Search Results (414)

Degraded industrial sites in arid and semi-arid regions often suffer from loose surface substrates, weak water-retention capacity, high wind-erosion risk, and poor early vegetation establishment. Combining photovoltaic (PV) deployment with ecological utilization may improve near-surface habitats by shading, reducing wind speed, and regulating soil heat and moisture. This study investigated an ash storage yard of a coal-fired power plant in Ordos, Inner Mongolia, China, by comparing soil temperature, soil moisture, and near-surface wind-speed responses under three representative fixed PV tilt angles of 36°, 43°, and 50°, together with the corresponding early plant-growth suitability. A multi-physics model coupling near-surface airflow, water-vapor transport, and porous-media hydrothermal migration was established. A Gaussian suitability function combined with AHP-CRITIC weighting was used to construct a model-based comprehensive growth index (CGI) from soil temperature and moisture, while short-term field monitoring was used to validate afternoon soil hydrothermal trends. Among the three scenarios, the 36° configuration produced the widest horizontal heat–moisture-affected zone and the highest CGI values for alfalfa and Elymus nutans, reaching 0.7741 and 0.6875, respectively. Relative to the outside reference area, the rear PV zone reduced the near-surface wind speed by 33–40% and increased the plant heights of alfalfa and Elymus nutans by 49.4% and 37.8%, respectively. A first-order PVsyst assessment showed that the 43° configuration achieved the highest specific energy yield of 1814 kWh kWp⁻¹ year⁻¹, whereas the annual grid-connected output at 36° was only 0.59% lower. These findings indicate that the 36° configuration may provide a favorable compromise between early vegetation establishment and photovoltaic electricity generation among the tested scenarios. By linking renewable-energy production with microenvironment regulation and early vegetation establishment, the proposed framework provides a decision basis for the multifunctional and sustainable reuse of degraded industrial land. Nevertheless, the results represent a site-specific, single-season assessment and should not be interpreted as a universal optimum. Full article

The scarcity of effective selective herbicides has made weed management a limiting factor for alfalfa yield and large-scale cultivation. This study aimed to preliminarily screen selective herbicides with acceptable safety to alfalfa and establish an effective weed management program based on sequential pre- and post-emergence herbicide applications through greenhouse screening and multi-year field trials. The greenhouse herbicide safety evaluation showed that, among the 22 herbicides tested, the post-application of 2 pre-emergence herbicides (s-metolachlor and prodiamine) and 5 post-emergence herbicides (benazolin, bentazon, fluazifop-p, imazethapyr, and nicosulfuron) showed a relatively higher survival rate (~4× the standard dose) on two alfalfa cultivars through assessing visual efficacy, plant height, and dry biomass per plant. However, even herbicides that result in relatively high plant survival can produce induce significant growth inhibition and biomass reduction when applied at high doses. Those herbicides were further tested under field conditions (2020–2023) for evaluation of weed control efficiency and alfalfa plant biomass yield potential and nutritive values. Among the herbicide application regimes, the pre-application of prodiamine followed by post-application of bentazon or fluazifop-p showed the most effective weed control efficacy (70–85% reduction of weed biomass in the alfalfa plot), which was greater than the reductions achieved with all single-herbicide applications (24–48%) and sequential application of s-metolachlor followed by the five post-emergence herbicides (25–46%). Additionally, the optimized combinations had no significant effect on the 1st and subsequent alfalfa plant height compared to that of alfalfa in weed-free control. No significant reductions in alfalfa yield or nutritive value were observed in the herbicide-treated plots treated with prodiamine followed by bentazon or fluazifop-p compared with the weed-free control. Collectively, sequential application combining pre- (prodiamine) and post-emergence (bentazon or fluazifop-p) herbicides shows effective weed control in alfalfa under the tested conditions, which provides a useful weed management program to enhance alfalfa forage production and nutritive values. Full article

