The scale of the problem is enormous. Most phosphate ions applied as fertilizer never reach the crops they were intended to feed. Instead, they bind with metal ions such as aluminum and iron, and their oxides, forming inner-sphere complexes that are among the most stable bonds in soil chemistry. Because phosphorus has negligible negative effects on crops, farmers have historically applied it in excess, including in organic farming, to guarantee stable production. This practice has fueled water pollution and ecosystem damage through eutrophication, and even when inputs are optimized, phosphorus continues to accumulate as legacy phosphorus that is extraordinarily difficult to recover. The Japanese team set out to test whether superabsorbent polymers, which share a striking chemical similarity with certain plant root structures, could break this cycle.

The inspiration for the approach came from an unexpected corner of plant biology. Groundnuts are the only crop known to yield well in Japan’s aluminum-rich Andisol soils, absorbing phosphorus from sparingly soluble iron and aluminum phosphates despite secreting very little in the way of organic acids. Earlier work by Noriharu Ae and colleagues revealed that groundnut root cell walls, which are packed with carboxyl groups and resistant to both heating and enzymatic attack, can release phosphate ions from minerals such as variscite and vivianite. Superabsorbent polymers, built from linked carboxyl groups arranged in a polymeric mesh that absorbs and retains water, mirror this architecture. The researchers reasoned that these synthetic analogs of groundnut cell walls might perform the same chemical trick on a field scale.

To test this hypothesis, the team conducted a lettuce cultivation bioassay using two contrasting soils: a high-phosphorus Inceptisol and a low-phosphorus Andisol, both collected from lettuce fields in Nagano, Japan. The soils had received annual phosphate fertilizer applications for at least ten years. Lettuce seeds were sown in pots and treated with either 0.04 percent or 0.08 percent SAP solution, with no phosphorus fertilizer added at any point. After 39 days in an artificial climate chamber at 25 degrees Celsius, the results were unambiguous. Application of the 0.08 percent SAP solution increased phosphorus uptake by lettuce by 1.6-fold in the high-phosphorus soil and 1.4-fold in the low-phosphorus soil, with statistical significance confirmed at p less than 0.05. The low-phosphorus soil contained no soluble phosphorus at all, meaning the lettuce could only have accessed phosphorus that the polymers had liberated from insoluble reserves.

Dissolution experiments on five agricultural soils reinforced the bioassay findings. When 0.5 grams of soil were mixed with 0.04 percent SAP solution and shaken for three hours, the amounts of phosphate ions released ranged from 0 to 88.2 milligrams per 100 grams of soil, compared with 0 to 24.9 milligrams in the untreated control. Notably, lower amounts of calcium, aluminum, and iron were detected in the SAP solution than in the control, consistent with these metals being chelated by the polymer and removed from the solution phase. The polymers also mediated the release of sulfate ions bound to the same metals. When the researchers extended the observation period to 38 days using Inceptisol 4, phosphate ion release increased linearly for 13 days and continued for 40 days, matching the performance of trisodium citrate, a well-known chelating agent used as a benchmark.

The team then turned to crystalline phosphate minerals, the most recalcitrant forms of soil phosphorus. Powdered variscite, an aluminum phosphate mined in Akashi, Japan, and vivianite, an iron phosphate mined in Australia, were incubated with SAP solution for seven days. Phosphate ions were dissolved from both minerals, with the amounts released reaching 67 percent of those obtained from non-crystalline aluminum phosphate reagents for variscite and 80 percent for vivianite. This demonstrated that SAPs can attack even the most stable, crystallized phosphate deposits that accumulate in agricultural soils over decades of fertilization.

To quantify the efficiency of the process, the researchers compared SAP performance against trisodium citrate across three metal phosphate reagents: tricalcium phosphate, ferric phosphate, and aluminum phosphate. They defined reaction efficiency as the molar ratio of carboxyl groups to metal ions required to release a given amount of phosphate. SAPs were less efficient than citrate at dissolving iron phosphate, but their efficiency for aluminum phosphate and tricalcium phosphate was nearly identical to that of citrate. The researchers attributed this pattern to the chemistry of the metal ions involved. Aluminum, with its small ionic radius, attracts neighboring carboxyl groups into a tight and efficient chelation structure. Calcium, with its larger radius and lower positive surface potential, forms weaker aggregates. Because aluminum and iron phosphates are the dominant chemical forms through which phosphorus accumulates in soil, the strong performance of SAPs on aluminum phosphate is particularly significant for field applications.

