Soil health assessment has become a cornerstone of sustainable agriculture. Laboratories measure a suite of physical, chemical, and biological properties to gauge how well a soil supports nutrient cycling, water regulation, carbon sequestration, and biodiversity. The most sensitive indicators are deliberately chosen because they respond quickly to management changes. Total soil organic carbon, the fundamental currency of soil fertility, moves slowly, often taking years or decades to register the effects of a new cropping practice. Labile carbon pools, by contrast, are designed to be fast. Water-extractable organic carbon reflects the readily available substrates that microbes consume; potentially mineralizable carbon captures how much carbon dioxide microbes release when soil is rewetted; and permanganate-oxidizable carbon, known as POX-C, measures a chemically reactive fraction of organic matter. These rapid-response metrics are attractive precisely because they change quickly, but the new work shows that speed comes with a hidden vulnerability.

The problem begins with water. Even soils classified as air-dried retain a small residue of moisture, typically between 0.3 and 6 percent of their mass, adsorbed to mineral surfaces and trapped in fine pores. That residual water, the researchers explain, can be enough to sustain low levels of microbial activity. Over months and years of storage, slowly metabolizing microbes, cell lysis, and continued enzymatic depolymerization can transform the labile carbon and nitrogen pools that sensitive indicators are supposed to measure. Drying itself may also alter mineral equilibria and the solubility of soil organic matter, releasing carbon that would have stayed bound in a fresh sample. Bulk soil organic carbon and nitrogen pools remain relatively stable during long-term storage, which is why archives have long been trusted for those measurements, but the water-extractable fractions are far more fragile.

To quantify these effects directly, the team designed what they call a Controlled Storage Experiment. They retrieved archived surface soils from a three-year cover crop study at the University of Florida’s Field and Fork Farm in Gainesville, where plots had been planted with pearl millet, sunn hemp, or a mixture of grasses and legumes including sorghum sudangrass, pearl millet, sunn hemp, and cowpea. The samples, collected from 2019 to 2021 before each summer planting season, had been air-dried in a climate-controlled laboratory, sieved, and stored in airtight plastic bags at room temperature. In 2025, the researchers reanalyzed the same archived samples using identical protocols to those applied in 2021 and 2022, isolating the effect of storage from any field-driven changes. Water-extractable carbon and nitrogen were extracted by shaking soil with ultrapure water; mineralizable carbon was measured as carbon dioxide accumulating in sealed jars after rewetting; and POX-C was determined colorimetrically after reaction with potassium permanganate.

The results were striking. Across all sampling years and cover crop treatments, WEOC concentrations increased by 96 percent after three years of storage, a near-doubling that was highly statistically significant. Water-extractable nitrogen moved in the opposite direction, declining by 19 percent, possibly because released organic nitrogen was immobilized by microbes or sorbed onto mineral surfaces. Mineralizable carbon showed a smaller but significant increase of about 6 percent, consistent with the well-known Birch effect, in which rewetting dry soil mobilizes previously protected substrates and triggers a pulse of microbial respiration. Only POX-C remained essentially unchanged, with no significant overall shift, indicating that this indicator is robust to the effects of multi-year storage. Notably, the storage effects were consistent across all three cover crop treatments, suggesting that the composition of plant residues did not buffer or amplify the distortion.

The timing of the changes offered additional clues. Storage effects on WEOC were stronger in soils collected in 2020 and 2021 than in those collected in 2019. The researchers speculate that air-drying itself introduces a strong immediate artifact on WEOC, and that this artifact gradually diminishes over time. Samples collected in 2019 were first analyzed in 2022, after an initial three-year storage period, whereas the 2021 samples experienced only a short interval between collection and first analysis, making them more susceptible to the immediate effects of drying. For mineralizable carbon, the pattern reversed: recent samples showed positive storage effects while older samples showed slight declines, hinting that prolonged storage may alter microbial communities in ways that reduce their capacity to metabolize organic substrates upon rewetting, a phenomenon previously observed in soils recovering from extended drought.

