Search Results (117)

Produce supply chains play a critical role in ensuring fruits and vegetables reach consumers efficiently, affordably, and at optimal freshness. In recent decades, hub-and-spoke network models have emerged as valuable tools for optimizing sustainable cold food supply chains. Traditional optimization efforts typically focus on removing inefficiencies, minimizing lead times, refining inventory management, strengthening supplier relationships, and leveraging technological advancements for better visibility and control. However, the majority of models rely on deterministic approaches that overlook the inherent uncertainties of crop yields, which are further intensified by climate variability. Rising atmospheric CO₂ concentrations, along with shifting temperature patterns and extreme weather events, have a substantial effect on crop productivity and availability. Such uncertainties can prompt distributors to seek alternative sources, increasing costs due to supply chain reconfiguration. This research introduces a stochastic hub-and-spoke network optimization model specifically designed to minimize transportation expenses by determining optimal distribution routes that explicitly account for climate variability effects on crop yields. A use case involving a cold food supply chain (CFSC) was carried out using several weather scenarios based on climate models and real soil data for California. Strawberries were selected as a representative crop, given California’s leading role in strawberry production. Simulation results show that scenarios characterized by increased rainfall during growing seasons result in increased yields, allowing distributors to reduce transportation costs by sourcing from nearby farms. Conversely, scenarios with reduced rainfall and lower yields require sourcing from more distant locations, thereby increasing transportation costs. Nonetheless, supply chain configurations may vary depending on the choice of climate models or weather prediction sources, highlighting the importance of regularly updating scenario inputs to ensure robust planning. This tool aids decision-making by planning climate-resilient supply chains, enhancing preparedness and responsiveness to future climate-related disruptions. Full article

In today’s volatile supply chain environment, organizations require flexible and collaborative procurement strategies. Swap contracts, originally developed as financial instruments, have recently been adopted to address inventory imbalances—such as the 2021 COVID-19 vaccine swap between South Korea and Israel. Despite its increasing adoption in the real world, theoretical studies on swap-based procurement remain limited. This study proposes an integrated model that combines buyer-to-buyer swap agreements with long-term wholesale contracts under demand uncertainty. The model quantifies the expected swap quantity between parties and embeds it into the profit function to derive optimal order quantities. Numerical experiments are conducted to compare the performance of the proposed strategy with that of a baseline wholesale contract. Sensitivity analyses are performed on key parameters, including demand asymmetry and swap prices. The numerical analysis indicates that the swap-integrated procurement strategy consistently outperforms procurement based on long-term wholesale contracts. Moreover, the results reveal that under the swap-integrated strategy, the optimal order quantity must be adjusted—either increased or decreased—depending on the demand scale of the counterpart and the specified swap price, deviating from the optimal quantity under traditional long-term contracts. These findings highlight the potential of swap-integrated procurement strategies as practical coordination mechanisms across both private and public sectors, offering strategic value in contexts such as vaccine distribution, fresh produce, and other critical products. Full article

The use of microwaves (MWs) has been proposed as an energy-efficient method for reducing checking. Along with understanding moisture distribution, it is essential to consider structural characteristics to explain how MWs reduce checking. The influence of MWs on these characteristics depends on the food matrix’s dielectric and viscoelastic properties, which vary significantly between fresh and pre-baked dough. This study investigates the effects of MW treatment applied before (MW-O) or after conventional oven baking (O-MW) on low-fat biscuits that are prone to checking. Color (CIELab), thickness, moisture content and distribution, checking rate, texture, sensory properties, energy consumption and baking time were analyzed. The findings suggest that MWs reduce checking rate by eliminating internal moisture differences, while also changing structural properties, as evidenced by increased thickness and hardness. MW-O eliminated checking (control samples showed 100%) but negatively affected color, texture (increased hardness and breaking work), and sensory quality. The O-MW checking rate (3.41%) was slightly higher than in MW-O, probably due to the resulting different structural properties (less thickness, less hardness and breaking work). O-MW biscuits were the most preferred by consumers (54.76% ranked them first), with color and texture close to the control samples. MW-O reduced total energy consumption by 16.39% and baking time by 25.00%. For producers, these improvements could compensate for the lower biscuit quality. O-MW did not affect energy consumption but reduced baking time by 14.38%. The productivity improvement, along with the reduction in checking and the satisfactory sensory quality, indicates that O-MW could be beneficial for the bakery sector. Full article

