The study, led by Meryem Qacami of Laval University in Quebec together with Marc-André Bourgault and Mohamed Chikhaoui, focused on the Tangier–Tétouan–Al Hoceima region, a Mediterranean mountain environment covering 17,262 square kilometers. This is one of the wettest parts of Morocco, often receiving more than 1,000 millimeters of rain annually, yet its agriculture remains almost entirely rainfed. Fields are small, fragmented, and scattered across terrain that ranges from coastal lowlands to peaks exceeding 2,000 meters. Under these conditions, the same crop can look spectrally different depending on where it sits in the landscape, making traditional crop classification approaches unreliable.

To tackle this challenge, the researchers turned to the European Space Agency’s Sentinel-1 and Sentinel-2 satellites, two of the most powerful Earth observation platforms currently in orbit. Sentinel-2 captures optical imagery in visible, near-infrared, red-edge, and shortwave-infrared bands at resolutions of 10 and 20 meters, providing direct insight into vegetation vigor, chlorophyll content, and phenological dynamics. Sentinel-1, by contrast, is a synthetic aperture radar that operates in the C-band, sending microwave pulses toward the ground and measuring the energy that bounces back. Because radar penetrates clouds and works day and night, it offers information on canopy structure, surface roughness, and soil moisture that optical sensors simply cannot access. The team combined these observations with topographic variables—elevation, slope, and aspect—derived from the 30-meter SRTM digital elevation model.

All data processing was carried out in Google Earth Engine, a cloud-based geospatial platform that allowed the researchers to handle the massive volumes of satellite imagery involved. Sentinel-2 scenes were filtered to retain only those with cloud cover below 20 percent, with clouds, cirrus, and cloud shadows removed using the Scene Classification Layer. The remaining observations were aggregated into monthly median composites from January to June 2024, capturing the full growing season. Sentinel-1 data, acquired in descending orbit with approximately 12-day revisit intervals, underwent speckle filtering using a Lee sigma filter, radiometric terrain normalization, and conversion to decibel units. From the dual-polarization VV and VH backscatter measurements, the team derived additional radar features including the difference, ratio, and radar vegetation index.

Phenological analysis played a crucial role in defining the classification window. The researchers reconstructed the NDVI time series using the Dynamic Harmonic Regression model and the Savitzky-Golay smoothing algorithm, achieving a root mean square error of 0.0544 and a correlation coefficient of 0.8865 with the Savitzky-Golay method. This revealed that the growing season in the region extends from early January, when vegetation activity begins, through late March, when biomass peaks, to early June, when senescence completes the crop cycle. This window defined the period during which crop separability was expected to be highest and guided the extraction of all satellite variables used in the classification.

For the classification itself, the team employed a Random Forest classifier implemented in Python using the scikit-learn library with 100 trees. They evaluated 31 predefined feature combinations organized into three categories: Sentinel-2-based scenarios, Sentinel-1-based scenarios, and integrated scenarios combining both sensors. The reference dataset contained 1,300 cereal samples and 750 olive samples, collected through field surveys and cross-checked against very high-resolution imagery in Google Earth. A stratified random sampling approach divided the data into 70 percent for training and 30 percent for validation, with the validation subset completely withheld during model selection.

The results revealed a clear hierarchy among data sources. Sentinel-2 spectral bands alone achieved an overall accuracy of 0.82, which improved to 0.89 when combined with topographic variables. Adding red-edge indices to this configuration pushed accuracy to 0.94. In contrast, Sentinel-1 radar features alone yielded the lowest performance, with overall accuracies ranging between 0.53 and 0.55 for individual radar metrics. Even when topographic variables were added, radar-only configurations reached only about 0.67. However, the best results came from the full integration of optical, radar, and topographic information. The winning configuration combined Sentinel-2 spectral bands, Sentinel-1 VV and VH backscatter, the Normalized Difference Red Edge Index 2, the VV/VH backscatter ratio, and elevation, slope, and aspect, achieving an overall accuracy of 0.96 with balanced F1-scores of 0.92 for cereals and 0.91 for olives.

