AI and Gene Editing Team Up to Slash the World’s Fruit and Vegetable Waste

Every year, between a quarter and half of all the fruits and vegetables grown on Earth never reach a hungry mouth. They rot in transit, succumb to fungal disease, or simply age past the point of sale, wasting billions of dollars along with the water, land, labor and energy that went into producing them. A sweeping new review published in Current Research in Food Science argues that this chronic hemorrhage of food is finally meeting its match, as artificial intelligence and modern biotechnology converge to transform postharvest handling from a reactive scramble against decay into a predictive, precision-driven science.

The review, led by Yuan Sui and colleagues, begins with a sobering biological reality: fruits and vegetables do not die at harvest. They remain metabolically alive, respiring, ripening and senescing according to tightly scripted genetic programs. Climacteric crops such as apples, bananas and tomatoes continue to produce the ripening hormone ethylene after picking, while non-climacteric crops like citrus and strawberries follow different respiratory patterns that dictate how long they can be stored. Ethylene biosynthesis follows a now-classically mapped pathway, from methionine to S-adenosyl-L-methionine, then to 1-aminocyclopropane-1-carboxylic acid via ACC synthase, and finally to ethylene through ACC oxidase. Downstream, membrane receptors such as ETR1 and ERS1, along with CTR1 and EIN signaling factors, switch on transcription factors that orchestrate the expression of hundreds of ripening genes.

Storage itself is a delicate balancing act. Refrigeration slows respiration, roughly halving metabolic rate for every 10 degrees Celsius of cooling, but temperatures that are too low trigger chilling injury, damaging membranes, depleting cellular energy and provoking oxidative stress. Central to that stress is the accumulation of reactive oxygen species, which in moderate amounts act as signaling molecules but in excess attack lipids, proteins and DNA. The produce fights back with enzymatic antioxidants such as superoxide dismutase, catalase and ascorbate peroxidase, supported by non-enzymatic compounds including ascorbate, phenols and flavonoids. Recent work highlighted in the review shows that treatments like melatonin and xanthan gum coatings can upregulate these antioxidant systems, lowering markers of oxidative damage such as malondialdehyde and hydrogen peroxide while preserving membrane integrity.

Perhaps the most striking conceptual shift in the review is the reframing of many familiar storage disorders as manifestations of programmed cell death. Internal browning in pome fruits, superficial scald in apples and russeting in lettuce all show hallmarks of genetically orchestrated cellular self-destruction rather than simple passive decay. Ethylene signaling and reactive oxygen species converge to activate cysteine proteases and other hydrolytic enzymes, while stresses such as low oxygen, high carbon dioxide and cold can prematurely trigger PCD-like symptoms. Even the mechanical wounding of fresh-cut processing launches a rapid cell death response that browns tissue and shortens marketability. The authors argue that integrating multi-omic profiling with high-throughput phenotyping could yield biomarkers for detecting the onset of PCD early, enabling intervention before visible damage appears.

On the pathogen side, the review details the stealthy strategies of postharvest fungi. Many pathogens infect fruit in the field but then lie quiescent, waiting for ripening to weaken host defenses and release nutrients. Botrytis cinerea, the gray mold agent, deploys necrosis-inducing proteins, ceratoplatanins and xyloglucanases to kill host cells, secretes the toxin botrydial, and even smuggles small RNAs into plant cells to hijack the host’s own RNA interference machinery and silence defense genes. Fungi also manipulate the pH of their microenvironment through the Pal/PacC signaling pathway, with B. cinerea and Sclerotinia sclerotiorum flooding tissue with oxalic acid while Colletotrichum and Alternaria species alkalinize it with ammonia. NADPH oxidase complexes generate the reactive oxygen species that fungi need for penetration and virulence, making these enzymes potential drug targets.