Despite the economic importance of Protected Designation of Origin (PDO) cheeses in Italy, little research has examined how label attributes affect price premiums. For Italian cheese producers, especially those investing in PDO certification, understanding which attributes generate premiums is crucial for sustainable business strategies. This study examined attributes displayed on 420 validated cheese labels collected across Italy in 2022, focusing on hard cheese, fresh soft cheese, and string cheese. A content analysis was conducted to identify and categorize the attributes displayed on cheese labels. Following this, the hedonic pricing method, supported by multiple linear regression analysis, was used to assess the impact of these attributes—along with brand and distribution channel—on product pricing. Our findings reveal that sustainability attributes show particularly strong effects on price premiums. PDO certification generates significant premiums prominently for hard and fresh soft cheeses, cow breed information for string cheese, while specialized retail channels create higher prices for fresh soft and string cheeses. While brand–price relationships are heterogeneous, the study provides evidence of their impact. These insights enable cheese producers, marketers, and retailers to strategically prioritize product attributes, optimize distribution channels, and make informed decisions about brand positioning to maximize value in competitive cheese markets. Full article

Mineral nutrition management in sweet cherry orchards remains a critical challenge due to the lack of site-specific fertilization guidelines, particularly in Greece, a significant cherry-producing country. This study aimed to develop a predictive framework for total nutrient losses in sweet cherry orchards by proposing simplified estimations using fresh fruit yield as the sole input variable. Field experiments were conducted in two orchards with distinct rootstocks (MxM 14 and CAB-6P), analyzing soil properties, leaf nutrient status, and uptake patterns on different plant components. Results indicated that despite differences in soil texture and pH, nutrient availability was generally sufficient, with only Fe and Zn marginally below optimal levels in leaf tissue. Principal Component Analysis (PCA) revealed distinct nutrient distribution patterns, with N evenly distributed across fruits, peduncles, and prunings, while K was concentrated in fruits and peduncles, and Ca and Mg predominantly in fallen leaves. Notably, K was redistributed from leaves to fruits under high yields, evidenced by negative correlations between leaf biomass and K uptake. Strong relationships (r² > 0.8) were found between fresh fruit yield and uptake of N, P, K, Mg, B, and Cu, enabling reliable predictions of total nutrient losses. Estimated annual nutrient removals were 85.6 kg ha⁻¹ N, 8.94 kg ha⁻¹ P, 42.7 kg ha⁻¹ K, and 12.0 kg ha⁻¹ Mg, with significant fractions retained in prunings and fallen leaves (e.g., 51.8 kg ha⁻¹ N, 6.2 kg ha⁻¹ P). The developed yield-based models provide a practical tool for optimizing fertilization strategies, while our findings highlight the potential for nutrient recycling through sustainable residue management. Full article

A study was conducted in Sierra Leone to identify cassava plants that are asymptomatic and symptomatic to cassava mosaic disease (CMD) and collect planting materials for field trial establishment; determine the prevalence of CMD caused by African cassava mosaic virus (ACMV) and East African cassava mosaic virus (EACMV) using the Nuru App and virus indexing techniques; and assess selected agronomic traits in cassava. A total of 80 cassava farms spanning four provinces (Southern, Eastern, Northern, and North-West) were surveyed in April 2022. Findings showed that the cassava variants of the experiment and locations significantly (p < 0.001) affected CMD incidence, severity, growth, and fresh storage root yield traits. The CMD incidence (87.0%) and whitefly abundance (144.8) were highest, and the CMD severity was moderate (4.0) for the plants derived from cuttings obtained from symptomatic Cocoa mother plants, while plants derived from cuttings of improved mother plants exhibited no visible symptoms of the disease and the lowest population (45.1) of whiteflies. The Nuru app is inefficient for phenotypically detecting CMD at 3 months after planting (MAP), while at 6, 9 and 12 MAP, the app efficiently detected the disease using a molecular analysis technique. Resistant, non-diseased plants derived from cuttings obtained from SLICASS 4 mother plants produced the highest fresh storage root yield (54.9 t ha⁻¹). The highest storage root yield loss was recorded in the plants obtained from cuttings of symptomatic variety Cocoa mother plants harvested at Matotoka grassland ecology, Bombali District (90.2%), while those harvested from cuttings of asymptomatic variety Cocoa mother plants grown at the four test environments had a similar storage root yield loss ranging from 40.3 to 46.2%. Findings suggest the importance of genetic variability, environmental adaptation, utilization of diseased-free materials, and phytosanitation as disease management strategies for increased production. These findings provide important insights into the distribution, impact, and spread of CMD and whitefly abundance in the studied areas in Sierra Leone that could be exploited for cassava production, productivity, conservation, and population improvement. Full article

