Search Results (2,612)

Polyvinyl chloride (PVC) is commonly employed as mulch in agriculture to boost crop yields. However, its toxicity is often overlooked. Due to its chemical stability, resistance to degradation, and the inadequacy of the recycling system, PVC tends to persist in farm environments, where it can decompose into microplastics (MPs) or nanoplastics (NPs). The radish (Raphanus sativus L.) was chosen as the model plant for this study to evaluate the underlying toxic mechanisms of PVC NPs on seedling growth through the integration of multi-omics approaches with oxidative stress evaluations. The results indicated that, compared with the control group, the shoot lengths in the 5 mg/L and 150 mg/L treatment groups decreased by 33.7% and 18.0%, respectively, and the root lengths decreased by 28.3% and 11.3%, respectively. However, there was no observable effect on seed germination rates. Except for the peroxidase (POD) activity in the 150 mg/L group, all antioxidant enzyme activities and malondialdehyde (MDA) levels were higher in the treated root tips than in the control group. Both transcriptome and metabolomic analysis profiles showed 2075 and 4635 differentially expressed genes (DEGs) in the high- and low-concentration groups, respectively, and 1961 metabolites under each treatment. PVC NPs predominantly influenced seedling growth by interfering with plant hormone signaling pathways and phenylpropanoid production. Notably, the reported toxicity was more evident at lower concentrations. This can be accounted for by the plant’s “growth-defense trade-off” strategy and the manner in which nanoparticles aggregate. By clarifying how PVC NPs coordinately regulate plant stress responses via hormone signaling and phenylpropanoid biosynthesis pathways, this research offers a scientific basis for assessing environmental concerns related to nanoplastics in agricultural systems. Full article

In chili cultivation, obstacles to continuous cropping significantly compromise crop yield and soil health, whereas crop rotation can enhance the microbial environment of the soil and reduce disease incidence. However, its effects on the diversity of rhizosphere soil microbial communities are not clear. In this study, we analyzed the composition and characteristics of rhizosphere soil microbial communities under chili continuous cropping (CC) and chili–cotton crop rotation (CR) using high-throughput sequencing technology. CR treatment reduced the alpha diversity indices (including Chao1, Observed_species, and Shannon index) of bacterial communities and had less of an effect on fungal community diversity. Principal component analysis (PCA) revealed distinct compositional differences in bacterial and fungal communities between the treatments. Compared with CC, CR treatment has altered the structure of the soil microbial community. In terms of bacterial communities, the relative abundance of Firmicutes increased from 12.89% to 17.97%, while the Proteobacteria increased by 6.8%. At the genus level, CR treatment significantly enriched beneficial genera such as RB41 (8.19%), Lactobacillus (4.56%), and Bacillus (1.50%) (p < 0.05). In contrast, the relative abundances of Alternaria and Fusarium in the fungal community decreased by 6.62% and 5.34%, respectively (p < 0.05). Venn diagrams and linear discriminant effect size analysis (LEfSe) further indicated that CR facilitated the enrichment of beneficial bacteria, such as Bacillus, whereas CC favored enrichment of pathogens, such as Firmicutes. Fusarium solani MG6 and F. oxysporum LG2 are the primary chili root-rot pathogens. Optimal growth occurs at 25 °C, pH 6: after 5 days, MG6 colonies reach 6.42 ± 0.04 cm, and LG2 5.33 ± 0.02 cm, peaking in sporulation (p < 0.05). In addition, there are significant differences in the utilization spectra of carbon and nitrogen sources between the two strains of fungi, suggesting their different ecological adaptability. Integrated analyses revealed that CR enhanced soil health and reduced the root rot incidence by optimizing the structure of soil microbial communities, increasing the proportion of beneficial bacteria, and suppressing pathogens, providing a scientific basis for microbial-based soil management strategies in chili cultivation. Full article