The mechanistic heart of the study lies in a diffusion analysis that reveals how SAPs dissolve aluminum phosphate under neutral pH conditions. The researchers mixed aluminum phosphate reagent with SAP or citrate solution in beakers and tracked phosphate ion release over 672 hours. Fitting the data to diffusion equations based on the complementary error function, they estimated apparent diffusion coefficients for each process. In the water control, the coefficient was 10 to the power of negative 9 square meters per second, consistent with the known diffusion coefficient of phosphate ions in water, confirming that phosphate migrated solely by molecular diffusion. In the citrate solution, a small amount of phosphate was released for approximately 2.7 hours, after which release accelerated dramatically. The slow citrate-mediated process had a diffusion coefficient of 10 to the power of negative 11 square meters per second, two orders of magnitude lower than molecular diffusion, and accounted for approximately 95 percent of total phosphate release. This slow process is governed by film diffusion: at neutral pH, the solubility of aluminum hydroxide is minimal, so a thin colloidal film of aluminum hydroxide forms on the mineral surface, and the dissolution rate is limited not by the chelation reaction itself but by the mass transfer of aluminum-citrate complexes through this barrier.

SAPs exhibited a dual release pattern that sets them apart from citrate. Processes 1 and 2 accounted for approximately 28 percent and 72 percent of total phosphate release, respectively, and occurred simultaneously rather than sequentially. The rapid process likely involves competitive adsorption, in which the high density of carboxyl groups on the polymer displaces phosphate ions from metal oxide surfaces. Because adsorption is a very fast reaction, this mechanism can release phosphate almost immediately upon contact. The exposed aluminum surface then generates positively charged hydrated aluminum species that subsequently chelate with SAP carboxyl groups, feeding into the slower film-diffusion-controlled process. The researchers propose that the polymeric network structure of SAPs, capable of chelating multiple aluminum species simultaneously, combined with the high density of carboxyl functional groups, enables this dual mechanism. Future studies incorporating spectroscopic characterization such as FTIR of SAP-aluminum complexes will be needed to validate the proposed dissolution pathway.

The implications extend well beyond the laboratory. Because SAPs are neutralized with sodium, phosphate ions are released under neutral pH conditions, meaning crops can absorb phosphorus without root damage. Unlike citrate, which is rapidly absorbed by soil microorganisms, SAPs persist in soil for extended periods, offering sustained phosphorus mobilization. A meta-analysis has already reported yield increases of more than 10 percent following SAP application, and the polymers are cost-effective and non-toxic. The technology could enable the recovery and reuse of legacy phosphorus that has accumulated in soils as sparingly soluble deposits, gradually restoring soil phosphorus availability and reducing the environmental impacts associated with phosphorus loss. It could also broaden the range of usable phosphate sources by tapping aluminum- and iron-associated phosphate minerals that have remained largely underexploited. However, challenges remain. SAPs are petroleum-derived substances, and concerns about their environmental impact and degradation products, including their potential classification as a new form of microplastics, are under active investigation. The researchers also note that the behavior and longevity of SAPs under diverse field conditions, involving more complex hydrological and soil dynamics, require further study. Redox conditions, which can convert ferric iron to ferrous iron and influence phosphorus release from iron phosphates, represent another significant frontier. Looking ahead, the team suggests evaluating the recyclability of SAPs from waste materials such as disposable diapers, which could support a circular economy for both phosphorus and the polymers themselves. If these hurdles are cleared, superabsorbent polymers could become key materials for recycling phosphorus fertilizers in agricultural soils, transforming one of agriculture’s most persistent liabilities into a renewable resource.

Subject of Research: Dissolution of “sparingly soluble phosphates” in soil by polyacrylic super absorbent polymers

Article Title: Dissolution of “sparingly soluble phosphates” in soil by polyacrylic super absorbent polymers

Article References: Moriizumi, M., Inoue, H., Suzuki, K., & Ae, N. (2026). Dissolution of “sparingly soluble phosphates” in soil by polyacrylic super absorbent polymers. Discover Soil, 3(1), Article 98. https://doi.org/10.1007/s44378-026-00232-x

Image Credits: AI Generated

DOI: 10.1007/s44378-026-00232-x

Keywords: Dissolution, sparingly, soluble, phosphates, soil, polyacrylic, super, absorbent, polymers, scientific research