Repeated 10-fold cross-validation confirmed that the integrated scenario significantly outperformed both single-sensor approaches in terms of overall accuracy and olive-grove discrimination. For cereals, however, the improvement over the Sentinel-2-based scenario was marginal and not statistically significant, indicating that optical and topographic information alone already provided strong discrimination of this class. The benefit of sensor integration was therefore class-dependent, proving particularly valuable for the more challenging olive-grove classification.

Perhaps the most striking finding came from the SHAP-based interpretation of the model. Using Shapley Additive exPlanations, a game-theoretic approach that assigns each predictor a marginal contribution value, the researchers found that elevation emerged as the single most influential variable, followed by slope. Among spectral features, NDRE2 ranked highest, confirming the discriminative power of red-edge information. Several Sentinel-2 bands, particularly B6, B7, and B8A in the red-edge and near-infrared regions, also contributed substantially. Radar features showed comparatively lower importance, suggesting a limited but complementary role.

The dominance of topographic variables makes profound agronomic sense in this rainfed landscape. Under bour conditions—the Moroccan term for rainfed farming—the same crop type can exhibit highly variable spectral signatures across the landscape because of spatial differences in water stress, phenological timing, and soil moisture, all of which are governed by topography. A cereal field on a north-facing slope at 600 meters may look spectrally different from one on a south-facing slope at 300 meters, despite being the same crop, because rainfall interception, soil moisture retention, and growing season length differ. In such conditions, topographic context provides a more stable discriminant than spectral reflectance alone. The western Rif receives between 500 and over 1,000 millimeters of annual rainfall depending on altitude and exposure, making elevation a key predictor of crop viability. Olive trees, with their deep root systems and tolerance to thin soils, are well adapted to sloping terrain, whereas cereals generally require flatter land and are more sensitive to erosion.

The spectral patterns also differed between the two classes in agronomically meaningful ways. For cereals, the narrow near-infrared band B8A and the shortwave-infrared band B12 ranked highest, reflecting the strong NIR reflectance plateau of dense herbaceous canopies at peak growth and the sensitivity of SWIR to moisture content in both vegetation and soil. For olives, the red-edge bands B6 and B7 ranked higher, consistent with the evergreen, sclerophyllous canopy of olive trees, which maintains relatively stable chlorophyll content year-round with subtle seasonal variations best captured in the red-edge region.

Within the rainfed agricultural classification domain, the final map identified approximately 453,215 hectares as rainfed cereals and 23,428 hectares as olive groves, corresponding to 95.1 percent and 4.9 percent of the total mapped area. The largest cereal areas occurred in Chefchaouen province, followed by Larache, Al Hoceima, Ouazzane, and Tétouan. Olive groves showed a more concentrated distribution, with the largest mapped areas in Chefchaouen, Larache, and Tétouan provinces.

The researchers acknowledge several limitations. The analysis focused on a single agricultural season and therefore does not capture interannual variability associated with climate fluctuations or management changes. The use of 10-meter satellite imagery may still be affected by mixed-pixel effects in highly fragmented agricultural areas. Only the Random Forest algorithm was evaluated, although other machine-learning and deep-learning approaches may offer complementary insights. The binary classification task also represents a relatively straightforward discrimination between two structurally and phenologically contrasting categories, and the high accuracy should not be directly generalized to more complex multiclass problems involving several annual crops with overlapping phenological cycles.

Nevertheless, the study demonstrates that accurate mapping of rainfed cereals and olive groves in heterogeneous Mediterranean agro-ecosystems benefits from the integration of spectral, structural, and topographic information. The proposed framework provides a useful foundation for extending crop mapping and agricultural monitoring approaches in data-scarce and climate-sensitive regions, where rainfed agriculture supports the livelihoods of millions and remains highly vulnerable to climatic variability. By linking classification performance with agro-ecological interpretation, the work offers new insights into the environmental and anthropogenic drivers of crop distribution and contributes to the development of more robust agricultural monitoring systems for the world’s most fragile farming landscapes.