Drosophila suzukii is an invasive pest of many fruit crops worldwide. Employing the Sterile Insect Technique (SIT) could mitigate D. suzukii population growth and crop damage. This study evaluated the efficacy of SIT on commercial fruit, by (1) validating the quality of irradiated sterile males (male mating competitiveness, courtship, and flight performance) in the laboratory, and (2) assessing population suppression and fruit damage reduction in commercial raspberry fields. Treatment with SIT was compared to the grower’s standard chemical insecticide program throughout the season. The principal metrics of efficacy were trap counts of wild adult female D. suzukii in crops and larvae per fruit during harvesting. These metrics together with monitoring of border areas allowed targeting of high-pressure areas with higher releases of sterile males, to maximise efficacy for a given release number. The sterile male D. suzukii were as competitive as their fertile non-irradiated counterparts in laboratory mating competitiveness and flight performance studies while fertility egg-to-pupae recovery was reduced by 99%. In commercial raspberry crops, season-long releases of sterile males significantly suppressed the wild D. suzukii population, compared to the grower standard control strategy; with up to 89% reduction in wild female D. suzukii and 80% decrease in numbers of larvae per harvested fruit. Additionally, relative fruit waste (i.e., percentage of harvested fruits rejected for sale) at harvest was reduced for early, mid and late harvest crops, by up to 58% compared to the grower standard control. SIT has the potential to provide an effective and sustainable strategy for managing D. suzukii in raspberries, increasing marketable yield by reducing adult populations, fruit damage and waste fruit. SIT could therefore serve as a valuable tool for integrated pest management practices in berry production systems. Full article

Early crop yield prediction is a major challenge in precision agriculture, and efficient and rapid yield prediction is highly important for sustainable fruit production. The accurate detection of major fruit characteristics, including flowering, green fruiting, and ripening stages, is crucial for early yield estimation. Currently, most crop yield estimation studies based on the YOLO model are only conducted during a single stage of maturity. Combining multi-growth period data for crop analysis is of great significance for crop growth detection and early yield estimation. In this study, a new network model, YOLOv8-RL, was proposed using citrus multigrowth period characteristics as a data source. A citrus yield estimation model was constructed and validated by combining network identification counts with manual field counts. Compared with YOLOv8, the number of parameters of the improved network is reduced by 50.7%, the number of floating-point operations is decreased by 49.4%, and the size of the model is only 3.2 MB. In the test set, the average recognition rate of citrus flowers, green fruits, and orange fruits was 95.6%, the mAP@.5 was 94.6%, the FPS value was 123.1, and the inference time was only 2.3 milliseconds. This provides a reference for the design of lightweight networks and offers the possibility of deployment on embedded devices with limited computational resources. The two estimation models constructed on the basis of the new network had coefficients of determination R² values of 0.91992 and 0.95639, respectively, with a prediction error rate of 6.96% for citrus green fruits and an average error rate of 3.71% for orange fruits. Compared with network counting, the yield estimation model had a low error rate and high accuracy, which provided a theoretical basis and technical support for the early prediction of fruit yield in complex environments. Full article

Wheat is one of the important grain crops, and spike counting is crucial for predicting spike yield. However, in complex farmland environments, the wheat body scale has huge differences, its color is highly similar to the background, and wheat ears often overlap with each other, which makes wheat ear detection work face a lot of challenges. At the same time, the increasing demand for high accuracy and fast response in wheat spike detection has led to the need for models to be lightweight function with reduced the hardware costs. Therefore, this study proposes a lightweight wheat ear detection model, CML-RTDETR, for efficient and accurate detection of wheat ears in real complex farmland environments. In the model construction, the lightweight network CSPDarknet is firstly introduced as the backbone network of CML-RTDETR to enhance the feature extraction efficiency. In addition, the FM module is cleverly introduced to modify the bottleneck layer in the C2f component, and hybrid feature extraction is realized by spatial and frequency domain splicing to enhance the feature extraction capability of wheat to be tested in complex scenes. Secondly, to improve the model’s detection capability for targets of different scales, a multi-scale feature enhancement pyramid (MFEP) is designed, consisting of GHSDConv, for efficiently obtaining low-level detail information and CSPDWOK for constructing a multi-scale semantic fusion structure. Finally, channel pruning based on Layer-Adaptive Magnitude Pruning (LAMP) scoring is performed to reduce model parameters and runtime memory. The experimental results on the GWHD2021 dataset show that the ${\mathrm{AP}}_{50}$ of CML-RTDETR reaches 90.5%, which is an improvement of 1.2% compared to the baseline RTDETR-R18 model. Meanwhile, the parameters and GFLOPs have been decreased to 11.03 M and 37.8 G, respectively, resulting in a reduction of 42% and 34%, respectively. Finally, the real-time frame rate reaches 73 fps, significantly achieving parameter simplification and speed improvement. Full article