Total soluble solids, typically expressed in degrees Brix, constitute the standard industry metric for sweetness and ripeness in mango. The measurement integrates the concentration of sugars, primarily sucrose, glucose, and fructose, along with smaller contributions from organic acids, amino acids, and other dissolved compounds. Conventional determination requires homogenizing flesh samples and reading refractometry values, a process that destroys the fruit and provides information only about the sampled tissue. Because mangoes display considerable spatial heterogeneity in soluble solids, with gradients from the stem end to the blossom end and from the peel inward toward the stone, destructive sampling introduces uncertainty about whether a single measurement represents the whole fruit. A color-based predictive model circumvents this limitation by estimating quality from the intact exterior, enabling repeated assessment of the same fruit across time.

Vitamin C presents an even greater analytical challenge than soluble solids. Ascorbic acid is labile, oxidizing readily upon exposure to oxygen, light, heat, and enzymes released during tissue disruption. Accurate quantification demands rapid extraction into stabilizing media such as metaphosphoric acid, followed by titration with 2,6-dichlorophenolindophenol or separation by high-performance liquid chromatography. These procedures are time-consuming, reagent-intensive, and subject to artifacts if samples are not handled immediately. The finding that peel reflectance characteristics can predict flesh ascorbic acid content therefore offers substantial practical value, particularly for breeding programs and quality assurance workflows where hundreds or thousands of fruit must be screened rapidly without access to full analytical laboratories.

The scientific rationale linking external color to internal vitamin C rests on shared biosynthetic and catabolic pathways. In climacteric fruit such as mango, the respiratory burst accompanying ripening accelerates reactive oxygen species production, and ascorbic acid functions as a principal antioxidant defense. As ripening proceeds, the balance between ascorbate synthesis, recycling through the glutathione-ascorbate cycle, and irreversible oxidation shifts, producing characteristic declines or plateaus in vitamin C content that coincide temporally with pigment changes in the peel. Both chlorophyll catabolism and ascorbate turnover are modulated by ethylene signaling, harvest maturity, and postharvest storage conditions, creating the statistical covariance that predictive models exploit. This coupling is cultivar-dependent, however, since varieties differ in their carotenoid profiles, ascorbate retention, and the degree to which peel coloration tracks flesh maturity.

Reflectance color measurement itself relies on well-established colorimetric principles, most commonly the CIELAB system, in which L* describes lightness, a* the green-to-red axis, and b* the blue-to-yellow axis. Portable colorimeters or spectrophotometers illuminate a small area of the peel with a standardized light source and record the spectrum or tristimulus values of reflected light. These coordinates can be used directly as predictor variables or transformed into indices such as hue angle and chroma, which often correlate more intuitively with human perception of ripeness. Compared with hyperspectral imaging or near-infrared spectroscopy, simple reflectance colorimetry requires inexpensive instrumentation, minimal training, and no complex spectral preprocessing, making it attractive for deployment in packinghouses, wholesale markets, and even field conditions in producing regions.

Statistical modeling of the relationship between color coordinates and quality attributes typically employs regression frameworks ranging from simple linear models to machine learning approaches such as support vector regression, random forests, and artificial neural networks. Model performance is conventionally evaluated through the coefficient of determination and the root mean square error of prediction on independent validation sets. A recurring theme in the literature is that prediction accuracy for soluble solids generally exceeds that for vitamin C, reflecting the tighter biochemical linkage between pigment development and sugar accumulation than between pigments and ascorbate dynamics. Preharvest factors, including orchard location, canopy position, irrigation regime, and maturity at harvest, introduce variability that models trained on one population may not generalize to another, underscoring the importance of cultivar-specific and season-specific calibration.

The practical implications of validated color-based prediction extend across the mango supply chain. Growers can time harvests more precisely, reducing the incidence of fruit picked too early, which never develops full flavor, or too late, which deteriorates rapidly in transit. Packinghouse operators could sort fruit into ripeness classes non-destructively, enabling targeted distribution so that riper lots reach nearby markets while greener fruit is reserved for long-distance shipping. Retailers might monitor displayed inventory and adjust pricing or discounting based on predicted remaining shelf life. For consumers, the approach underpins the growing interest in smartphone-based applications that estimate fruit quality from photographs, democratizing access to quality information that was previously confined to laboratory settings.

