2026

Digital soil mapping (DSM), based on multimodal satellite data, is a crucial tool for the transition to precision agriculture. However, systematic studies using this method and machine and deep learning techniques are lacking for the arid and semi-arid regions of Central Asia, where multimodal satellite data can provide valuable insights into soil conditions. This work provides, for the first time, benchmark metrics for the predictive ability of six soil agrochemical properties (pH, Soil Organic Carbon, NO3, P2O5, K2O, and S) in the dry steppe zone of Central Asia, with a quantitative assessment of the difference between "standard" and "fair" validation strategies. This has methodological significance for the entire field of DSM research. A comprehensive comparison of 11 machine learning (ML) models and four deep learning (DL) architectures was conducted to predict soil agrochemical properties using a set of 530 features extracted from various satellite datasets. These features were extracted from Sentinel-2, Landsat-8, Sentinel-1 SAR, SRTM DEM, and ERA 5-Land using Google Earth Engine (GEE) automated pipeline. All models were evaluated using three spatial validation strategies with increasing stringency: Leave-One-Field-Out CV (LOFO-CV), Leave-One-Farm-Out CV (Farm-LOFO), and an optimized spatial split. We propose a three-level hierarchical validation scheme that allows for the quantitative separation of spatial leakage and feature selection leakage, a methodology that can be applied to any spatial ML problem. Local models have been shown to outperform the global SoilGrids v2.0 product in terms of accuracy, demonstrating the need for high-resolution regional models for precision agriculture. Local models outperformed SoilGrids v2.0 by 3.6 & times; in Spearman rho for pH (0.750 vs. 0.208), quantitatively confirming the necessity of regional calibration over global soil products. Multi-season ConvNeXt with SE-blocks on 54-channel composites improved R2 for NO3 by 36% (0.422 -> 0.575), confirming the value of temporal dynamics for mobile elements; however, it underperformed RF on tabular features for most properties at the available sample size (n = 1085).

The study examines how food security operates at the national level in the Republic of Kazakhstan, using the grain sector as a focal case. The analysis responds to a gap in empirical research that connects agricultural investment, grain production trends, and food price behavior within one food security framework. The study relies on national statistical data from Kazakhstan for the period 2015-2023. The analysis applies descriptive statistics, trend analysis, and correlation assessment to gross grain and legume harvests, per capita consumption of staple foods, fixed capital investment in agriculture, forestry, and fisheries, agricultural lending volumes, and food price inflation. A SWOT analysis complements the quantitative results and places them within existing institutional and market conditions. The findings show a general rise in grain and legume output over the study period, alongside marked year-to-year volatility. Consumption data confirm the central role of grain-based foods in household diets. Correlation results show a strong statistical association between fixed capital investment in agriculture-related sectors and food price inflation (R 2 = 0.9238). The relationship reflects structural co-movement rather than direct causation. The SWOT analysis highlights key strengths of Kazakhstan's grain sector, including high production capacity, export potential, developed infrastructure, and state support. At the same time, it reveals ongoing weaknesses linked to climate exposure, narrow production structure, and transport and logistics limits. The study offers an integrated empirical view of food security in Kazakhstan that links production, investment, and price dynamics within a single system-based approach. The results inform policy discussions on grain sector resilience and national food security. Stable investment conditions, technological renewal, and effective risk management emerge as central priorities. The analysis also creates a basis for future research using advanced econometric methods and cross-country comparison.