Subject of Research: Mapping rainfed cereals and olive groves using Sentinel-1, Sentinel-2, and topographic data in northern Morocco

Article Title: Mapping rainfed cereals and olive groves using Sentinel-1, Sentinel-2, and topographic data in northern Morocco

Article References: Qacami, M., Bourgault, M.-A., & Chikhaoui, M. (2026). Mapping rainfed cereals and olive groves using Sentinel-1, Sentinel-2, and topographic data in northern Morocco. Frontiers in Remote Sensing, 7, Article 1880806. https://doi.org/10.3389/frsen.2026.1880806

Image Credits: AI Generated

DOI: 10.3389/frsen.2026.1880806

Keywords: Mapping, rainfed, cereals, olive, groves, Sentinel-1, Sentinel-2, topographic, data, northern, Morocco, scientific research

The scale of the contamination problem is staggering. The Food and Agriculture Organization has long estimated that about 25 percent of food crops are tainted with mycotoxins, but more recent analyses suggest the true figure may be as high as 60 to 80 percent, a revision driven largely by improvements in analytical sensitivity. On the pesticide front, roughly 3.73 million tonnes of agricultural chemicals were applied globally in 2023, yet only an estimated 0.1 percent of pesticides actually reach their intended targets. The rest disperses into air, water, and soil, eventually threading its way back into the food chain and onto our plates.

The health stakes are far from theoretical. Organophosphate pesticides such as chlorpyrifos, diazinon, and malathion can inflict long-term neurological and psychiatric damage by inhibiting the acetylcholinesterase enzyme. Paraquat exposure is linked to severe skin burns, pulmonary fibrosis, and respiratory failure, while carbamates like carbofuran have been associated with endocrine disruption, reproductive harm, and elevated risk of non-Hodgkin lymphoma. Mycotoxins, including aflatoxins, ochratoxin A, deoxynivalenol, and zearalenone, cause both acute and chronic toxicity and have been detected at alarming rates in staple grains worldwide.

The evidence from market surveys is sobering. In Turkish cereal products, aflatoxin B1 concentrations exceeded regulatory limits in more than a quarter of tested samples. In Pakistan, a study of 229 retail cereal products found that 130 were contaminated with zearalenone, 121 with aflatoxin B1, and 115 with ochratoxin A, with many samples breaching maximum permissible levels. In India, 70 of 117 cereal samples tested positive for zearalenone, and one-third of those exceeded European Union limits. Meanwhile, European Rapid Alert System data show that fruits and vegetables accounted for 67.1 percent of all pesticide residue notifications between 1999 and 2022, with okra, chili peppers, beans, and aubergines showing the highest contamination rates.

Against this backdrop, conventional analytical techniques such as gas chromatography-mass spectrometry and liquid chromatography-mass spectrometry remain the gold standard for accuracy and sensitivity. But they come with serious drawbacks: they are time-consuming, demand toxic organic solvents, require expensive equipment and trained personnel, and are poorly suited to on-site or high-throughput screening. This is precisely the gap that antibody-based sensing platforms are engineered to fill, leveraging the exquisite molecular specificity of antigen-antibody interactions to deliver rapid results with minimal infrastructure.

ELISA, or enzyme-linked immunosorbent assay, has emerged as one of the most versatile of these platforms. Competitive ELISA formats dominate for small-molecule contaminants such as pesticides and mycotoxins, which lack the multiple epitopes needed for sandwich-style detection. Recent innovations are striking. An indirect competitive ELISA developed for the neonicotinoid pymetrozine achieved detection limits between 1.62 and 1.66 micrograms per kilogram in wheat, maize, and rice, matching the sensitivity of liquid chromatography-tandem mass spectrometry at a fraction of the cost and time. Similarly, a direct competitive ELISA for the herbicide metsulfuron-methyl reached an IC50 of 37.03 micrograms per liter with recovery rates between 81 and 102 percent in spiked cereal samples.

