The research team, led by Parvin Sharayei and colleagues at the Agricultural Engineering Research Institute in Iran, surveyed 23 orchards, 23 wholesale traders, 14 cold storage facilities, 49 retail fruit shops, and 64 households during the July to September harvest season. At the orchard stage, the researchers went beyond interviews and actually weighed harvested lots on calibrated digital platform scales, separating fruit with visible defects such as bruising, decay, pest damage, and cracking from marketable produce. At later stages, where rapid product turnover made direct weighing impractical, they relied on structured interviews and standardized observational assessments, converting all observations into percentage-based indicators so that stages could be compared on equal footing.

The headline numbers reveal a consistent and striking pattern. Physical losses were modest at every stage: 4.54 percent at orchards, 2.49 percent at the wholesale stage, 2.70 percent in cold storage, 3.35 percent at retail, and just 1.77 percent in households. Economic value decline, however, was higher than physical loss at every stage where it could be measured, reaching 7.85 percent at the orchard, 4.23 percent at wholesale, 3.70 percent during storage, and 4.60 percent at retail. In other words, fruit was losing commercial value faster than it was physically disappearing, a distinction that conventional food loss assessments, which typically count only discarded mass, systematically miss.

The study defines the two measures carefully. Physical loss is the proportion of fruit that becomes non-marketable and is removed from the supply because of bruising, decay, pest damage, or cracking. Economic value decline is the relative reduction in the commercial value of fruit that remains present but has been downgraded, whether through visual defects, softening, physiological disorders, or price markdowns. At each stage, the researchers compared the prevailing price of marketable fruit with the actual price achieved after deterioration. This operational distinction matters because a peach does not need to be thrown away to cost someone money. A soft spot, a skin blemish, or a loss of firmness can push fruit into a lower price grade while it still sits in the crate.

Statistical analysis reinforced the point. At the wholesale stage, linear regression showed a weak association between physical loss and value decline, with physical loss explaining only about nine percent of the variation in economic devaluation. At retail, the relationship was similarly weak, with an R-squared of just 0.16. The magnitude of physical loss simply did not predict how much commercial value was being destroyed. This echoes findings from Spanish persimmon production, where economic depreciation of 38.5 percent of commercialized volume exceeded physical mass loss of 29.5 percent, suggesting that the gap between what is discarded and what is devalued may be a general feature of fresh fruit supply chains rather than a quirk of peaches.

To identify which factors mattered most at each stage, the team applied TOPSIS, the Technique for Order Preference by Similarity to Ideal Solution, a multi-criteria decision-making method that ranks factors by their distance from ideal and worst-case solutions. Stakeholders at each stage rated candidate determinants on a five-point importance scale, and the researchers weighted respondents using attributes such as education, experience, and operational capacity, with orchard weights proportional to production volume. The result was a stage-specific priority ranking of loss drivers, grounded in the practical knowledge of the people who actually handle the fruit.

The rankings tell a coherent story about where the supply chain leaks value. At the orchard stage, water stress emerged as the highest-ranked factor with a priority score of 52.2 percent, followed closely by the absence of pre-cooling systems, which 73.9 percent of surveyed orchards lacked. Without rapid removal of field heat, harvested fruit continues respiring at elevated temperatures, accelerating ethylene production, moisture loss, tissue softening, and senescence. At the wholesale stage, inappropriate harvest timing ranked first at 63 percent, followed by cold chain disruption at 58 percent and harvest-to-market shipment delays at roughly 55 percent. In cold storage, where temperatures were appropriately held between 0 and 1 degrees Celsius but humidity ran slightly below the recommended 90 to 95 percent, the single most influential factor, scoring a perfect 100 percent, was low inbound fruit quality, evidence that storage losses often originate upstream rather than in the storage facility itself.

Retail and household results shifted the focus toward economics and behavior. At retail, where every shop relied on ambient storage with no cooling, high fruit prices received the highest TOPSIS priority score, plausibly because expensive fruit sells more slowly, sits longer on display, and deteriorates further under warm conditions. Failure to sell fruit on time and inadequate cooling ranked second and third. At the household level, where average waste was a remarkably low 1.77 percent, the dominant perceived drivers were low-quality fruit at purchase, buying beyond actual consumption needs, and insufficient personal concern about food waste. Nearly 97 percent of consumers refrigerated their fruit, and average storage lasted 6.8 days, suggesting that Iranian households in the study region were already handling peaches and nectarines relatively carefully.