To test whether these effects were unique to one sandy Florida soil, the team conducted a Multi-site Validation Experiment using archived soils from four long-term agricultural studies across the Midwest: the W.K. Kellogg Biological Station Long-Term Ecological Research site and the Great Lakes Bioenergy Research Center in Michigan, the Northern Great Plains Long-Term Agroecological Research site in North Dakota, and the Eastern Nebraska Extension and Education Center in Nebraska. These sites spanned certified organic cropping systems, perennial switchgrass monocultures, fallow treatments following spring wheat, and no-till corn systems with stover retention, on soils ranging from loamy Hapludalfs to silt loam Mollisols. The comparison revealed a consistent signature. At every one of the five studies, WEOC declined significantly over time, with correlation coefficients between minus 0.60 and minus 0.84, while the corresponding trends in bulk soil organic carbon or soil organic matter varied independently, increasing at one site, declining marginally at another, and remaining stable elsewhere.

That divergence is the smoking gun. Because bulk carbon is known to be robust against storage, a labile pool whose trajectory departs from bulk carbon across multiple independent sites points to an additional process beyond genuine soil change. The Controlled Storage Experiment supplies the explanation: prolonged storage inflates WEOC, so the oldest archived samples, which waited longest before analysis, carry the largest storage-induced increases. When those inflated values are plotted against sampling date, the result is an apparent decline in WEOC over time that reflects shelf time rather than soil biology. Although the observational nature of the multi-site data cannot fully separate storage artifacts from every other factor, the consistency of the pattern across such different climates, textures, and management systems strongly supports the conclusion that storage history can substantially bias retrospective analyses of archived soils.

The implications ripple outward. Soil archives are treasured resources, allowing scientists to apply newly developed indicators to samples collected decades ago and to track long-term impacts of management practices. But if labile carbon indicators are systematically inflated by storage, temporal comparisons built on archived samples may confuse artifacts with real management effects, undermining the very decisions soil health testing is meant to inform. The authors recommend that storage-sensitive pools like WEOC be analyzed immediately upon collection, and suggest that controlled-temperature drying or cold storage deserve exploration for labile indicators. They also caution against using WEOC to infer long-term trajectories in carbon storage or composition. In contrast, the stability of POX-C across multi-year storage underscores its potential for retrospective studies, offering new input into ongoing debates about that indicator’s interpretability. As soil health datasets increasingly span years and decades, the study delivers a clear message: a soil sample is not a frozen moment in time, and the shelf it sits on can rewrite its story.

Subject of Research: Effects of long-term air-dried storage on soil health indicators, particularly water-extractable organic carbon

Article Title: Long-term storage of air-dried samples compromises water-extractable organic carbon as a soil health indicator

Article References: Long-term storage of air-dried samples compromises water-extractable organic carbon as a soil health indicator. (n.d.). https://doi.org/10.5194/soil-12-937-2026

Image Credits: AI Generated

DOI: 10.5194/soil-12-937-2026

Keywords: soil health, water-extractable organic carbon, soil archives, soil organic carbon, cover crops, permanganate-oxidizable carbon, mineralizable carbon, sample storage, agricultural research, soil testing, Long-term, storage

The study, conducted by researchers at Banaras Hindu University in Varanasi and published in the journal Discover Soil, grew out of a growing anxiety about potassium mining in one of the world’s most intensively farmed regions. The rice-wheat cropping system that dominates the Indo-Gangetic plains supplies more than half of the food consumed in India, occupying roughly 27 percent of the country’s agricultural land. Yet fertilizer use in India has become badly skewed: between 1971-72 and 2021-22, nitrogen consumption surged 11.3-fold and phosphorus 14.2-fold, while potassium rose only 5.71-fold. The current national ratio of nitrogen to phosphorus to potassium stands at 6.7:2.4:1, far from the 4:2:1 ratio long recommended by the Fertiliser Association of India. An estimated 72 percent of India’s agricultural land is now considered potassium deficient.

Why does this imbalance matter? Potassium is not a minor player in crop physiology. It governs enzyme activation, water regulation, photosynthesis, and the transport of sugars, all of which feed directly into yield, grain quality, and the plant’s resilience to stress. When farmers skimp on potassium while piling on nitrogen, they quietly draw down the soil’s native reserves, a process scientists call potassium mining. Crop residues complicate the picture further: rice and wheat straw is extraordinarily rich in potassium, containing 80 to 85 percent of the nutrient taken up by the plant, and returning it to the field can substitute for 20 to 50 percent of potassium fertilizer. In conservation agriculture systems, where residues are retained on the soil surface and tillage is minimized, this recycling loop changes the chemistry of potassium availability in ways that conventional soil tests were never designed to capture.