Analyzing the soil organic carbon (SOC) stock in dryland areas of southern Shanxi, particularly under the influence of fertilization and mulching conditions, is crucial for enhancing soil fertility and crop productivity and understanding the SOC pool’s resilience to future climate change scenarios in the region. In a long-term experimental site located in Hongtong County, Shanxi Province, soil samples were collected from the 0–100 cm depth over a nine-year period. These samples were analyzed to evaluate the impact of five treatments: no fertilization and no mulching (CK), conventional farming practices (FP), nitrogen reduction and controlled fertilization (MF), nitrogen reduction and controlled fertilization with ridge-film furrow-sowing (RF), and nitrogen reduction and controlled fertilization with flat-film hole-sowing (FH). The average annual yield of wheat grain, SOC stock, water-soluble organic carbon (WSOC), particulate organic carbon (POC), light fraction organic carbon (LFOC), mineral-associated organic carbon (MOC), and heavy fraction organic carbon (HFOC) stocks were measured. The results revealed that the FH treatment not only significantly increased wheat grain yield but also significantly elevated the SOC stock by 23.71% at the 0–100 cm depth compared to CK. Furthermore, this treatment significantly enhanced the POC, LFOC, and MOC stocks by 106.43–292.98%, 36.93–158.73%, and 17.83–81.55%, respectively, within 0–80 cm. However, it also significantly decreased the WSOC stock by 34.32–42.81% within the same soil layer and the HFOC stock by 72.05–101.51% between the 20 and 100 cm depth. Notably, the SOC stock at the 0–100 cm depth was primarily influenced by the HFOC. Utilizing the DNDC (denitrification–decomposition) model, we found that future temperature increases are detrimental to SOC sequestration in dryland areas, whereas reduced rainfall is beneficial. The simulation results indicated that in a warmer climate, a 2 °C temperature increase would result in a SOC stock decrease of 0.77 to 1.01 t·ha⁻¹ compared to a 1 °C increase scenario. Conversely, under conditions of reduced precipitation, a 20% rainfall reduction would lead to a SOC stock increase of 1.53% to 3.42% compared to a 10% decrease scenario. In conclusion, the nitrogen reduction and controlled fertilization with flat-film hole-sowing (FH) treatment emerged as the most effective practice for increasing SOC sequestration in dryland areas by enhancing the HFOC stock. This treatment also fortified the SOC pool’s capacity to withstand future climate change, thereby serving as the optimal approach for concurrently enhancing production and fertility in this region. Full article

Understanding future changes in crop phenology and climate suitability is essential for sustaining winter wheat production in the Huang-Huai-Hai (3H) Plain under climate change. This study integrates bias-corrected CMIP6 climate projections, the DSSAT CERES-Wheat crop model, and Random Forest analysis to assess spatiotemporal shifts in winter wheat phenology and climate suitability. The assessment focuses on the mid- (2041–2060) and late 21st century (2081–2100) under the SSP2-4.5 and SSP5-8.5 scenarios. The results indicate that the vegetative and whole growing periods (VGP and WGP) will be extended in the mid-century but shorten by the late century. In contrast, the reproductive growing period (RGP) will be slightly reduced in the mid-century and extended under high emissions in the late century. Temperature suitability is projected to increase during the VGP and WGP but decline during the RGP. Precipitation suitability generally improves, except for a decrease during the reproductive period south of 32° N. Solar radiation suitability is expected to decline across all stages. Temperature is identified as the primary driver of phenological changes, with solar radiation and precipitation playing increasingly important roles in the mid- and late 21st century, respectively. Adaptive strategies, including the adoption of heat-tolerant varieties, longer reproductive periods, and earlier sowing, are recommended to enhance yield stability under future climate conditions. Full article

Enhanced weathering of silicate rocks in agriculture is an option for atmospheric CO₂ removal and fertility improvement. The objective of our work is to characterise some of the agricultural consequences of a basaltic powder amendment on soil-crop systems. Two doses of basalt (80 and 160 t ha⁻¹) were applied to two types of slightly acid soils (sandy or silty clayey), derived from long-term trials at Bordeaux (INRAE, France) and Rothamsted Research (England), respectively. For each soil, half of the pots were planted with ryegrass; the other half were left bare. Thus, the experiment had twelve treatments with four replications per treatment. Soil pH increased with the addition of basalt (+0.8 unit), with a 5% equivalence of that of reactive chalk. The basalt contained macro- and micronutrients. Some cations extractable in the basalt before being mixed to the soil became more extractable with increased weathering, independent of plant cover. Plant uptake generally increased for macronutrients and decreased for micronutrients, due to increased stock (macro) and reduced availability (micronutrients and P), related to pH increases. K supplied in the basalt was responsible for a significant increase in plant yield on the sandy soil, linked to an average basalt K utilisation efficiency of 33%. Our general conclusion is that rock dust applications have to be re-evaluated at each site with differing soil characteristics. Full article