Biotechnology is now striking back on both fronts. CRISPR/Cas9 editing has produced banana lines resistant to Fusarium wilt tropical race 4, knocked out the VvWRKY52 transcription factor in grapes to boost resistance against gray mold, and disrupted the CsLOB1 promoter in citrus to confer resistance against canker. The non-browning Arctic apple, created by silencing the polyphenoloxidase gene, has already reached consumers. RNA interference offers a complementary weapon: silencing Dicer-like genes in B. cinerea reduces gray mold on strawberries, and researchers have documented cross-kingdom RNAi in which citrus microRNAs target the blue mold pathogen Penicillium italicum during natural infection. Nanostructured double-stranded RNA sprays are pushing this technology toward field-ready delivery, though questions of dosage, stability and off-target effects remain.

Meanwhile, artificial intelligence is rewriting quality inspection. Traditional sensory assessment is subjective and slow; AI-driven systems combining computer vision, deep learning, hyperspectral imaging and Internet-of-Things sensors now detect defects, diseases and ripeness stages with remarkable speed and accuracy. A YOLOv4-based IoT system for cherry tomatoes achieved 97.4 percent classification accuracy in real-time defect sorting. Hyperspectral fluorescence imaging paired with a ResNet-50-based one-dimensional convolutional neural network could stage Botrytis infections in strawberries before symptoms became visible, and deep transfer learning on ultraviolet imagery identified Aspergillus flavus contamination in dried figs with 98.57 percent accuracy. Hyperspectral imaging with machine learning has also detected early bruising in apples, with extreme learning machine models reaching nearly 96 percent accuracy.

AI is equally reshaping packaging and robotics. Artificial neural networks predicted that polyethylene packaging under a modified atmosphere of 92 percent nitrogen, 5 percent carbon dioxide and 3 percent oxygen could extend cauliflower shelf life beyond 30 days, with a potential market life of 50 days. Other models have designed pH-sensitive chitosan-anthocyanin films that signal freshness changes, and optimized gelatin films loaded with propolis and titanium dioxide nanoparticles. Robotic handling systems are keeping pace: a deep-learning robot for soft fruits achieved pick success rates between 97 and 100 percent with a cycle time of just 253 milliseconds, using spatial frequency domain imaging to spot bruises the human eye would miss. The review cautions, however, that AI methods still lack the metrological traceability and regulatory acceptance of conventional reference methods, and their performance depends heavily on the quality and representativeness of training data.

The challenges ahead are substantial. Biological variability across cultivars, seasons and growing conditions produces fragmented datasets; regulatory frameworks for AI-integrated smart packaging remain patchy; and the capital costs of sensors, computing and robotics weigh heavily on the small and medium-sized enterprises that dominate the food sector. Yet the trajectory is clear. The authors envision AI systems that fuse host omics, microbiome profiles and supply-chain exposome data to move beyond prediction toward mechanistic understanding and actionable intervention, supported by blockchain traceability, responsive packaging materials and few-shot learning models that adapt across crops and regions. If that vision materializes, the cold chain of the future will not merely store produce; it will watch it, understand it and act to save it, turning one of agriculture’s oldest problems into one of its most sophisticated technological success stories.

Subject of Research: Artificial intelligence and biotechnology applications for postharvest quality and safety of horticultural produce

Article Title: Artificial Intelligence and Biotechnology for Smart Storage: Quality and Safety Perspectives in Horticultural Produce

Article References: Sui, Y., Zhao, Y., Chen, W., Duan, B., Wang, Z., & Chen, Z. (2026). Artificial Intelligence and Biotechnology for Smart Storage: Quality and Safety Perspectives in Horticultural Produce. Current Research in Food Science, Article 101594. https://doi.org/10.1016/j.crfs.2026.101594

Image Credits: AI Generated

DOI: 10.1016/j.crfs.2026.101594

Keywords: postharvest losses, artificial intelligence, ethylene, CRISPR, RNA interference, food safety, mycotoxins, hyperspectral imaging, smart packaging, Botrytis cinerea, programmed cell death, cold chain