To find out which chemical extractants best reflect reality under these conditions, the team turned to a long-term experiment established in 2012 at the university’s agricultural research farm. The site sits on sandy loam soils of the Typic Ustochrept family in a humid subtropical climate with about 1,110 millimeters of annual rainfall. The experiment followed a split-plot design with four crop establishment methods, ranging from full conventional tillage to full conservation agriculture with residue retention in both seasons, crossed with three nutrient management levels. After eleven complete crop cycles, the researchers sampled soil from all 36 plots at a depth of 0 to 15 centimeters and subjected it to a battery of twelve different potassium extractants.

The extractants spanned four mechanistic families. Distilled water and dilute salt solutions such as calcium chloride, barium chloride, ammonium acetate, sodium acetate, and sodium tetraphenyl boron target the potassium held in soil solution and on exchange sites. Multi-nutrient extractants, including ammonium bicarbonate-DTPA and the Mehlich solutions, pull several nutrients simultaneously. Acidic extractants, including strontium chloride mixtures and boiling nitric acid, attack the mineral lattice itself, releasing the non-exchangeable potassium locked between the layers of clay minerals. The logic is that plants do not simply sip from the soil solution; as roots deplete it, potassium desorbs from exchange sites and, over longer timescales, is released from mineral interlayers. A good soil test should mimic that whole cascade.

The results were striking. Boiling nitric acid extracted the most potassium, between 1,042 and 1,189 milligrams per kilogram of soil, followed by sodium tetraphenyl boron at 407.8 to 495.5 milligrams per kilogram, because both tap the non-exchangeable reservoir. At the other extreme, distilled water pulled out a mere 13.98 to 20.63 milligrams per kilogram. The workhorse ammonium acetate test extracted between 46.33 and 62.86 milligrams per kilogram, a middling figure that belies its global status. Among exchangeable-potassium extractants, barium chloride was the most aggressive, yielding 251.15 to 277.41 milligrams per kilogram, likely because barium is not preferentially adsorbed and does not collapse the expanded clay structures that hold potassium.

Correlation analysis revealed the real story. Sodium acetate emerged as the standout performer, correlating strongly with sodium tetraphenyl boron (r = 0.979), with relative grain yield (r = 0.927 to 0.984), with plant potassium uptake (r = 0.930 to 0.974), and with key soil indices such as cation exchange capacity, specific surface area, and organic carbon. The conventional ammonium acetate test performed respectably but less impressively, with correlations of 0.80 to 0.94 against plant indices. The acidic extractants fared worst: strontium chloride at 0.002 molar showed correlations as weak as 0.231 and no significant relationship with yield, while even boiling nitric acid, despite extracting the largest quantity of potassium, correlated poorly with what plants actually achieved. The researchers attribute sodium acetate’s advantage to its ability to pull water-soluble and exchangeable potassium along with a fraction of the non-exchangeable pool, capturing a broader spectrum of the potassium a crop can access during a growing season.

The team also established critical concentration thresholds using the Cate-Nelson statistical procedure, which partitions soil test values into ranges below which crops respond to fertilizer and above which they do not. Most extractants predicted critical levels with high coefficients of determination between 0.63 and 0.76. The critical value for ammonium acetate ranged from 51 to 54 milligrams per kilogram, while sodium acetate fell between 108 and 116 milligrams per kilogram. Boiling nitric acid produced the highest critical concentration, 1,224 milligrams per kilogram, but with the weakest predictive power, a coefficient of determination of only 0.35 to 0.46. Notably, critical values differed between rice and wheat for the same extractant, a reminder that soil test interpretation cannot be divorced from crop identity.

The agronomic findings were equally telling. Plots under full conservation agriculture, with residue retention in both seasons and minimal soil disturbance, outyielded conventionally tilled plots by 8.47 percent in rice and 10.72 percent in wheat, and recorded the highest potassium uptake, reaching 135.7 kilograms per hectare in rice and 112.4 kilograms per hectare in wheat. Residues appear to work through two mechanisms: their decomposition releases organic acids that dissolve potassium-bearing minerals, and the straw itself delivers a substantial potassium input back to the soil. Full conservation agriculture also raised cation exchange capacity by 19.4 percent relative to conventional tillage and boosted easily oxidizable organic carbon by 64.32 percent, changes that increase the number of adsorption sites available to hold and release potassium. Interestingly, additional potassium fertilizer did not significantly raise grain yields in this experiment, underscoring how much the residue-recycling system was already supplying.