Lateral-flow immunoassays, the same technology behind at-home pregnancy tests, push accessibility even further. These paper-based strips deliver visual results in minutes without instrumentation, making them ideal for farm, warehouse, or border-inspection settings. The review highlights how nanomaterial labels, particularly gold nanoparticles, have transformed LFIA performance. A gold nanoflower-based LFIA for the herbicide acifluorfen achieved a detection limit of 7.79 nanograms per milliliter, 9.6 times lower than a conventional gold nanoparticle version. Time-resolved fluorescent microsphere-based LFIAs have pushed limits even lower, detecting the fungicide paclobutrazol at 1.72 nanograms per milliliter and providing results within 18 minutes for triadimefon residues in oranges, tomatoes, and cucumbers.

Immunosensors represent the most technologically sophisticated end of the antibody-sensing spectrum, coupling immunochemical recognition to electrochemical, optical, or microgravimetric transducers. Electrochemical formats dominate because they offer high sensitivity, portability, and low cost. A graphene oxide-decorated screen-printed electrode immunosensor detected aflatoxin B1 in wheat flour at an astonishing 1.26 femtograms per microliter. A smartphone-based magneto-immunosensor for the same toxin in corn extract achieved a detection limit of 24 picograms per milliliter, displaying results in a simple traffic-light format through a companion Android app. Nanobody-mediated FRET immunosensors have detected ochratoxin A in rice, barley, wheat, and oats within five minutes at sub-microgram-per-kilogram limits.

Despite these advances, significant hurdles remain. Matrix effects, in which naturally occurring compounds in fruits, vegetables, and cereals such as enzymes, lipids, pigments, and sugars interfere with the analytical signal, continue to plague antibody-based methods, causing signal suppression or enhancement that undermines accuracy. Researchers are countering this through optimized extraction protocols, including QuEChERS pretreatment, hexane cleanup, and careful buffer selection. Antibody stability during storage and repeated freeze-thaw cycles poses another challenge, with aggregation and denaturation eroding performance over time. Camelid-derived nanobodies offer a promising solution, retaining functionality at temperatures as high as 40 degrees Celsius where conventional antibodies would fail, making them especially valuable for on-site applications in resource-limited settings.

Looking ahead, the review points toward a hybrid future in which artificial intelligence amplifies the reach of antibody-based sensing. Connectionist machine learning models excel at extracting subtle patterns from raw sensor data, while symbolic AI frameworks provide the transparent, rule-based reasoning needed for regulatory compliance and traceability across food supply chains. Integrating smartphone readers, cloud connectivity, and AI-driven interpretation with LFIA and immunosensor platforms could automate result analysis, minimize human error, and enable real-time remote monitoring. As contamination pressures mount under climate change and intensifying agriculture, these antibody-powered technologies are poised to become an indispensable frontline defense in keeping the global food supply safe.

Subject of Research: Antibody-based biosensing technologies for detecting pesticide residues and mycotoxins in plant-derived foods

Article Title: Antibody-based sensing of pesticide residues and mycotoxins in plant-derived foods: A narrative review of ELISA, lateral-flow immunoassays and immunosensors

Article References: Kumar, H., Guleria, S., Peter, L., Akhtar, N., Asghar, R., Harun, H. B. C., Kumar, D., Kuča, K., Shaikh, A. M., Harsányi, E., & Kovács, B. (2026). Antibody-based sensing of pesticide residues and mycotoxins in plant-derived foods: A narrative review of ELISA, lateral-flow immunoassays and immunosensors. Food Chemistry: X, Article 104530. https://doi.org/10.1016/j.fochx.2026.104530

Image Credits: AI Generated

DOI: 10.1016/j.fochx.2026.104530

Keywords: ELISA, lateral-flow immunoassay, immunosensors, pesticide residues, mycotoxins, food safety, biosensors, nanoparticles, cereals, fruits and vegetables, nanobodies, food contamination

The distinction between biostimulants and other biological products is central to the problem. Unlike biopesticides, which combat pathogens and fall under plant protection law, biostimulants are defined by what they are supposed to do, stimulating growth, nutrient use efficiency, crop quality or tolerance of abiotic stress, rather than by what they contain. In practice, their composition is frequently not fully characterized at all. That definitional looseness has real consequences. The review catalogs proven successes in horticultural crops: moringa extracts boosting growth in peas and beans, microalgal extracts lengthening tomato roots, arbuscular mycorrhizal fungi improving phosphorus uptake in cotton, and seaweed extracts from Ascophyllum nodosum enhancing stress tolerance in broccoli and spinach. But when the authors searched the literature from 2020 to 2026 for studies on biostimulants in cereals, a starkly different picture emerged, one dominated by inconsistency, single-environment experiments and effects that failed to survive the journey from growth chamber to farm.