This study aims to assess the drought stress tolerance of germinating seeds of the invasive indehiscent fruit-producing Lepidium species, specifically Lepidium appelianum, Lepidium draba, and the invasive dehiscent fruit-producing L. campestre. Drought stress tolerance experiments were conducted using various concentrations of polyethylene glycol (PEG) following standard protocols. The results revealed that seeds/fruits of L. appelianum and L. draba exhibited significantly higher drought stress tolerance compared to seeds of L. campestre. Fresh seeds and fruits of L. appelianum were capable of germinating under various drought stress treatments, while fresh and after-ripened seeds and fruits of L. draba germinated in every condition except for −0.8 MPa. Conversely, L. campestre fresh seeds did not germinate under the most severe drought stress conditions (−0.6 and −0.8 MPa). It is crucial to note that fresh fruits of L. draba displayed pericarp-mediated chemical dormancy, while fresh seeds of L. campestre demonstrated physiological dormancy. However, fresh seeds and fruits of L. appelianum did not exhibit any dormancy. This study suggests that germinating seeds and fruits of L. appelianum demonstrate the strongest tolerance to drought stress, while L. draba exhibits moderate tolerance. On the contrary, L. campestre seeds display the least tolerance to drought stress. The differences in drought stress tolerance among the studied Lepidium species reflect the climatic facets in their native distribution areas. Given the potential high invasiveness associated with the drought stress tolerance of L. appelianum and L. draba, it is imperative to develop special control strategies to manage these invasive species in the face of future climate change. Full article

In this study, we investigated the effects of mortar milling conditions on the quality and noodle-processing suitability of whole-wheat flours (WWFs). The WWFs were milled at varying pestle speeds (50 and 130 rpm) and for varying durations (10, 20, 40, and 60 min) and analyzed to determine their particle size distribution, physicochemical properties, dough-mixing characteristics, antioxidant activities, and noodle-making performance. High pestle speed (Group H) produced significantly smaller particle sizes, higher flour temperatures, greater moisture loss, and increased starch damage compared to that produced at low pestle speeds (Group L). Compared with Group L, Group H exhibited higher water and sodium carbonate solvent-retention capacity (SRC) values, increased pasting viscosities, and greater gluten strength owing to finer particles. Total phenolic content increased with reduced particle size, whereas antioxidant activity (ABTS radical scavenging) exhibited inconsistent trends. Fresh noodle properties varied with milling conditions; finer WWF particles improved dough resistance but reduced extensibility when water was adjusted according to water SRC. Thus, WWF particle size strongly influences flour functionality and noodle quality, which highlights the need for precise milling control. This study demonstrates, for the first time, the applicability of a mortar-type mill for producing WWFs, with implications for enhancing WWF functionality. Full article

With the surge in digital farming, real-time quality management of fresh produce has become essential. For apples (Malus domestica Borkh.), consumer demand extends beyond sweetness, texture, and appearance to internal quality factors such as moisture content. Existing non-destructive methods, however, involve costly equipment, complex calibration, and sensitivity to environmental conditions. This study hypothesizes that thermal diffusivity indices derived from surface heating and cooling patterns can accurately predict apple moisture content non-destructively. A total of 823 apples from seven varieties were analyzed using a thermal imaging sensor in a 120-s process comprising 40 s of heating and 80 s of cooling. Key thermal diffusivity indices—minimum, maximum, mean, and max–min values—were extracted and correlated with actual moisture content measured via the drying method. Multiple linear regression and leave-one-out cross-validation confirmed that mean temperature-based models provided the most stable predictions ($R_{CV}^2$ ≥ 0.90 for some varieties). Frame optimization and artificial neural networks further improved prediction accuracy for varieties exhibiting higher variability. The proposed method is cost-effective, requires minimal calibration, and is less affected by surface reflectance, outperforming conventional optical methods (e.g., NIR spectroscopy, hyperspectral imaging), especially regarding robustness against surface reflectance variability and calibration complexity. This offers a practical solution for monitoring apple freshness and quality during sorting and distribution processes, with expanded research on sugar content and acidity expected to accelerate commercialization. Full article