The implications ripple outward from a single research farm in eastern Uttar Pradesh. Soil test calibration is inherently local, dependent on soil mineralogy, climate, and cropping system, and no single extractant works universally. But the message from Varanasi is clear: the global default test for potassium, ammonium acetate, captures only part of the story in soils where non-exchangeable potassium feeds crops, and it may systematically misjudge the potassium supplying power of conservation agriculture systems. Sodium acetate and the multi-nutrient extractants AB-DTPA, Mehlich I, and Mehlich III, which tap all or part of the non-exchangeable pool, tracked crop performance more faithfully. For a country where potassium fertilizer is expensive and farmers already under-apply it, a soil test that better reflects what the soil can actually deliver could save money, slow the mining of native reserves, and help sustain the rice-wheat system that feeds hundreds of millions. The researchers caution that their calibration must be validated across wider cropping systems, but the direction is unmistakable: the chemistry of measuring potassium needs to catch up with the agriculture it is meant to serve.

Subject of Research: Evaluation of chemical soil extractants for measuring plant-available potassium in long-term conservation agriculture rice-wheat systems

Article Title: Evaluating suitability of chemical extractants for measuring available soil potassium under long term conservation agriculture

Article References: Deepak, Jha, S., Singh, U. P., & Rakshit, A. (2026). Evaluating suitability of chemical extractants for measuring available soil potassium under long term conservation agriculture. Discover Soil, 3(1), Article 170. https://doi.org/10.1007/s44378-026-00330-w

Image Credits: AI Generated

DOI: 10.1007/s44378-026-00330-w

Keywords: soil potassium, chemical extractants, conservation agriculture, rice-wheat system, ammonium acetate, sodium acetate, soil testing, Indo-Gangetic plains, non-exchangeable potassium, critical concentration, Cate-Nelson, crop residue retention

The findings, published in the Journal of Agriculture and Food Research, carry serious implications for how growers interpret soil tests, not just in Florida but anywhere crops are grown on phosphorus-enriched soils. Florida’s potato industry is substantial, with roughly 6,800 hectares harvested in 2023 producing 190,500 megagrams of tubers valued at 105.4 million dollars. Because potato plants have shallow root systems, limited root hairs, and a notoriously weak ability to scavenge phosphorus from soil, the crop is heavily dependent on fertilizer inputs. Decades of repeated applications have left many fields with elevated soil-test phosphorus values, well above the thresholds where guidelines say no additional fertilizer is needed.

Yet growers in the region have repeatedly reported yield losses when they withheld phosphorus in high-testing soils. To investigate, the research team ran a factorial experiment over three growing seasons at the UF/IFAS Hastings Agricultural Extension Center. Two adjacent 0.3-hectare sites were planted with the chipping cultivar Atlantic each spring from 2023 to 2025. The sites shared a soil type, a sandy Alfisol of the Ellzey series, but differed sharply in their starting phosphorus status. Site 1 averaged 50.6 milligrams per kilogram of Mehlich-1 extractable phosphorus in the surface 15 centimeters, while site 2 averaged 110.9 milligrams per kilogram. Under the historical interpretation system, both values fall into the high or very high categories, which normally trigger no phosphorus recommendation at all.

Each site received ten treatment combinations: five phosphorus pentoxide rates, from zero up to 269 kilograms per hectare, crossed with two nitrogen rates of 168 and 280 kilograms per hectare. The team tracked soil phosphorus and mineral nitrogen through the profile, measured plant biomass and nutrient uptake at 50, 70, and 90 days after planting, and mechanically harvested and graded tubers according to USDA size classes. A total of 240 plot-level observations across six site-years fed into the analysis.