At the molecular level, the mechanisms behind biostimulants are genuinely impressive, which makes the field-level failures all the more frustrating. Arbuscular mycorrhizal fungi enhance phosphorus uptake by inducing phosphate transporter genes, raise antioxidant defenses such as superoxide dismutase and catalase, and reduce water loss by downregulating aquaporin proteins. Plant growth-promoting rhizobacteria modulate entire gene networks involved in ethylene biosynthesis, salicylic acid and jasmonate signaling, dehydrin production and osmolyte accumulation. Seaweed extracts upregulate abscisic acid-responsive genes that accelerate stomatal closure, improving water use efficiency, while their cytokinin content promotes cell division. Humic acids stimulate root growth through reactive oxygen species modulation and expansin gene expression. These are not vague claims; they are documented, gene-level physiological responses. The problem is that a mechanism demonstrated in a climate chamber on a single genotype under a defined stress tells you almost nothing about what will happen in a heterogeneous field with unpredictable weather, variable soil and a complex native microbiome.

The review’s literature analysis makes the translation gap concrete. Of the cereal studies examined, the majority were conducted under controlled conditions, in petri dishes, climate chambers or greenhouses, typically in a single environment, making reproducibility impossible to assess. Most evaluated biostimulants under non-stress conditions, even though the economic rationale for such applications is questionable. And the few studies that did span multiple environments generally reported inconsistent responses: seaweed extracts showed low consistency for yield and grain quality in barley, humic acid effects in wheat varied between years, microbial treatments in maize differed between locations, and rice responses depended on genotype. The authors describe this as the translation gap between controlled experimental systems and field conditions, widely regarded as the most critical challenge limiting biostimulant application in cereals. Promising greenhouse findings repeatedly fail to deliver reliable agronomic benefits, creating unrealistic expectations and ultimately disappointing growers who have bet on these products.

The strongest evidence for inconsistency points to the products themselves. Because biostimulants come from natural raw materials, their chemical composition varies enormously. Three commercial seaweed extract products differed substantially in nitrogen, macro- and micronutrient, ash and carbohydrate content, producing distinct physiological responses in wheat leaves. Fifteen accessions of Reynoutria from invasive Central European populations showed considerable variation in both chemistry and genetics. Manufacturing compounds the problem: extraction method, solvent ratios, temperature and duration all significantly alter the final composition, and comparisons of four extraction methods for Chlorella vulgaris showed that acid hydrolysis and microwave-assisted extraction produced the strongest growth promotion in wheat. For microbial products, low quality, such as deficiencies of living cells, and mutations during propagation undermine reproducibility. Heavy metal impurities have even been detected in some formulations. In short, two bottles labeled with the same product may be biologically quite different substances.

Environmental dependence adds a second layer of unpredictability. Seaweed extracts elicit stronger responses in tropical climates than in cooler regions, and a meta-analysis found significant biostimulant-induced yield increases in maize only in Asia and South America. Heat and drought can reduce the efficacy of microbial biostimulants by impairing survival and colonization, while soil texture influences how seaweed-derived polysaccharides affect nutrient retention and root-soil interactions. Beyond these well-supported factors, the review identifies moderate-evidence causes: application method, timing and dosage, and crucially, genotype. In a study of ten spring barley genotypes under early drought, drought-sensitive lines benefited more from biostimulants than drought-tolerant ones, meaning the value of a treatment depends on the genetic adaptation strategy of the crop it is applied to. Seed priming is cheap and low-input but applies the product blind, before anyone knows whether stress will occur; foliar spraying and soil application offer flexibility but demand large volumes and risk drift and washoff.