Salt stress is a prevalent abiotic stress worldwide, which markedly inhibits crop growth and triggers yield losses. In this study, salt-tolerant plant-growth-promoting rhizobacteria of Cerasus humilis—Bacillus pumilus and B. velezensis, which possess nitrogen-fixing, phosphate-solubilizing, and indole-3-acetic acid (IAA) and 1-aminocyclopropane-1-carboxylate (ACC) deaminase-producing traits—were co-inoculated with Sinorhizobium meliloti. The effects of these bacterial combinations on alfalfa (Medicago sativa L.) were systematically evaluated during seed germination and plant growth under salt stress simulated using NaCl, Na₂SO₄, NaHCO₃, and Na₂CO₃ at varying intensities. The results showed that under salt stress, inoculation significantly increased the seed germination rate by 11.33–41.33%. Pot experiments further revealed that inoculation significantly enhanced symbiotic nitrogen fixation efficiency in alfalfa and effectively maintained K⁺/Na⁺ homeostasis (K⁺ concentration increased by 4.23–125.34%, while Na⁺ concentration decreased by 7.15–102.09%). Concurrently, inoculation upregulated antioxidant enzyme activities and promoted the accumulation of non-enzymatic antioxidants, thereby significantly reducing reactive oxygen species levels. Moreover, inoculation substantially increased the content of osmoregulatory substances such as proline and soluble protein; proline accumulation surged more than fivefold (39.97–551.05%) compared with the non-inoculated control, effectively alleviating cellular dehydration. Through these multi-pathway regulations mediated by Bacillus sp. and S. meliloti, the inhibitory effect of salt stress on alfalfa growth was significantly mitigated, with dry weight increasing by 45.9–92.4%. Principal component analysis indicated that inoculation with the B. velezensis–S. meliloti microbial combination was the most promising strategy for promoting alfalfa growth and alleviating salt stress. The results provide a theoretical basis for developing microbial fertilizers and establishing alfalfa pastures in saline lands, thereby promoting their sustainable utilization. Full article

The convective drying of agricultural materials is an energy-intensive process, and optimizing dryer design is critical for improving efficiency and product quality. This study presents a comprehensive heat and mass transfer model for the convective drying of alfalfa leaves in a rotary drum dryer. Freshly harvested leaves with an initial moisture content of approximately 70% (w.b.) were used as the test material. The proposed system features a simplified drum design aimed at enhancing process efficiency while reducing equipment complexity. The primary objective was to reduce the moisture content of alfalfa leaves to below 50% to ensure their quality during subsequent storage and transportation. To determine the optimal operating conditions, the kinematics of leaf motion inside the rotating drum and the associated heat and mass transfer phenomena were investigated through analytical modeling, numerical simulation, and experimental studies on a laboratory-scale physical model. An analytical model was developed to establish relationships between transverse kinematic characteristics (detachment condition, Froude number, drum inclination angle), average longitudinal velocity, and residence time. Numerical simulations based on the Navier–Stokes equations (continuity, momentum, and energy) provided detailed moisture content distributions within individual leaves under varying airflow orientations and drying durations. The novelty of this work lies in the integrated determination of optimized operating parameters through combined analytical, numerical, and experimental approaches. A regression model relating final moisture content to key process variables (air velocity, temperature of 60 °C, drum rotation frequency and mass of loaded material) was developed from experimental data, yielding practical recommendations for the design and operation of rotary drum dryers for alfalfa and similar agricultural materials. Full article