The results were striking. At site 1, the field with the lower starting phosphorus, fertilization raised total yield from 21.6 megagrams per hectare in the unfertilized control to an average of 30.6 megagrams across rates of 135 to 269 kilograms of phosphorus pentoxide per hectare, a gain of roughly 42 percent. Marketable yield climbed even more dramatically, from 16.4 to about 25.1 megagrams per hectare, an increase of 53 percent. Most of the gain came from intermediate-sized tubers, the A23 fraction, which jumped from 9.1 to 17.4 megagrams per hectare. Tuber specific gravity, a key quality measure for chipping potatoes, also improved. At site 2, by contrast, phosphorus rate had no significant effect on total yield, marketable yield, tuber size distribution, or specific gravity, and the yield gap between the two sites vanished once phosphorus was applied at 135 kilograms per hectare or more.

The physiological story behind those numbers is revealing. At site 1, phosphorus fertilization increased whole-plant dry biomass from 5.48 to 7.96 megagrams per hectare and nitrogen uptake from 89.5 to 132.2 kilograms per hectare, while nitrogen uptake efficiency rose from 26.8 to 42.3 percent. In other words, when phosphorus is limiting, the constraint ripples outward: restricted root and shoot growth lower the plant’s demand for nitrogen and its capacity to acquire it. Adequate phosphorus supply therefore unlocks the crop’s ability to use nitrogen efficiently. At site 2, the higher-phosphorus field, the only response to added fertilizer was a modest increase in nitrogen uptake efficiency, with biomass and productivity per unit of nitrogen unchanged. Notably, whole-plant phosphorus uptake at site 2 pulled ahead of site 1 after 50 days after planting and stayed ahead through harvest, showing that the richer soil sustained phosphorus delivery during the critical tuber-bulking period.

Nitrogen management, meanwhile, turned out to be a non-player in the phosphorus story. The two nitrogen rates produced clearly different soil mineral nitrogen levels, but phosphorus rate by nitrogen rate interactions were limited to efficiency indices, and the crop’s principal responses to phosphorus were identical under both nitrogen regimes. Raising nitrogen from 168 to 280 kilograms per hectare never increased yield and consistently reduced both nitrogen uptake efficiency and partial factor productivity, the tubers produced per kilogram of nitrogen applied. In the difficult 2024 season, when seed-piece decay cut plant stands by 57 percent, the higher nitrogen rate actually lowered total and marketable yields by about 4.4 megagrams per hectare. The team stresses this does not establish 168 kilograms as a regional optimum, only that extra nitrogen neither overcame phosphorus deficiency nor added yield when phosphorus was sufficient.

The soil itself told a story of accumulation and movement. Over the experiment, surface Mehlich-1 phosphorus in fertilized plots rose by roughly 63 to 67 milligrams per kilogram, while unfertilized controls declined by 7 to 27. Concentrations peaked near crop emergence after pre-plant fertilization and then shifted, with measurable increases detectable down to the 30 to 45 centimeter layer, particularly at site 2 in 2024. Because most potato roots in these seepage-irrigated soils sit within the top 30 centimeters, phosphorus moving below that depth is effectively out of reach for the crop and represents a potential pathway for transport off-site, although drainage losses were not directly measured in this study.

To translate the yield responses into a usable threshold, the researchers modeled relative yield against Mehlich-1 phosphorus measured at harvest using four normalization methods and several calibration models. The best-performing combination, the MAXRATE normalization paired with a modified arcsine-log model, explained 41 percent of the variation in relative yield. It estimated critical phosphorus levels of 63.6 milligrams per kilogram for 80 percent relative yield, 81.4 for 90 percent, and 96.2 for 95 percent, with the response curve flattening above roughly 100 milligrams per kilogram. Those numbers are far above the historical sufficiency threshold of about 30 milligrams per kilogram of Mehlich-1 phosphorus, and they even exceed the high category boundaries of both the Mehlich-1 and Mehlich-3 systems currently used in Florida. The moderate fit and the overlap of high- and low-yielding observations across the range reinforce a point echoed in decades of Ohio fertilizer trials: a soil test is a probabilistic index of potentially available phosphorus, not a deterministic boundary between deficiency and sufficiency.

The practical message is nuanced. A high soil-test classification does not guarantee a field will ignore added phosphorus, and skipping fertilizer in a responsive high-testing soil can be costly; conversely, blanket phosphorus applications to nonresponsive soils simply inflate soil phosphorus reserves and environmental risk. The authors caution that their critical level of 96.2 milligrams per kilogram derives from a specific soil, cultivar, sampling protocol, and set of conditions, and that each initial phosphorus status was represented by a single site with different irrigation infrastructure, so broader calibration and independent validation are needed before any new threshold enters recommendations. Still, the study makes a compelling case that Florida’s provisional allowance of up to 134 kilograms of phosphorus pentoxide per hectare, applied regardless of soil test, is a blunt instrument. A validated critical level could enable a tiered strategy: full fertilization below the threshold, crop-removal-based maintenance near it, and deliberate drawdown above it, protecting both potato yields and the waterways downstream of phosphorus-enriched sands.