Some of the most intriguing hypotheses concern the soil microbiome, though the evidence here remains thin. Soil microbial activity depends strongly on soil type, humus content and particle size, and it is genuinely unclear whether inoculating arbuscular mycorrhizal fungi in the field helps or harms indigenous mycorrhizal communities, as both outcomes have been reported. A zeolite-based biostimulant was found to negatively affect soil enzyme activity. Introduced microbes may persist only briefly, with laboratory studies showing survival of less than 28 days for E. coli in natural soil and up to 49 days for other biostimulant-associated strains. Host plants shape rhizosphere communities through root exudates, and cereal-dominated rotations may accumulate soil-borne pathogens such as Alternaria alternata or Fusarium oxysporum that could negate biostimulant effects entirely. Single-strain inoculants face particular difficulty establishing against endemic communities already adapted to local conditions. None of these interactions has been systematically studied in cereals, representing a major knowledge gap.

The proposed solutions are refreshingly practical. In the near term, the authors call for identifying the active compounds in biostimulants using liquid and gas chromatography coupled to mass spectrometry, following the model that turned pyrethrin from chrysanthemum into the well-characterized insecticide allethrin. Standardized cultivation of raw materials, macroalgae grown in photobioreactors and tank cultures rather than harvested wild from oceans, and clonal propagation of species like Gracilaria and Kappaphycus would stabilize composition. Multi-environment trials with precisely defined experimental parameters, stress-specific validation and genotype-specific evaluation would expose which products actually work, for which crops, under which conditions. Screening large genotype sets within a single crop, and eventually identifying quantitative trait loci associated with biostimulant responsiveness, could let breeders select varieties that respond reliably. Application technology also has room to improve: dropleg sprayers, originally developed to protect pollinators in oilseed rape, deliver product to the underside of cereal leaves with less drift, while moderate application frequencies of four to six seaweed treatments outperformed sporadic use, and powdered mycorrhizal inoculants adhere best to the rough, hairy surface of cereal grains.

Looking further ahead, the review sketches a genuinely futuristic agenda. Next-generation sequencing could identify the biosynthetic gene clusters responsible for biostimulant activity in microbes, fungi and seaweeds, enabling CRISPR/Cas9 engineering of so-called designer biostimulants with stable, defined compositions, though European regulation and the risk of metabolic burden on crops remain obstacles. Drones equipped with multispectral and hyperspectral cameras could map crop stress in real time and generate prescription maps for site-specific biostimulant application, an approach already proven for disease detection and fertilizer optimization, though battery limits, cost and weather dependence currently restrict practical use. Circular economy approaches could lower costs by converting shrimp shells, potato peels and chicken feathers into protein hydrolysates and chitosan derivatives, provided contaminants such as pharmaceuticals and microplastics are excluded. Artificial intelligence applied to multi-omics data, genomics, transcriptomics, proteomics and metabolomics, could untangle the nonlinear interactions among soil, microbiome and plant that determine whether a treatment works. The authors’ bottom line is sober but optimistic: biostimulants are not a universal solution, but treated as precisely targeted tools, matched to specific crops, genotypes, stresses and sites, they could yet become a dependable pillar of sustainable cereal production.

Subject of Research: Improving the effectiveness and reproducibility of biostimulants in field-grown cereal crops

Article Title: How to make the action of biostimulants more effective and reproducible for field crops?

Article References: Töpfer, V., Breitkreuz, C., Matros, A., Stahl, A., Warnemünde, S., & Wehner, G. (2026). How to make the action of biostimulants more effective and reproducible for field crops?. Journal of Agriculture and Food Research, 31, Article 103316. https://doi.org/10.1016/j.jafr.2026.103316

Image Credits: AI Generated

DOI: 10.1016/j.jafr.2026.103316

Keywords: biostimulants, cereals, drought stress, soil microbiome, seaweed extracts, arbuscular mycorrhizal fungi, plant growth-promoting rhizobacteria, precision agriculture, genotype-specific response, circular economy, CRISPR, sustainable agriculture

The review, led by researchers at Sun Yat-sen University in collaboration with the University of Almería and the Swedish University of Agricultural Sciences, systematically surveys more than a decade of progress in plant lipid metabolic engineering. Its central argument is that cereals, despite their naturally low seed oil content of roughly 2 to 4 percent of grain dry weight, possess the complete lipid biosynthetic machinery, the agronomic infrastructure and the transformation toolkits needed to become scalable chassis for lipid biomanufacturing. What has been missing until recently is the ability to redirect their carbon flow, and that is precisely what modern genome editing and multigene stacking now make possible.