This paper reviews the performance of low-grade calcined clay as a partial substitute for Portland cement in concrete, emphasizing its potential to enhance sustainability in construction. Thermal treatment of naturally occurring clays at optimal temperatures produces amorphous siliceous materials with pozzolanic properties. Clays with substantial kaolinite content exhibit significant pozzolanic reactivity when calcined at temperatures between 700 and 850 °C, with effective firing possible up to 1000 °C. Research shows that replacing Portland cement with calcined clays improves the mechanical and durability properties of concrete, with replacement levels ranging from 10% to 60%, depending on factors such as chemical composition, mineralogy, and reactivity. This paper synthesizes recent findings on low-grade calcined clays with 60–80% purity, which are more abundant, cost-effective, and easier to produce, particularly in developing regions lacking the resources and technology to process high-purity clays (>95% purity). Key aspects explored include calcination methods, optimal firing temperatures, and their effects on particle size distribution and pozzolanic activity. This study also examines the impact of low-grade calcined clay on fresh and hardened concrete and the durability properties of concrete and mortar. By providing a comprehensive analysis, this review highlights the potential of low-grade calcined clays to contribute to more sustainable and durable concrete production, emphasizing the need to optimize calcination processes and fully harness their pozzolanic properties. Full article

Vinegar, frequently distilled by solid fermentation or liquid processes, was generated through the synergistic effect of a microbial community in open or semi-open environments. Based on the studied raw materials, researchers distributed the vinegar into three classes: grain, fruit and animal, with lactic acid bacteria (LAB) playing a pivotal role in their fermentation and contributing significantly to their functional and sensory qualities. Typically, the natural maturation of fresh vinegar necessitates a long period and vast space, engendering a reduced efficiency. To accelerate the vinegar aging process, some physical methods, viz. micro-oxygenation, ozone, ultrasound, microwave, gamma rays, infrared, electric fields and high pressure, have been developed. Produced or enriched by LAB, key bioactive vinegar components are organic acids, phenolic compounds, melanoidins, and tetramethylpyrazine. These active compounds have antibacterial, antioxidant, anti-inflammatory functions; aid in the regulation of liver protection metabolism and glucose control; and have blood pressure, anti-tumor, anti-fatigue and metabolic regulatory effects. The review explores advancements in vinegar production, including modernized fermentation processes and optimized aging techniques, which enhance these beneficial compounds and ensure product consistency and safety. By examining the LAB variety strains and the bioactive profiles of different vinegar types, this study highlights vinegar’s value beyond a culinary product, as a potential therapeutic agent in human nutrition and health. The findings underscore vinegar’s relevance not only in dietary and preventive healthcare but also as a potential functional food ingredient. Further research is needed to explore the mechanisms of action through which LAB contribute to the development of several new healthy vinegars. Full article

Shiga toxin-producing Escherichia coli (STEC) is a foodborne pathogen and known to reside naturally in cattle. The application of untreated biological soil amendments of animal origin on fresh produce fields results in unique food safety challenges. It is critical to identify farm manure management practices to mitigate pre-harvest pathogen contamination. The objective of this study was to quantify the prevalence and level of STEC in cattle manure in the Mid-Atlantic region of the United States. A total of 161 bovine manure samples were collected from 13 cattle farms between 2016 and 2018. The samples were enriched with non-selective and selective media and quantified following a Most-Probable Number (MPN) assay. Among the recovered STEC isolates, PCR was performed to determine the presence of stx, eae, and rfbE. Clermont PCR was performed to identify phylogenetic groups of isolates. Of the 13 farms, 11 had STEC populations between <1.0 and >5.6 log MPN/g. Farm, humidity, and sampling year significantly (p < 0.05) influenced STEC populations in bovine manure. Of the 108 isolates, 50% were stx+ and 14% eae+. Phylogenetic group analysis revealed that 46% of the isolates belonged to group A, 19% to B1, 7% to B2, and 28% to D. Group D had the highest prevalence of stx+ and eae+ and group B1 had the lowest prevalence. Results suggest STEC geographical distribution in the Mid-Atlantic region is farm-specific, and climatic conditions can be critical for its survival and dissemination. Full article

