (145 μm) compared to refined wheat flour (91 μm). Results and discussion. 2, 4, 6, and 8% w/w okara flour biscuits showed significantly (P ≤ 0.05) lower spread ratio and weight loss than biscuits from wheat flour. Hardness, stickiness, and cohesiveness of 2, 4, 6, and 8% okara flour dough were significantly (P ≤ 0.05) lower compared to the control, resulting in decreased cutting strength and increased hardness of okara flour biscuits. Moisture, protein, ash, fat, and crude fiber contents of 2, 4, 6, and 8% okara biscuits were significantly (P ≤ 0.05) higher compared to the control biscuits. The sensory evaluation suggested that 4% okara biscuits had higher consumer acceptability and were superior to the control and other okara biscuits. Conclusion. Mixed flour biscuits made from okara and wheat flours were superior in physicochemical, nutritional, textural, and sensory attributes, which allows considering them as an alternative healthy snack.