At the heart of the engineering challenge lies a well-characterized metabolic network. De novo fatty acid synthesis begins in the plastid, where acetyl-CoA is carboxylated by acetyl-CoA carboxylase, the rate-limiting enzyme of the pathway, to generate malonyl-CoA. The fatty acid synthase complex then elongates the carbon chain in two-carbon increments, typically producing C16 and C18 fatty acids that are released by thioesterases and exported to the cytosol. There, long-chain acyl-CoA synthetases activate them into the acyl-CoA pool that feeds triacylglycerol assembly in the endoplasmic reticulum, proceeding through the Kennedy pathway or the acyl-CoA-independent PDAT route. Phosphatidylcholine acts as a central hub in this network, hosting desaturation reactions catalyzed by FAD2 and FAD3 and shuttling modified fatty acids back and forth through acyl editing mediated by LPCAT.

Engineering this network in cereals has followed what the authors describe as a push-pull-package-protect strategy. The push component boosts fatty acid synthesis in the plastid, often by overexpressing the transcription factor WRINKLED1, a master regulator that activates genes for glycolysis and fatty acid production. The pull component drives fatty acids into triacylglycerol through diacylglycerol acyltransferases such as DGAT1. The package component sequesters the resulting oil into stable oil bodies, frequently by enhancing oleosin proteins that coat and stabilize lipid droplets. The protect component preserves oil body integrity and limits turnover. In rice, combining all four modules by co-expressing Arabidopsis WRI1, DGAT1, PDAT and oleosin increased seed triacylglycerol content by 26 percent and raised total oil by 70 percent in seeds and 22.5 percent in leaves.

The most dramatic demonstration of carbon reallocation in a cereal came from a recent rice study highlighted in the review. By expressing Arabidopsis DGAT1 specifically in the endosperm under the Glb1 promoter, while simultaneously using CRISPR-Cas9 to knock out AGPL2, a rate-limiting gene in starch biosynthesis, and MTSSB1, a regulator of aleurone layer thickness, researchers pushed grain oil content from 2.33 percent to 11.72 percent of dry weight, a more than fivefold increase achieved in an elite cultivar without major agronomic penalties. In maize, embryo-preferred expression of the native ZmWRI1 raised seed oil by 30.6 percent without harming vegetative growth, whereas overexpression of ZmLEC1, which acts upstream of WRI1, boosted oil by 48.7 percent but caused germination and developmental defects, underscoring the importance of tissue-specific and carefully balanced regulation.

Beyond simply making more oil, engineers are now introducing entirely foreign lipid products. The flagship target is the very-long-chain omega-3 polyunsaturated fatty acids eicosapentaenoic acid and docosahexaenoic acid, the compounds that make oily fish so nutritionally prized. Humans convert the plant-derived precursor alpha-linolenic acid into EPA and DHA very inefficiently, and marine fish stocks are under pressure, so plant-based sources are urgently needed. In oilseed crops such as Camelina sativa and canola, heterologous pathways assembled from marine algal and fungal genes have already achieved seed oils containing up to 19 percent combined EPA and DHA, and Nuseed’s omega-3 canola has reached commercial aquafeed markets. Cereals are catching up: in maize, introduction of an alternative delta-8 desaturation pathway using genes from Isochrysis galbana, Euglena gracilis and Mortierella alpina produced EPA at nearly 2 percent of total leaf fatty acids, a proof of concept that grain-targeted versions could follow.