The authors are appropriately cautious about generalizing. The study was designed as a descriptive, stage-based assessment rather than a probability survey, so the figures represent estimates for the surveyed actors rather than statistically representative values for the entire province. The stage-specific percentages cannot simply be added together into a single supply chain total, because the same fruit batches were not tracked longitudinally from orchard to table. The algebraic sum of the stage averages, 14.90 percent, is reported only as a descriptive indicator. Still, when set against regional production of roughly 9,590 tonnes of peaches and nectarines and a population of 7.1 million, the numbers hint at the scale of value quietly leaking out of the system, equivalent to a descriptive estimate of about 14 kilograms of fruit per capita across the assessed stages.

The practical implications are refreshingly concrete. Growers could benefit from improved irrigation management, better harvest scheduling, effective pest and disease control, and access to pre-cooling facilities. Wholesale distributors would gain from minimizing delays between harvest and market and maintaining cold chain continuity. Storage operators should focus on assessing fruit quality at intake, respecting recommended storage durations, and using packaging that cushions and ventilates. Retailers need cooling infrastructure, careful handling, and pricing strategies that encourage timely turnover rather than slow-moving premium displays. Because the dominant loss factors differ from stage to stage, the authors argue, interventions tailored to each node of the chain will accomplish far more than any one-size-fits-all waste reduction campaign. And perhaps most importantly, anyone measuring food loss should look beyond the bin: the truest accounting of waste in perishable fruit includes every discount, downgrade, and devaluation that happens long before anything is thrown away.

Subject of Research: Postharvest physical loss and economic value decline in peach and nectarine supply chains

Article Title: Physical loss/waste vs. value decline in peaches and nectarines: A multi-stage empirical and TOPSIS based assessment

Article References: Sharayei, P., Einafshar, S., Sabeghi, Y., Azarpazhooh, E., Gandomzadeh, D., & Hassan, H. F. (2026). Physical loss/waste vs. value decline in peaches and nectarines: A multi-stage empirical and TOPSIS based assessment. Journal of Agriculture and Food Research, 31, Article 103338. https://doi.org/10.1016/j.jafr.2026.103338

Image Credits: AI Generated

DOI: 10.1016/j.jafr.2026.103338

Keywords: peaches, nectarines, postharvest losses, food waste, economic value decline, supply chain, TOPSIS, cold chain, Iran, Razavi Khorasan, fruit quality, pre-cooling

Researchers at Yanbian University in China worked with rump steaks from 36-month-old Yanbian Yellow Cattle, cut from the biceps femoris muscle within 24 hours of slaughter. The steaks, vacuum-packed and weighing roughly 250 grams each, were divided into four treatment groups drawn from the same carcass. One control group was held at 4 degrees Celsius. The others were rapidly frozen in a minus 30 degrees Celsius freezer until their core temperatures reached minus 0.5 degrees Celsius, representing supercooling with little or no ice formation; minus 5 degrees Celsius, representing sub-freezing with partial ice formation; or minus 18 degrees Celsius, representing deep-freezing with complete freezing. Each group was then packed with six pre-frozen gel ice packs in alternating layers, wrapped in an insulating bag, sealed inside an EPS box, and placed in an incubator at 25 degrees Celsius for 48 hours to simulate a realistic summer delivery.

Temperature logging confirmed the scenario the team wanted to reproduce. During the first 15 hours, while the ice packs melted, the core temperature of all pre-cooled groups stayed below zero. Thereafter, temperatures gradually rose, reaching between minus 1.7 and 3.3 degrees Celsius at the delivery stage depending on the treatment. Sampling continued through five days of subsequent refrigerated storage at 4 degrees Celsius, but only while total volatile basic nitrogen, a spoilage marker, remained below the strict threshold of 20 milligrams per 100 grams. The deep-frozen and sub-frozen groups crossed that limit prematurely, a first hint that their quality was deteriorating faster than the others.

Color told the most visible part of the story. Surface color is the attribute consumers weigh most heavily when buying meat, and it depends on the balance between bright red oxymyoglobin and brown metmyoglobin. At the frozen stage, the deep-frozen steaks actually looked best, showing the highest redness values and the highest lightness, the latter reflecting ice-crystal damage that pushed free water to the surface and increased light scattering. But appearances deceived. Once the parcels warmed during simulated distribution, redness in the deep-frozen group fell fastest, and its metmyoglobin content climbed to the highest level of any group during refrigerated storage. The supercooled group, by contrast, showed the slowest decline in redness, the smallest rise in lightness and yellowness, and consistently low metmyoglobin accumulation, indicating that avoiding ice formation preserved both pigment stability and the endogenous antioxidant environment that protects it.