Subject of Research: Potato yield and nutrient uptake responses to phosphorus fertilization in phosphorus-enriched sandy soils

Article Title: Initial soil phosphorus status governs potato yield and nutrient uptake responses to fertilization in P-enriched sandy soils

Article References: Oliveira, J. D. M., de Castro, G. F., da Silva, B. A., Clark, M. W., Nunez, G. H., Guzmán, S., & Zotarelli, L. (2026). Initial soil phosphorus status governs potato yield and nutrient uptake responses to fertilization in P-enriched sandy soils. Journal of Agriculture and Food Research, 31, Article 103296. https://doi.org/10.1016/j.jafr.2026.103296

Image Credits: AI Generated

DOI: 10.1016/j.jafr.2026.103296

Keywords: phosphorus, potato, soil testing, Mehlich-1, fertilizer recommendations, sandy soils, nitrogen use efficiency, critical phosphorus level, Florida agriculture, nutrient uptake, soil fertility, alfisols

The physical basis of the technique rests on two fundamental processes. Molecular vibrations, the bending and stretching of chemical bonds when they absorb radiation matching their vibrational frequency, produce characteristic absorption bands that dominate the shortwave-infrared and mid-infrared regions. Electronic transitions between atomic orbital energy levels generate absorptions concentrated in the visible range. The key soil chromophores are well understood: organic matter darkens reflectance progressively as carbon content rises, iron-bearing minerals such as hematite and goethite leave distinctive fingerprints through charge transfers and crystal-field transitions, and clay minerals produce O-H stretching and Si-O-Al bending signatures at defined wavelengths. Because these features overlap and interact, no single wavelength maps cleanly onto a single soil property; instead, chemometric and machine-learning models must untangle the composite signal.

The review, led by Tushar Kumar of Maharana Pratap University of Agriculture and Technology in Udaipur, traces the field from the X-ray and microscopical studies of soil colloids in the 1930s through Condit’s foundational 1970 spectral library of American soils to the digital revolution of the 1980s and 1990s, when chart recorders gave way to instruments capturing thousands of data points per spectrum. Today the instrumental ecosystem spans laboratory benchtop analysers, portable handheld sensors, drone-mounted hyperspectral cameras, and satellite-borne spectrometers. Vis-NIR instruments operating from 350 to 2500 nanometres have been miniaturized into smartphone-compatible units, while the most sensitive mid-infrared systems still require liquid nitrogen cooling, confining them largely to well-resourced laboratories.

On the central question of which spectral region performs better, the evidence is nuanced. A comprehensive synthesis by Soriano-Disla and colleagues concluded that mid-infrared spectroscopy outperforms Vis-NIR for pH, soil organic carbon, cation exchange capacity, particle-size fractions, phosphorus, and potassium, because MIR wavelengths probe directly the functional groups that govern these properties. Yet biological properties such as microbial biomass carbon are more reliably predicted in the visible-near infrared, whose chromophores respond to the organic matrix in which biological activity is embedded. Practical considerations sharpen the trade-off: portable NIR units are dramatically cheaper and more field-deployable, making them the default for large surveys, while MIR’s theoretical advantage justifies its cost only for properties where the accuracy gain is significant.

Raw spectra, the review stresses, are rarely fit for modelling. Variable sample packing, particle-size differences, moisture, and instrument drift superimpose additive and multiplicative distortions on the true signal. Pre-processing is therefore integral, not optional. Standard steps include trimming noisy spectral extremes, converting reflectance to absorbance via the Beer-Lambert relationship, smoothing with Savitzky-Golay filters that preserve peak shape better than simple averaging, and scatter correction through the standard normal variate transformation, which centres each spectrum to zero mean and unit variance. Derivative transformations sharpen overlapping bands. Crucially, the review cites evidence that no universally optimal pre-processing sequence exists; the best combination depends on soil type, instrument, property, and model, and reported optima shift with spectral resolution rather than converging on a single setting.