Rice has taken a different route toward omega-3 enrichment, focusing first on boosting the precursor alpha-linolenic acid. Endosperm-specific overexpression of omega-3 desaturase genes from soybean and rice raised seed ALA content from 0.36 to as much as 10.06 milligrams per gram, roughly a 28-fold increase and enough to meet most daily dietary requirements. More recently, an intragenic approach using only the rice’s own FAD3 gene under an endosperm-specific promoter increased ALA nearly 15-fold without introducing any foreign DNA, potentially easing biosafety and regulatory concerns. Feeding trials in rats showed that consuming this enriched rice elevated ALA, EPA and DHA levels in serum and brain tissue, offering a glimpse of staple-food biofortification in action.

The review also charts progress on two industrial targets. Wax esters, the neutral lipids that made sperm whale oil and jojoba oil so valuable for lubricants and cosmetics, can now be produced in plants by co-expressing a fatty acyl reductase and a wax synthase. Transgenic Camelina lines have accumulated wax esters exceeding 60 percent of seed oil, and enzyme selection, oleosin-mediated targeting to lipid droplets and fusion protein design have pushed yields in Arabidopsis to over 100 milligrams per gram of seed. Insect sex pheromones represent a third frontier. Roughly three-quarters of lepidopteran sex pheromones are C10 to C18 fatty alcohols, aldehydes or acetates, and plants can be engineered to make their fatty acid precursors using desaturases, elongases and reductases borrowed from insects. Engineered Camelina accumulating pheromone precursors at more than 20 percent of seed fatty acids yielded blends that matched synthetic pheromones in field trials against the diamondback moth, and tunable CRISPR-based activation systems in Nicotiana benthamiana now allow programmable, high-yield de novo pheromone biosynthesis.

Why choose cereals at all when oilseeds are further along? The review’s comparative analysis points to scale and infrastructure. Cereals occupy vast cultivation areas, benefit from mature supply chains, harvesting systems and processing networks, and produce enormous vegetative biomass that could host industrial lipid production without competing with food uses in the grain. Rice is currently the most tractable cereal for transformation and editing, wheat remains recalcitrant although new haploid-embryo systems are changing that, and maize sits in between, with particle bombardment still widely used because Agrobacterium transformation is technically difficult. The design-build-test-learn cycle of synthetic biology, combined with multi-omics profiling, promoter engineering and iterative optimization, is expected to accelerate the identification of rate-limiting steps and tissue-specific regulatory elements in all three crops.

Significant obstacles remain. Transformation efficiency varies widely by genotype, stable multigene expression is technically demanding, and redirecting carbon away from starch can trigger pleiotropic effects including dwarfism, reduced fertility and impaired seed development, as seen in some engineered sorghum lines. Regulatory frameworks for genetically modified staple foods, particularly in the European Union, add another layer of complexity, although the authors note a gradual global shift toward more enabling policies. Still, the trajectory is clear: with omega-3 oilseeds already commercialized, wax ester and pheromone platforms advancing through field trials, and cereal oil contents now being pushed fivefold higher, the prospect of fields of rice and maize quietly manufacturing fish oils, industrial lubricants and pest-control chemicals is moving from speculation toward engineering reality, positioning the world’s oldest crops at the frontier of the emerging bio-based economy.

Subject of Research: Metabolic engineering of cereal crops for sustainable production of high-value lipids including omega-3 fatty acids, wax esters and insect sex pheromones

Article Title: Metabolic engineering of cereal lipids: from omega-3 fatty acids to wax esters and pheromones

Article References: Li, M.-T., Lin, J.-T., García-Caparros, P., Zhu, L.-H., Yao, N., & Xia, Y.-H. (2026). Metabolic engineering of cereal lipids: from omega-3 fatty acids to wax esters and pheromones. Advanced Biotechnology, 4(3), Article 28. https://doi.org/10.1007/s44307-026-00124-9

Image Credits: AI Generated

DOI: 10.1007/s44307-026-00124-9

Keywords: metabolic engineering, cereals, omega-3 fatty acids, EPA, DHA, wax esters, insect pheromones, rice, maize, wheat, synthetic biology, seed oil