Water and nitrogen application rates directly affect crop yield formation and protein accumulation. Nitrogen metabolism, as a key physiological process linking water and nitrogen supply with crop growth, plays a critical role in regulating nitrogen uptake, transformation, and accumulation. However, the functional relationships among different nitrogen metabolism indicators in mediating the formation of high-quality and high-yield alfalfa under water–nitrogen regulation remain unclear. In this study, alfalfa (Medicago sativa L.) was subjected to four nitrogen application levels [N0 (0 kg·hm⁻²), N1 (80 kg·hm⁻²), N2 (160 kg·hm⁻²), N3 (240 kg·hm⁻²)] and four irrigation gradients [severe deficit (W0, 45–60% θ_f), moderate deficit (W1, 55–70% θ_f), mild deficit (W2, 65–80% θ_f), and full irrigation (W3, 75–90% θ_f), where θ_f represents field capacity]. The relationships between water–nitrogen regulation and alfalfa nitrogen metabolism and productive performance were analyzed. The results showed that (1) both irrigation amount and nitrogen application rate significantly affected the activities of leaf nitrate reductase (NR), glutamine synthetase (GS), glutamate synthase (GOGAT), and soluble protein (SP) content (p < 0.05). Aboveground nitrogen content (TN) initially increased and then decreased with increasing irrigation and nitrogen application, reaching its maximum under W2N2, with leaves being the primary site of aboveground nitrogen accumulation. (2) Under W2N2, alfalfa yield and crude protein accumulation (CP-a) both reached their maximum values, averaging 10.22 t·ha⁻¹ and 1187.10 kg·ha⁻¹, respectively. (3) Structural equation modeling (SEM) indicated that water–nitrogen regulation primarily influenced yield and CP-a formation through its effects on GS activity and TN. Based on these findings, a comprehensive evaluation model (GS–TN–Yield–CP-a) was constructed, and the preliminary suitable water–nitrogen regulation ranges for high-quality and high-yield alfalfa were identified as an irrigation amount of 69.4–85.9% θ_f and a nitrogen application rate of 102.6–222.3 kg·hm⁻². These results can provide a theoretical basis for high-quality and high-yield alfalfa management in arid and semi-arid regions, but further verification through field experiments is still required. Full article

Alfalfa spring black stem and leaf spot (ASBS), caused by Ascochyta medicaginicola, threatens alfalfa yield, forage quality, and stand persistence. Conventional resistance assessments of alfalfa cultivars generally rely on disease incidence, disease severity, or the percentage of healthy plants. Although these measures describe symptom occurrence and development, they do not capture biomass retention or root growth after infection. In this study, 12 alfalfa cultivars were spray-inoculated with A. medicaginicola under greenhouse conditions and evaluated 14 days after inoculation. Disease incidence was positively correlated with the disease severity index and negatively correlated with relative fresh weight, relative dry weight, and relative root length. We integrated these five indicators using a membership-function-based standard-deviation coefficient weighting method to derive a comprehensive response score (D value). D values ranged from 0.0340 to 0.9611. Magnum 2 had the highest D value, followed by Gannong No. 3, Adrenalin, and Dryland, whereas Thunder, Zhongmu No. 1, and Aohan had the lowest values. Compared with the National Alfalfa and Forage Alliance classification based on the percentage of healthy plants, the D-value ranking provided additional discrimination among cultivars within the same resistance class under the present greenhouse conditions. The first two principal components explained 89.24% of the total variation and separated resistant, intermediate, and susceptible response types. Thus, combining disease suppression with growth retention yielded a complementary quantitative description of cultivar performance under the conditions tested. Full article

Perennial alfalfa roots form a composite with the soil, contributing to intensified grassland degradation and reduced yields. Soil-loosening and root-cutting tools are effective in disrupting root–soil composites and reducing soil compaction. However, loosening and root-cutting operations commonly face challenges, such as high tillage resistance and disturbance. This study developed a simulation model of the alfalfa root–soil composite based on the coupled Finite Element Method (FEM) and Smoothed Particle Hydrodynamics (SPH) method when considering the biomechanical properties of roots. The validity of the model was verified using direct shear and cutting tests. The errors in both simulation and test results were less than 8%. Additionally, a vibration root-cutting shovel was designed. The factors of tillage speed, vibration frequency, amplitude, and direction were analyzed for their impact on tillage resistance and root shear displacement. Results indicated that the incorporation of vibration enhanced soil breaking and reduced root-cutting displacement. The optimal combination of parameters determined using the Response Surface Method (RSM) for minimizing tillage resistance and shear displacement were a tillage speed of 0.86 m·s⁻¹, vibration amplitude of 3.79 mm, vibration frequency of 45.05 Hz, and vibration parallel to the tillage direction. Field tests confirmed the effectiveness of the vibratory root-cutting shovel. The addition of vibration parallel to the tillage direction can reduce tillage resistance by 16.68% and penetration resistance by 26.80%. This study provides a methodology for modeling root–soil composite and improving the root-cutting shovel for grassland degradation restoration. Full article