Background and Aim: Brucellosis is a chronic infectious disease of cattle that may influence not only animal health but also the nutritional and sanitary quality of meat. While veterinary-sanitary implications of infected carcasses are well documented, limited information is available on the biochemical composition of meat derived from chronically infected animals. This study aimed to evaluate the veterinary-sanitary status, organoleptic characteristics, and biochemical composition of beef obtained from cattle with chronic brucellosis compared with clinically healthy animals. Materials and Methods: An observational comparative cross-sectional study was conducted using post-slaughter samples collected within official veterinary surveillance programs. A total of 250 meat samples were subjected to veterinary-sanitary and organoleptic assessment, including animals diagnosed with brucellosis, leukemia, tuberculosis, and leptospirosis. Biochemical analysis was restricted to chronic brucellosis and matched controls (n = 100 per group). Standardized methods were used to determine proximate composition, mineral content, vitamin levels, fatty acid profile, and amino acid composition. Statistical analysis was performed using independent Student's t-test, with significance set at p <= 0.05, and false discovery rate correction applied for multiple comparisons. Results: Veterinary-sanitary assessment revealed a higher proportion of carcass alterations and conditional suitability in infected animals compared with controls. Organoleptic evaluation indicated mild but consistent changes in color, texture, and overall quality of meat from infected cattle. Biochemical analysis demonstrated significant alterations in nutrient composition in the infected group, including reduced protein content and modifications in lipid fractions. Changes in fatty acid composition were observed, with variations in saturated and unsaturated fatty acids and altered polyunsaturated to saturated fatty acids and n-6 to n-3 ratios. Mineral and vitamin profiles also exhibited measurable differences between groups. Effect size analysis confirmed moderate to large differences for several key nutritional parameters, indicating biologically relevant impacts of chronic infection on meat quality. Conclusion: Chronic brucellosis is associated with measurable alterations in the biochemical composition and veterinary-sanitary quality of beef. Although meat from infected animals may remain conditionally suitable for consumption following regulatory assessment, its nutritional value can be compromised. These findings highlight the importance of integrating veterinary disease status into meat quality evaluation frameworks and support the need for continued surveillance and risk-based assessment in meat inspection systems

The presented study analyzes the international experience in conceptualization and assessment of land degradation in the context of achieving the Sustainable Development Goals (SDGs). It is a well-known fact that the traditional approach to differentiated interpretation of land degradation is insufficient and requires numerous adjustments. From ecological, economic, and social perspectives, the necessity of a comprehensive interpretation of land degradation needs substantiation. The importance of considering the close association of these aspects entails emphasis. In this study, the proposed land degradation underwent an analysis of the scale of degradation in the modern world. It was well noted that up to 40% of the planet's soils reached degradation to some extent, and the total degraded land areas amounted to about 15% of terrestrial lands. The said problem is most acute in developing countries. Giving specific attention is essential to sustainable land management, which can ensure the prevention of land degradation to achieve significant ecological, economic, and social benefits.

Postharvest loss of tropical fruits remains a significant challenge for food security and sustainability, as their delicate texture and high metabolic activity make them highly susceptible to rapid deterioration through handling and distribution. This study investigates the application of an edible coating technique to reduce loss, deterioration, and spoilage, and to increase the shelf-life of guava fruit. The fruits were immersed in chitosan and edible oils (moringa, lemongrass, marjoram, and rosemary). Chitosan (2%) and 1-2% moringa oil extended the shelf life of fruits by up to 24 days. Moringa oil at 1-2% mitigated the loss in fruit weight compared to 1% chitosan after the 24th day of storage, and the fruits had superior quality attributes (TSS, vitamin C, sugar content). The findings show that 2% chitosan and 1-2% moringa oil were the most effective treatments, reducing weight loss to about 10-25% compared to nearly 50% in untreated fruits and maintaining overall fruit quality. These treatments boosted peroxidase (POD) activity, reaching a peak of 76.47 U/g and keeping hydrogen peroxide (H2O2) levels low at 24.25 & micro;mol g-& sup1; FW, signalling strong protection against oxidative stress. On the chemical side, they maintained higher total soluble solids (13.17 degrees Brix), total sugars (11.36%), and vitamin C (32.49 mg/100 mL), while keeping acidity lower (0.82%). By comparison, lemongrass and marjoram oil treatments were far less effective, showing faster weight loss and oxidative damage levels similar to those of the control group. Chitosan and oil coatings substantially reduce bacteria and yeasts/moulds on guava fruits, and moringa oil treatment improved physio-biochemical characteristics and reduced postharvest disease spoilage. The results highlight that natural coatings, particularly chitosan and moringa oil, not only preserved the physio-biochemical quality of guava but also offered a sustainable, biodegradable solution that can help reduce food loss, limit reliance on synthetic chemicals, and support environmentally responsible postharvest management practices.

Computerized adaptive testing (CAT) systems face major challenges at the beginning of test administration, when limited response data produces unstable ability estimates and poor item selection. This cold-start problem reduces measurement precision and testing efficiency, especially for students whose abilities diverge from population norms. This study introduces a hybrid ability-estimation model that dynamically integrates neural network predictions with classical item response theory (IRT) estimation throughout the adaptive testing process. The neural component uses auxiliary student information-including demographics, prior performance, and early response patterns-to generate accurate initial ability estimates, while the IRT component preserves psychometric validity as response data accumulate. A dynamic fusion mechanism gradually shifts estimation weight from the neural model to the IRT model as more items are administered. Experimental validation on 2847 students across four subject domains shows that the hybrid approach reduces RMSE in ability estimation by 34.2% during the first five items compared with traditional CAT methods, while maintaining equivalent precision in later stages. The system also decreases the number of items required to reach target precision (SE < 0.3) by 28.7% on average, with the largest gains observed for students at ability extremes.