Food loss and waste provide an additional motivation for this line of research. Mangoes are climacteric and highly perishable, with postharvest losses in some producing regions estimated at a substantial fraction of total production. A significant portion of these losses stems from mismatches between fruit maturity and market timing: fruit that appears acceptable externally may be internally underripe or overripe when it reaches the consumer. Objective, non-destructive quality assessment allows interventions such as modified atmosphere packaging, controlled temperature regimes, or accelerated marketing to be applied selectively to fruit predicted to be at risk, rather than uniformly to entire lots. This targeted approach conserves resources and reduces the environmental footprint associated with wasted production inputs.

From a breeding perspective, rapid phenotyping of vitamin C content addresses a persistent bottleneck in developing nutritionally enhanced cultivars. Biofortification efforts aimed at increasing micronutrient content in staple and horticultural crops require screening large segregating populations across multiple seasons and environments. Destructive vitamin C assays limit throughput and consume valuable fruit that breeders may wish to retain for seed or further evaluation. If reflectance color measurements can reliably predict ascorbic acid concentration, breeders could screen far more individuals at earlier stages, accelerating genetic gain. Similar logic applies to soluble solids, a heritable trait that directly influences consumer acceptance and market price, and for which high-throughput indirect phenotyping has long been sought.

Several methodological considerations temper enthusiasm and define the agenda for future work. Color measurements capture only the superficial few hundred micrometers of the peel, so their predictive power depends entirely on statistical association rather than direct sensing of flesh composition. This association can be disrupted by treatments that decouple peel color from flesh maturity, such as ethylene degreening, hot water treatment, controlled atmosphere storage, or the application of skin coatings. Pathogen damage, sap burn, lenticel discoloration, and sunburn alter surface optics without proportional changes in internal quality, potentially biasing predictions. Robust deployment therefore requires either careful fruit selection and cleaning protocols or models that incorporate additional spectral bands beyond the visible range to distinguish genuine ripeness signals from surface defects.

Instrument standardization presents a further challenge. Different colorimeters vary in illuminant geometry, aperture size, and calibration, and ambient lighting conditions influence measurements taken with consumer devices. Efforts to harmonize protocols, publish open calibration datasets, and report colorimetric conditions alongside model coefficients would facilitate comparison across studies and support the development of transferable models. The growing adoption of standardized reporting in food research journals reflects recognition that reproducibility is essential if color-based prediction is to move from academic demonstration to industrial practice. Cultivar-specific calibration databases, updated across seasons and growing regions, would constitute valuable shared infrastructure for the mango industry.

The broader scientific context situates this work within the field of non-destructive food quality evaluation, which encompasses hyperspectral imaging, near-infrared spectroscopy, Raman spectroscopy, acoustic and vibration methods, computer vision, and electronic noses. Each technique occupies a niche defined by cost, speed, penetration depth, and the specific quality attributes it senses most effectively. Visible reflectance colorimetry sits at the accessible end of this spectrum, trading depth of information for simplicity and affordability. Hybrid systems that combine color coordinates with a small number of near-infrared wavelengths, or that fuse color imaging with mass estimation and shape analysis, represent a promising middle ground that could improve prediction of attributes like vitamin C while retaining practical deployability.

Looking forward, the integration of color-based prediction models with digital supply chain infrastructure offers transformative potential. When paired with lot-level tracking, temperature logging, and ripening models, per-fruit color measurements taken at packing could feed dynamic shelf-life forecasts that inform logistics decisions in near real time. Machine learning models retrained continuously on incoming measurement-outcome pairs could adapt to seasonal drift and regional variation. In producing countries where laboratory capacity is limited, validated color-based methods could extend quality assessment capabilities to cooperatives and smallholder aggregation centers, improving bargaining position and reducing losses at the point closest to production. The convergence of inexpensive optical sensing, robust statistical modeling, and mobile computing thus positions external color as a durable and scalable window into the internal quality of mangoes and, by extension, other climacteric horticultural commodities.

Subject of Research: Color-based prediction of mango total soluble solids and vitamin C using reflectance color measurement

Article Title: Color-based prediction of mango total soluble solids and vitamin C using reflectance color measurement

Article References: Kusumiyati, K., Sutari, W., Supratman, U., & Munawar, A. A. (2026). Color-based prediction of mango total soluble solids and vitamin C using reflectance color measurement. npj Science of Food. https://doi.org/10.1038/s41538-026-01120-y

Image Credits: AI Generated

DOI: 10.1038/s41538-026-01120-y

Keywords: Color-based, prediction, mango, total, soluble, solids, vitamin, reflectance, color, measurement, scientific research