Evapotranspiration (ET) plays a crucial role in the surface water cycle and energy balance, and accurate ET estimation is essential for study in various domains, including agricultural irrigation, drought monitoring, and water resource management. Remote sensing (RS) technology presents an efficient approach for estimating ET at regional scales; however, existing RS retrieval algorithms for ET are intricate and necessitate a multitude of parameters. The land surface temperature–vegetation index (LST-VI) space method and statistical regression by machine learning (ML) offer the benefits of simplicity and straightforward implementation. This study endeavors to identify the optimal long-term sequence LST-VI space method and ML for ET estimation under conditions of limited observed variables, (LST, VI, and near-surface air temperature). A comparative analysis of their performance is undertaken using ground-based flux observations and MOD16 ET data. The findings can be summarized as follows: (1) Long-term remote sensing data can furnish a more comprehensive background field for the LST-VI space, achieving superior fitting accuracy for wet and dry edges, thereby enabling precise ET estimation with the following metrics: correlation coefficient (r) = 0.68, root mean square error (RMSE) = 0.76 mm/d, mean absolute error (MAE) = 0.49 mm/d, and mean bias error (MBE) = −0.14 mm. (2) ML generally produces more accurate ET estimates, with the Random Forest Regressor (RFR) demonstrating the highest accuracy: r = 0.79, RMSE = 0.61 mm/d, MAE = 0.42 mm/d, and MBE = −0.02 mm. (3) Both ET estimates derived from the LST-VI space and ML exhibit spatial distribution characteristics comparable to those of MOD16 ET data, further attesting to the efficacy of these two algorithms. Nevertheless, when compared to MOD16 data, both approaches exhibit varying degrees of underestimation. The results of this study can contribute to water resource management and offer a fresh perspective on remote sensing estimation methods for ET. Full article

Fresh produce, as a primary source of nutrition, plays a pivotal role in daily life. However, the unique characteristics of fresh produce—such as perishability, widespread production, short shelf life, long distribution cycles, and high volatility in both supply and demand—render the fresh produce supply chain particularly vulnerable to disruptions. These vulnerabilities not only impact daily consumption but also pose significant challenges to the operational efficiency of enterprises. Enhancing the fresh produce supply chain resilience is crucial for businesses to effectively mitigate risks, ensure consistent product quality, and maintain overall supply chain stability. Nevertheless, there remains a lack of clear, process-oriented guidance for developing resilience improvement strategies within the fresh agricultural product sector. Specifically, there is insufficient clarity regarding which elements should be prioritized for investment in resilience strategies, how these strategies should be formulated, and the absence of a theoretically sound framework to guide the strategic development of supply chain resilience improvements. To address the lack of scientific, quantitative, efficient, and specific processes for generating supply chain resilience improvement strategies in fresh agricultural product enterprises, this study adopts the framework of extensible primitive theory. Initially, an evaluation index system for the fresh produce supply chain is constructed, and the extendable evaluation method is employed to assess the resilience level of fresh agricultural product enterprises. This approach facilitates the identification of the key challenges that must be addressed to enhance supply chain resilience and helps generate strategies that reconcile previously incompatible issues. Next, the core objectives and conditions underlying the resilience incompatibilities in fresh agricultural product enterprises are quantitatively analyzed. Finally, the expansion transformation of both target and condition primitives is carried out to derive the optimal strategy for improving supply chain resilience. The study uses company M as a case example, where the evaluation results indicate that the company’s supply chain resilience is rated as “good”. However, several issues were identified, including inefficiencies in product supply, limited financing capacity, low enterprise visibility, and inadequate production and processing equipment. Based on these findings, the paper proposes a series of optimization strategies aimed at improving the fresh produce supply chain resilience through extension transformation. Full article

This descriptive review summarizes the most recent findings on the induction and distribution of viable non-culturable (VBNC) Listeria monocytogenes in food production conditions and food. The aim was to obtain information on the factors that favor the transition to the VBNC state in L. monocytogenes; its resuscitation capacity; and, according to scientific articles published since 2020, how food contamination by the bacterium in a VBNC state can be prevented. The methods used for VBNC L. monocytogenes detection were also reviewed. A few studies reported the presence of VBNC L. monocytogenes in food, in which fresh produce and chicken meat were considered. Different physicochemical stresses such as exposure to disinfectants with diverse actions and essential oils, desiccation, low temperatures, absence of nutrients, high NaCl and iron concentrations, and low pH adjusted with acetic acid were reported to induce the VBNC state in L. monocytogenes. The VBNC forms of L. monocytogenes were able to regain growth and virulence. This could pose a safety risk that cannot be revealed by the standard culture-dependent methods recommended for L. monocytogenes detection. Therefore, the presence in food and food production plants of VBNC L. monocytogenes should be prevented by the appropriate use of hurdles and cleaning/disinfection procedures. The opportunity to harmonize VBNC cell detection methods for regular use in food safety evaluation also emerged. Full article