Water and nitrogen management influences farmland productivity and greenhouse gas emissions by regulating the soil micro-environment. However, the synergistic optimization strategy among yield improvement, economic benefit, and emission reduction in intercropping systems in arid regions remains unclear. Based on a two-year field experiment using an intercropping system of wolfberry and alfalfa, this study established four irrigation levels [full irrigation (W0), mild water deficit (W1), moderate water deficit (W2), and severe water deficit (W3)] and four nitrogen application levels [0 (N0), 150 (N1), 300 (N2), and 450 kg·ha⁻¹ (N3)]. The effects of water and nitrogen regulation on soil hydrothermal conditions, greenhouse gas emissions, crop yield, and economic benefits were systematically analyzed. The results showed that soil water content increased with higher nitrogen application rates but decreased with a more severe water deficit. In contrast, soil temperature exhibited the opposite trend, with the W3 treatment increasing by 2.23–2.41 °C compared to W0 during the full fruiting period. The emission fluxes of CO₂ and N₂O increased with higher nitrogen application rates but decreased with a more severe water deficit. CH₄ acted as a sink, with its uptake decreasing as nitrogen application increased and the water deficit intensified. CO₂ was the dominant contributor to the global warming potential of the intercropping system of wolfberry and alfalfa, accounting for 85.3–94.6% of the total. The emission fluxes of CO₂ and N₂O were significantly positively correlated with the soil water content, while the CH₄ emission flux was significantly positively correlated with the soil temperature. The W0N2 treatment achieved the highest system yield and net profit, whereas the W1N2 treatment exhibited the highest return on investment. A comprehensive evaluation using the entropy weight–TOPSIS model identified W1N2 as the optimal treatment. An integrated water–nitrogen decision model determined that the optimal water and nitrogen combination for achieving a high yield, a high efficiency, and low emissions was an irrigation amount of 4245–4413 m³·ha⁻¹ and a nitrogen application rate of 290–323 kg·ha⁻¹. The findings of this study can provide a scientific basis for the sustainable water and nitrogen management of characteristic cash crop intercropping systems in arid regions. Full article

Alfalfa (Medicago sativa L.) exhibits high feeding value in agricultural and livestock production, with its above-ground parts determining yield and quality. Promoting the development of molecular breeding of alfalfa helps to clarify the function of MsARG4 in regulating its growth. Obtaining MsARG4-overexpressing and RNA interference-positive plants via genetic transformation, we compared their phenotypic, nutritional, physicochemical, and cellular structural characteristics with those of wild-type plants. The results showed that the plant height, stem diameter, number of branches, number of lateral branches, internode length, and crude protein content of overexpressing plants were significantly higher than those of wild-type and RNAi plants (p < 0.05). Furthermore, we observed that the cell area of OE lines was larger than that of WT and RNAi lines. The stem-to-leaf ratio of overexpressing plants in the branching and budding stages was significantly lower than in wild-type and RNAi plants (p < 0.05). Our study suggests that MsARG4 promotes alfalfa quality improvement and rapid stem growth. Full article

Alfalfa (Medicago sativa) is an important forage source for grassland agricultural development; developing accurate and efficient methods for alfalfa identification and yield estimation using remote sensing is of considerable interest. However, the traditional methods of identifying large areas of crops and yield estimation have some problems, such as the limited spatial resolution of remote sensing data and a strong dependence on training data. In this study, using Sentinel-2 high-resolution imagery and the Google Earth Engine (GEE) platform, we constructed a cloud-free normalized difference vegetation index (NDVI) time-series dataset and proposed an effective method for alfalfa feature extraction and yield estimation. The results show that: (1) the producer’s accuracy, user’s accuracy, overall accuracy, and Kappa coefficient of alfalfa identification using the trough recognition algorithm were 98.51%, 91.67%, 94.26%, and 0.88, respectively. The total area of cultivated alfalfa identified in the study area in 2020 was estimated at 46,793.21 hm², and was mainly distributed in the northern region of the Qilian Mountains. (2) NDVI showed a highly significant correlation with alfalfa hay yield, and the power function regression model performed best, with an R² greater than 0.65. (3) The annual unit hay yield of four alfalfa cuttings was estimated at 17,497.55–32,962.10 kg/hm², with a total hay yield of 4.838 × 10⁸ kg and an average hay yield of 4464.95 kg/hm². The proposed method has significant application potential for automated and rapid remote sensing-based identification and yield estimation of large-scale alfalfa cultivation. Full article