Garlic is a widely cultivated vegetable valued for its health-promoting compounds. This study investigated the effects of humic acid (HA) and potassium (K) on garlic productivity, bioactive compounds, and nutrient uptake. A field trial was conducted to evaluate treatments combining potassium sulfate (120 and 150 kg K2O ha-1) and humic acid (10 and 20 kg ha-1). Potassium and humic acid significantly enhanced garlic performance, with combined treatments producing the most potent effects. Applying humic and K significantly increased productivity. Photosynthetic pigments increased up to 22% for chlorophylls and 45.7% for carotenoids, improving photosynthesis and photoprotection. HA raised TSS by 20% and vitamin C by 32%. Potassium enhanced TSS by 24%, carbohydrates by 3%, and vitamin C by 28%. Combined treatments maximized TSS (+32%) and vitamin C (+38%), with polyphenols restored to 40%. Bioactive compounds, metabolites, and antioxidants were enhanced, with proline up to 45%, H2O2 up to 55.7%, APX up to 25%, SOD up to 42%, and CAT up to 25-79%, indicating improved osmotic and oxidative management. Nutrient uptake (N, P, Ca, Mg, S, and K) improved markedly, highlighting balanced nutrient allocation from leaves to cloves. Moderate combinations (K120+HA10) maximized yield, improved photosynthetic pigments, increased vitamin C and total soluble solids, and balanced nutrient allocation between cloves and leaves. These results demonstrate that integrating HA and K provides a practical strategy to support sustainable production under nutrient-efficient management.

Sowing represents one of the most critical technological processes in grain production, where seed distribution uniformity directly impacts crop yield by determining plant nutrition area efficiency. Conventional sowing methods with varying row spacings often fail to ensure optimal area utilization. This study enhances subsoil-broadcast sowing quality through a novel trough-profile seed guide that ensures uniform seed distribution across the sweep opener's working width. The research employed a combined methodology of theoretical analysis, DEM simulation, and experimental studies. Theoretical analysis demonstrated that sowing parameters depend mainly on seeder forward speed and the rotational speed of the seed-metering device's rollers. DEM simulations visually confirmed the mechanism of ordered seed flow formation within the guide. Experiments simulated drill seeder operation, evaluating forward speed (1.2-2.4 m/s) and fluted roller rotational speed (20-25 rpm) effects on distribution uniformity and sowing instability. The results at 20 rpm with 2.0-3.0 grains per cell showed a standard deviation reaching 0.2-0.5 pcs. (CV: 13.0-24.2%). At 25 rpm, the deviation increased to 0.5-1.0 pcs. (CV: 18.2-39.4%). For total sowing instability at 20 rpm with 10.0-15.0 grains per opener, the standard deviation measured 0.3-3.3 pcs. (CV: 2.8-22.4%), while at 25 rpm, with 15.0-19.0 grains, values reached 0.5-3.9 pcs. (CV: 3.5-19.8%). All parameters conform to agrotechnical requirements, confirming solution effectiveness and addressing the literature gap in uniform seed distribution across the sweep opener's working width.

Context and problem: As potato is one of the four major food crops, enhancing yield is crucial, particularly when considering the mitigation of environmental impacts. Deep fertilization represents a potential strategy for efficient nutrient utilization; however, its specific on potato yield, quality and greenhouse gas emissions require further elucidation. Methods: We conducted a four-year field experiment (2020-2023) using potatoes as the test crop. We investigated the impacts of four fertilization depths (D5, 5 cm, control with locally conventional fertilization depth; D15, 15 cm; D25, 25 cm; D35, 35 cm) on soil C, N, and P content and ratios, enzyme activity, greenhouse gas emissions, potato growth, yield, and quality. Results: Deep fertilization significantly increased the soil SOC:TN, SOC:TP, MBC:MBN, and SIC:SIN ratios, while decreasing the MBC:MBP, MBN:MBP, and POC:PON ratios. In addition to soil catalase, the activities of invertase, urease and phosphatase were closely related to the soil C:N:P ratio. Specifically, deep fertilization increased soil invertase and phosphatase activities but decreased catalase and urease activities. Correlation analysis showed that N2O and CO2 emissions were positively correlated with soil urease activity, whereas CH4 uptake and CO2 emissions were negatively correlated with soil phosphatase and sucrase activities, respectively. Furthermore, increase of soil phosphatase activity enhanced the leaf area index, net photosynthetic rate, and dry matter accumulation of potato while reducing stem lodging, ultimately improving yield and quality. Among these treatments, D25 achieved the highest improvements in large potato rate (16.4 %) and yield (11.5 %), while simultaneously resulting in high tuber quality in starch (42.5 %), reducing sugar (52.7 %), protein (33.4 %), and vitamin C (31.9 %) content. In addition, its greenhouse gas emission intensity was also at the lowest level (decreased by 32.7 %). Conclusions: Deep fertilization affects enzyme activity by altering soil C:N:P ratios, thereby promoting potato production and reducing greenhouse gas emissions. In this region, fertilization depths of 15-25 cm exhibited distinct advantage in terms of yield enhancement, whereas depths exceeding 35 cm were more effective in reducing emissions.