Soil organic nitrogen (SON) positively influences crop productivity, greenhouse gas (GHG) emissions, and sustained nitrogen (N) supply. Herein, we observed the effect of different treatments; no fertilizers (CK), chemical fertilizers (nitrogen, phosphorus, and potassium (NPK)), organic manure, and NPK + OM (NPKOM). This study was performed in a randomized complete block design (RCBD) with three replications. The results indicated that NPKOM treatment significantly decreased the nitrous oxide (N₂O) emissions by 19.97% and 17.47% compared to NPK in both years. This was linked with improved soil nutrient availability, soil organic carbon, soil organic nitrogen (SON) storage (10.06% and 12.38%), SON sequestration (150% and 140%), increased soil particulate (44.11% and 44%), and mineral-associated organic N (26.98% and 26.47%) availability. Furthermore, NPKOM also enhanced nitrate reductase (NR: 130% and 112%), glutamine synthetase (GS: 93% and 88%), sucrose phosphate synthase (SPS: 79% and 98%), SSs (synthetic direction; 57% and 50%), and decreased SSs activity in the decomposition direction (18% and 21%). This, in turn, inhibited the decomposition of sucrase and enhanced starch conversion into carbohydrates, thus leading to an increase in rice yield and a decrease in N₂O emissions. All fertilizations, particularly NPKOM, significantly enhanced grain protein contents by increasing N uptake and its availability. Therefore, NPKOM is an effective practice to enhance rice productivity, and SON sequestration and mitigate the N₂O emissions and subsequent climate change. Full article

A circular tri-trophic system integrating aquaponics, i.e., combined cultivation of crops and fish, with insect rearing is presented for lettuce cultivation. The nutrition cycle among crops, insects and fish turns waste into resource, thereby increasing the sustainability of this food production system. A comprehensive evaluation of the system’s efficiency was performed, including the growth, functional and resource use efficiency traits of lettuce, the dynamics of which were followed in a pilot-scale aquaponics greenhouse, under three treatments: conventional hydroponics (HP) as the control, coupled aquaponics (CAP) with crops irrigated with fish-derived water, and decoupled aquaponics (DCAP), where fish-derived water was amended with fertilizers to reach the HP target. The main findings indicate comparable physiological performance between DCAP and HP, despite the slightly lower yield observed in the former. The CAP treatment exhibited a significant decrease in biomass accumulation and functional impairments, which were attributed to reduced nutrient levels in lettuce leaves. The DCAP treatment exhibited a 180% increase in fertilizer use efficiency compared to the HP treatment. We conclude that the tri-trophic cropping system with the implementation of DCAP variant is an effective system that enables the combined production of crops and fish, the latter being fed with sustainably derived insect protein. The tri-trophic system improves the environmental impact and sustainability of lettuce production, while making circularity feasible. Full article

The rice-wheat rotation is the main agricultural cropping system in Jiangsu Province, playing a vital role in ensuring food security and promoting economic development. However, current research on rice-wheat systems mainly focuses on in-situ controlled experiments at the point scale, with limited studies addressing carbon footprint (CF) and energy balance (EB) at the regional scale and long time series. Therefore, we analyzed the evolution patterns of the CF and EB of the rice-wheat system in Jiangsu Province from 1980 to 2022, as well as their influencing factors. The results showed that the sown area and total yield of rice and wheat exhibited an increasing–decreasing–increasing trend during 1980–2022, while the yield per unit area increased continuously. The CF of rice and wheat increased by 4172.27 kg CO₂ eq ha⁻¹ and 2729.18 kg CO₂ eq ha⁻¹, respectively, with the greenhouse gas emissions intensity (GHGI) showing a fluctuating upward trend. Furthermore, CH₄ emission, nitrogen (N) fertilizer, and irrigation were the main factors affecting the CF of rice, with proportions of 36%, 20.26%, and 17.34%, respectively. For wheat, N fertilizer, agricultural diesel, compound fertilizer, and total N₂O emission were the primary contributors, accounting for 42.39%, 22.54%, 13.65%, and 13.14%, respectively. Among energy balances, the net energy (NE) of rice exhibited an increasing and then fluctuating trend, while that of wheat remained relatively stable. The energy utilization efficiency (EUE), energy productivity (EPD), and energy profitability (EPF) of rice showed an increasing and then decreasing trend, while wheat decreased by 46.31%, 46.31%, and 60.62% during 43 years, respectively. Additionally, N fertilizer, agricultural diesel, and compound fertilizer accounted for 43.91–45.37%, 21.63–25.81%, and 12.46–20.37% of energy input for rice and wheat, respectively. Moreover, emission factors and energy coefficients may vary over time, which is an important consideration in the analysis of long-term time series. This study analyzes the ecological and environmental effects of the rice-wheat system in Jiangsu Province, which helps to promote the development of agriculture in a green, low-carbon, and high-efficiency direction. It also offers a theoretical basis for constructing a low-carbon sustainable agricultural production system. Full article