Among prediction models, partial least squares regression remains the dependable baseline. Unlike principal component regression, which selects components by spectral variance rather than predictive relevance, PLSR extracts latent variables that maximize covariance with the target property, making it robust against the severe collinearity of spectral data. Where the spectral-property relationship is genuinely non-linear, alternatives earn their keep. Support vector regression achieved R² of 0.912 for total nitrogen in one study, and ensemble tree methods such as random forests outperformed PLSR for available sulphur. Deep-learning architectures including convolutional neural networks have produced strong results at global scale, but the review counsels caution: CNNs are data-hungry, overfit readily on the small local datasets typical of a single regional survey, and their reported gains over well-tuned classical baselines are frequently modest and inconsistent. The most defensible use of deep learning in data-scarce settings is transfer learning, pre-training on large external libraries and fine-tuning locally, an approach whose advantage for heterogeneous soils remains an open empirical question.

The property-by-property verdict falls into three reliability tiers. Clay and texture, soil organic carbon, moisture, cation exchange capacity, calcium, magnesium, and total nitrogen sit in a robust tier, predicted well wherever calibration is representative, with texture predictions across studies reaching R² values of 0.67 to 0.87 and organic carbon reaching R² of 0.89 in some Vis-NIR calibrations. A conditional tier, including pH, potassium, sorbed phosphorus, bulk density, and aggregate properties, is predictable only through proxies such as clay mineralogy and organic matter, so performance travels poorly between soils. A weak tier remains unreliable regardless of model: electrical conductivity in non-saline soils, extractable plant-available phosphorus, and DTPA-extractable micronutrients, whose trace concentrations are swamped by the spectra of dominant constituents. Potassium illustrates the contradictions sharply, with one study reporting R² of 0.41 and another 0.84, the difference hinging on whether soils contain abundant, spectrally active potassium-bearing clays such as illite.

The review is unsparing about the field’s untested assumptions. Laboratory reference measurements are treated as error-free ground truth despite carrying their own uncertainties; the chromophore framework, which assumes spectral features arise from a stable, approximately additive set of constituents, has never been subjected to systematic perturbation experiments; and model transferability is assumed whenever a global library calibrates predictions for a new region, even though Indian studies consistently report weaker performance than global benchmarks promise. Five frontier questions are identified, chief among them whether spectroscopy can deliver transferable predictions across the extreme variability of landscapes like Udaipur in Rajasthan, where soils range from red gneissic types at 1300 metres to deep black Vertisols on the plains.

For India, whose Soil Health Card programme has issued 24.74 crore cards through 8,272 laboratories, the realistic near-term role for spectroscopy is complementary rather than substitutive: rapid spectral screening for well-supported properties, reserving wet chemistry for extractable phosphorus, potassium in low-illite soils, and micronutrients. Global-to-local transfer learning offers a tested shortcut, with one study reporting lower error in 91 percent of comparisons after transfer, but local reference samples and independent validation remain indispensable. The review also flags data governance concerns, noting that digital soil mapping ties fertility records to identifiable landholdings and calling for consent, de-identification, and access controls as spectral monitoring scales.

The ultimate message is that diffuse reflectance spectroscopy has matured from a mineral identification tool into a credible multi-property platform underpinning digital soil mapping and precision agriculture, yet the field’s next advance will come not from another incremental model comparison but from rigorously testing its own foundations. Whether the technology can finally deliver affordable, trustworthy soil surveillance to the farmers who depend on it will be decided by the answers.

Subject of Research: Advances in diffuse reflectance spectroscopy for rapid soil fertility assessment

Article Title: A critical review of advances in diffuse reflectance spectroscopy for rapid soil fertility assessment

Article References: Kumar, T., Yadav, K. K., Meena, R. H., Lakhawat, S. S., & Jat, G. (2026). A critical review of advances in diffuse reflectance spectroscopy for rapid soil fertility assessment. Discover Soil, 3(1), Article 160. https://doi.org/10.1007/s44378-026-00314-w

Image Credits: AI Generated

DOI: 10.1007/s44378-026-00314-w

Keywords: diffuse reflectance spectroscopy, Vis-NIR, MIR, soil fertility, soil organic carbon, PLSR, machine learning, digital soil mapping, spectral pre-processing, soil testing, transfer learning, India