Purpose. To investigate the regularities of reactive species formation during the plasma treatment of multicomponent wastewater from the mining and petroleum industries, as well as to assess their role in contaminant transformation and removal efficiency. Methods. Laboratory experiments were carried out using a specially designed plasma-liquid reactor operating under high-frequency electrical discharge conditions (10-25 kV, 10-30 kHz, interelectrode gap 3-7 mm). The study included determination of the initial physicochemical characteristics of wastewater, including pH, electrical conductivity, total dissolved solids, and concentrations of heavy metals (Cu, Zn, Cd). During plasma treatment, the formation of reactive species (center dot OH, O3, H2O2) was analyzed, and a kinetic model was applied to describe contaminant removal dynamics and treatment efficiency. Findings. It was established that plasma treatment leads to the formation of hydroxyl radicals at a rate of (1-5)& centerdot;10-6 mol & centerdot;L-1 & centerdot;s-1, ozone in the concentration range of 10-6-10-4 mol & centerdot;L-1, and hydrogen peroxide accumulation within 10-80 mg/L, thereby creating a pronounced oxidative environment. Copper concentration decreased from 20 to 0.5 mg/L (97.5%), zinc from 15 to 0.4 mg/L (97.3%), and cadmium from 0.5 to 0.02 mg/L (96.0%). The degree of organic contaminant degradation reached 70-90%. It was shown that the intensity of reactive species formation strongly depends on discharge parameters, while the proposed kinetic model adequately describes the experimentally observed treatment dynamics. Originality. The study provides a comprehensive experimental and model-based analysis of reactive species formation during the plasma treatment of highly mineralized multicomponent wastewater from the mining and petroleum industries. Quantitative relationships were established among discharge parameters, reactive species generation, and contaminant removal efficiency. Practical implications. The obtained results confirm the potential of plasma technologies for the advanced treatment of industrial wastewater with complex composition and high salinity. Practical implementation of the proposed approach may contribute to improved environmental safety, reduced reagent consumption, lower sludge generation, and expanded opportunities for water reuse in mining and petroleum production processes.

The aim of this study was to analyze the nutritional value of feed mixtures and premixes produced by selected feed manufacturers in southeastern Kazakhstan for dairy farms. The feed mixtures produced in the analyzed feed mills differed significantly (p <= 0.01 and p <= 0.05) in terms of their basic nutrient content. The amino acid, mineral, and vitamin composition of the feed mixtures was neither monitored nor balanced, except in the Good-Zhem feed mill, as the facilities did not produce mineral-vitamin premixes. For research purposes, the Kormovik and Vet Effect feed mills developed premixes for lactating cows, dry cows, and young cattle aged 6-12 months. The premixes contained high levels of minerals, including Ca, P, Mg, Na, Cl, Cu, Zn, Mn, Co, Se, and I, as well as vitamins A, D, and E. For high-yielding cows from the OST group and for cows in the first dry period (period I), an antioxidant was added at levels of 177 mg kg-1 and 95 mg kg-1, respectively. Additionally, for low-yielding cows and cows in the second dry period (period II), supplementary vitamins were included: K, B1, B2, B4, B5, B6, B9, B12, and PP. The experimental premixes used in cattle feeding on the JSC AIC Adal farm allowed the maintenance of milk yield in cows, kept there at the level of 8 000 kg of milk. The research shows that including a premix in cattle feed rations helps to balance ratios in terms of their nutritional value and content of minerals and vitamins, which ultimately enables better use of the animals' genetic potential.