Texture measurements reinforced the pattern. Deep-frozen steaks were initially the most tender, with a shear force of about 82.65 newtons compared with 123.56 newtons for the refrigerated control, because ice crystals physically disrupted the muscle fibers. Yet after the temperature rise of distribution, shear force in the deep-frozen and sub-frozen groups spiked sharply to 142.37 and 132.36 newtons respectively, a hardening attributed to drip loss, fiber shrinkage, and protein denaturation. Later, both groups softened excessively as structural degradation took over, with the deep-frozen group falling to roughly 53 newtons by 72 hours after delivery. The myofibril fragmentation index, a measure of proteolytic breakdown, surged in the frozen groups after distribution, consistent with freeze-thaw damage releasing lysosomal enzymes such as cathepsins, while the supercooled group showed a gradual, orderly increase reflecting normal aging.

The molecular core of the study lay in the myofibrillar proteins, the structural scaffold that governs water-holding capacity and tenderness. These proteins are acutely sensitive to reactive oxygen species: oxidation converts amino acid side chains to carbonyls, unfolds the native alpha-helical structure, exposes hydrophobic groups buried inside the molecule, and drives cross-linking and aggregation. Carbonyl content rose in all pre-cooled groups during pre-cooling itself, showing that even the phase transition imposes oxidative stress. But after distribution the groups diverged dramatically. By 72 hours after delivery, carbonyl content in the deep-frozen group had reached 2.610 nanomoles per milligram and the sub-frozen group 2.287, while the supercooled group sat at only 1.357, close to the refrigerated control.

Surface hydrophobicity, measured by bromophenol blue binding, painted the same picture of unfolding and aggregation. Deep-frozen and sub-frozen samples already showed markedly elevated hydrophobicity before shipping, and values climbed steeply for every group once distribution began. Protein solubility, meanwhile, fell fastest in the deep-frozen group, dropping from 14.043 to 8.791 over 72 hours after delivery, a rate of decline roughly 80 percent faster than the supercooled group’s. Fourier transform infrared spectroscopy of the amide I band added a structural dimension: after distribution, alpha-helix content in the deep-frozen group collapsed from 56.21 percent to 11.25 percent while beta-sheet, a conformation associated with intermolecular aggregation, jumped to 50.19 percent. The supercooled group retained far more ordered structure, with 23.34 percent alpha-helix and only 18.55 percent beta-sheet at the same stage.

Sensory panels of ten trained assessors, evaluated against ISO 8586 standards, confirmed what the instruments recorded. Scores for meat color, fat color, wetness, and firmness declined most rapidly in the deep-frozen and sub-frozen groups after distribution, and by 72 hours after delivery those groups offered little remaining quality. The supercooled steaks maintained relatively high appearance scores, stable wetness, and acceptable firmness for the longest period, translating the molecular advantages into a longer window of consumer acceptability. The pH trajectory mirrored the biochemical sequence: stable and mildly acidic early on, rising near 6.8 as endogenous proteases released alkaline nitrogen compounds, then falling again as psychrotrophic spoilage bacteria presumably produced organic acids in the later stages.

The study’s central insight is the causal chain it draws from pre-cooling state to protein stability to final quality. Deep-freezing buys a larger thermal reserve and a briefly better initial appearance, but the ice crystals it creates, followed by melting and recrystallization during the warm ride, rupture cell membranes, release pro-oxidants and proteolytic enzymes, and set off a cascade of moisture exudation, pigment oxidation, carbonylation, unfolding, and aggregation. Supercooling at minus 0.5 degrees Celsius threads a needle: it supplies enough cold reserve to blunt the thermal shock of passive distribution while sidestepping the phase transition and its physical damage entirely. For the EPS box and ice pack systems that dominate fresh meat e-commerce, the authors conclude, supercooled pre-cooling is the strategy most likely to deliver beef that still looks, feels, and tastes the way the shopper expects, and the findings offer cold-chain planners a molecularly grounded rationale for rethinking how far down the thermometer a shipment should go before it leaves the warehouse.

Subject of Research: Effects of supercooling, sub-freezing, and deep-freezing pre-cooling on beef quality and myofibrillar protein stability during EPS-based e-commerce distribution

Article Title: Effects of supercooling, sub−freezing, and deep−freezing pre−cooling on color, pH, shear force, sensory quality, and myofibrillar protein properties of beef during expanded polystyrene−based distribution

Article References: Effects of supercooling, sub−freezing, and deep−freezing pre−cooling on color, pH, shear force, sensory quality, and myofibrillar protein properties of beef during expanded polystyrene−based distribution. (n.d.). https://doi.org/10.1007/s44463-026-00083-8

Image Credits: AI Generated

DOI: 10.1007/s44463-026-00083-8

Keywords: beef, supercooling, sub-freezing, deep-freezing, pre-cooling, cold chain, e-commerce distribution, myofibrillar proteins, protein oxidation, meat color, shear force, sensory quality