This study evaluated the effects of replacing alfalfa hay with sulla [Sulla coronaria (L.) B.H. Choi & H. Ohashi] hay or sulla haylage in pasture-based diets for lactating Sarda ewes on milk production, milk composition, and nutrient utilization efficiency. Seventy-two mid-lactation ewes were assigned to three dietary treatments for 56 days—alfalfa hay (AH), sulla hay (SH), or sulla haylage (SHL)—all combined with 3 h/day grazing and a fixed amount of supplemental concentrate. The diets were formulated to be theoretically isoenergetic and isoproteic. Pasture nutritive value was generally comparable among the groups throughout the experimental period. Milk yield did not differ among treatments; however, fat- and protein-corrected milk (FPCM) and milk fat and protein concentrations were higher in AH compared with the sulla-based diets. Actual nutrient intake differed among treatments, with nitrogen intake (NI) being greatest in AH, consistent with the higher milk urea concentration observed in this group. Estimated apparent energy utilization efficiency (FPCM/UFL intake) showed treatment-associated differences in exploratory analyses, with lower values observed in SH compared with AH and SHL. Similarly, exploratory estimates of apparent nitrogen utilization efficiency (Milk N/NI) were highest in SHL, intermediate in SH, and lowest in AH (p < 0.001). Condensed tannins were not detected in the conserved sulla forages under the analytical conditions adopted in this study. Therefore, the observed responses were unlikely to be directly associated with detectable condensed tannin activity. Overall, the results suggest that forage conservation method may influence milk composition and estimated apparent nutrient utilization indices, with sulla haylage showing higher exploratory estimates of apparent nitrogen utilization efficiency without negative effects on milk yield under the conditions of the present study. Full article

Alfalfa (Medicago sativa L.) is widely recognized as a major forage crop, yet its role as a multifunctional biological input in sustainable horticultural production remains underexplored. This review evaluates alfalfa as a biological nitrogen source, organic fertilization resource, and biofertilizer-supporting crop within vegetable, medicinal, and perennial horticultural systems. Due to its high capacity for biological nitrogen fixation, alfalfa can supply substantial amounts of plant-available nitrogen, reducing dependency on synthetic fertilizers and supporting environmentally sound nutrient management. When used as green manure, cover crop, intercrop, mulch source, compost feedstock, or processed organic fertilizer, alfalfa enhances the soil organic carbon (SOC), improves soil structure, and increases the water-holding capacity properties particularly critical in intensive horticultural production. Higher SOC levels also contribute to the improved tolerance of horticultural crops to drought and heat stress through enhanced soil moisture retention and rhizosphere buffering. Alfalfa-based organic inputs stimulate rhizosphere microbial biomass, enzymatic activity, and functional genes associated with nitrogen cycling, strengthening plant–microbe interactions that underpin biofertilizer effectiveness. Evidence from vegetable and perennial systems indicates that alfalfa-derived amendments and rotations increase soil nitrogen availability, support yield stability, and improve soil health over the long-term. In orchards and vineyards, alfalfa cover cropping contributes to carbon sequestration, erosion control, and enhanced soil biological functioning. Overall, alfalfa emerges as a strategic species for integrating organic fertilization and biofertilizer-based approaches into modern horticultural systems, supporting reduced mineral fertilizer inputs while sustaining productivity, soil health, and environmental quality. Full article

Agricultural producers need affordable tools to estimate reference evapotranspiration (ET₀) in field conditions, especially in regions with limited access to complete weather data. In this study, the ET₀ for an alfalfa (Medicago sativa) crop was estimated using the SEG-SRM-V1 electronic system, based on the surface renewal method and validated using the FAO-56 Penman–Monteith method. The estimated ET₀ values for alfalfa ranged from approximately 4.0 to 8.5 mm day⁻¹ under the prevailing climatic conditions: periods of high temperature (21 °C to 33 °C), as measured by the system in the experimental area, with cloud cover, wind (1 to 8 m/s) and net radiation of 664 W/m² to 910 W/m². Comparisons between the two methods yielded determination coefficients of between 0.65 and 0.85, and the values of the errors (MSE, RMSE and MAE) tend to 0, which indicates that the estimates of ET₀ measured by the system (SEG-SRM-V1) are close to those obtained using the Penman–Monteith method. Similarly to the performance of open-field systems operating under atmospheric and vegetation cover conditions, these results demonstrate that high-frequency (10 Hz) air temperature measurements provide sufficient physical information to support the estimation of ET₀ in alfalfa, while the open architecture of the SEG-SRM-V1 system allows for flexibility and scalability for irrigation management applications in other crop types. Full article

Alfalfa (Medicago sativa), a globally important perennial forage legume, is widely cultivated in China, where effective weed management is essential for sustainable production. Chemical weed control, primarily relying on the herbicide imazethapyr, represents the most common strategy. Reliance on a single-herbicide program, however, may lead to inconsistent weed control under field conditions and may raise environmental concerns when higher application rates are used. To address this challenge, a two-year field study (2022–2023) was conducted to reduce herbicide inputs and identify new weed management options through tank mixtures. Initial screening identified imazethapyr, prometryn, imazapic, and 2,4-DB as safe and effective against broadleaf weeds. To broaden the control spectrum and reduce total herbicide use, haloxyfop-R-methyl was tank-mixed with each of the four broadleaf-active herbicides. The combinations haloxyfop-R-methyl + imazethapyr (36.5 + 56.3 g a.i. ha⁻¹) provided broad-spectrum weed control without compromising alfalfa performance and, importantly, reduced herbicide input at least by 25% of the recommended label dose. Additionally, the mixture of haloxyfop-R-methyl with 2,4-DB (36.5 + 506.3 g a.i. ha⁻¹) achieved effective, broad-spectrum weed control, increased alfalfa yield, and reduced total herbicide input at least by 25% of the recommended label dose. This mixture offers a useful option for diversifying weed management programs and reducing reliance on repeated imazethapyr applications. These tank mixtures represent sustainable and practical components of an integrated weed management system in alfalfa production. Full article

Yield monitoring in forage production is typically limited to chopping or baling operations, where spatial resolution is often reduced by windrow merging. This study evaluated the feasibility of estimating mass flow rate (MFR) and generating spatial yield maps at the mowing stage using sensors integrated into a windrower. Conditioning roll speed, swath shield impact force, and the displacement of spring-loaded vanes (fingers) in the crop flow were evaluated during alfalfa harvest and calibrated against measured MFR. Model performance was assessed using cross-validation, and spatial fidelity was evaluated using experimental variograms and kriged yield maps. The average MFR was 19 kg·s⁻¹ with a range of 4 to 55 kg·s⁻¹. Conditioning roll speed provided the most robust and transferable predictor of MFR (R² = 0.89, RMSE = 3.4 kg·s⁻¹), consistently outperforming impact force (R² = 0.70, RMSE = 1.9 kg·s⁻¹) and finger displacement (R² = 0.82, RMSE = 4.3 kg·s⁻¹), which were more sensitive to machine dynamics and sensor placement. Validation of the roll-speed model using an independent dataset resulted in an R² = 0.87 and RMSE of 2.62 kg·s⁻¹. Yield maps derived from roll-speed-based models exhibited clear spatial structure with correlation lengths of approximately 25–40 m, whereas the finger displacement model exhibited higher nugget effects. Yield mapping with the forage harvester showed reduced spatial fidelity compared to mowing stage estimates, as windrow merging prior to chopping caused spatial averaging that diminished recoverable fine-scale yield variability. These results demonstrate that yield monitoring at the mowing stage enabled yield estimates to complement downstream harvest data and improve characterization of within-field yield variability. Full article