This study investigates farmers’ knowledge, perceptions, and adaptation strategies to climate change in Rwanda’s Eastern Province, integrating social and physical science approaches. Analyzing meteorological data (1981–2021) and surveys from 204 farmers across five districts, we assessed climate trends and adaptation behaviors using statistical methods (descriptive statistics, Chi-square, logistic regression, Regional Kendall test, dynamic linear state-space model). Results show that 85% of farmers acknowledge climate change, with 54% observing temperature increases and 37% noting rainfall declines. Climate data confirm significant rises in annual minimum (+0.76 °C/decade) and mean temperatures (+0.48 °C/decade), with the largest seasonal increase (+0.86 °C/decade) in June–August. Rainfall trends indicate a non-significant decrease in March–May and a slight increase in September–December. Farmers report crop failures, yield reductions, and food shortages as major climate impacts. Common adaptations include agroforestry, crop diversification, and fertilizer use, though financial limitations, information gaps, and input scarcity impede adoption. Despite limited formal education (53.9% primary, 22.3% no formal education), indigenous knowledge aids seasonal prediction. Farm location, group membership, and farming goal are key adaptation enablers. These findings emphasize the need for targeted policies and climate communication to enhance rural resilience by strengthening smallholder farmer support systems for effective climate adaptation. Full article

In agricultural practice, in addition to determining the nitrogen (N_f) dose, it is necessary to effectively control its effect on currently grown crops. Meeting these conditions requires not only the use of phosphorus (P) and potassium (K), but also nutrients such as magnesium (Mg) and sulfur (S). This hypothesis was verified in a single-factor field experiment with winter wheat (WW) carried out in the 2015/2016, 2016/2017, and 2017/2018 growing seasons. The experiment consisted of seven variants: absolute control (AC), NP, NPK-MOP (K as Muriate of Potash), NPK-MOP+Ki (Kieserite), NPK-KK (K as Korn–Kali), NPK-KK+Ki, and NPK-KK+Ki+ES (Epsom Salt). The use of K as MOP increased grain yield (GY) by 6.3% compared to NP. In the NPK-KK variant, GY was 13% (+0.84 t ha⁻¹) higher compared to NP. Moreover, GYs in this fertilization variant (FV) were stable over the years (coefficient of variation, CV = 9.4%). In NPK-KK+Ki+ES, the yield increase was the highest and mounted to 17.2% compared to NP, but the variability over the years was also the highest (CV ≈ 20%). The amount of N in grain N (GN) increased progressively from 4% for NPK-MOP to 15% for NPK-KK and 25% for NPK-KK+Ki+ES in comparison to NP. The nitrogen harvest index was highly stable, achieving 72.6 ± 3.1%. All analyzed NUE indices showed a significant response to FVs. The PFP-N_f (partial factor productivity of N_f) indices increased on NPK-MOP by 5.8%, NPK-KK by 12.9%, and NPK-KK+Ki+ES by 17.9% compared to NP. The corresponding N_f recovery of N_f in wheat grain was 47.2%, 55.9%, and 64.4%, but its total recovery by wheat (grain + straw) was 67%, 74.5%, and 87.2%, respectively. In terms of the theoretical and practical value of the tested indexes, two indices, namely, NUP (nitrogen unit productivity) and NUA (nitrogen unit accumulation), proved to be the most useful. From the farmer’s production strategy, FV with K applied in the form of Korn–Kali proved to be the most stable option due to high and stable yield, regardless of weather conditions. The increase in the number of nutritional factors optimizing the action of nitrogen in winter wheat caused the phenomenon known as the “scissors effect”. This phenomenon manifested itself in a progressive increase in nitrogen unit productivity (NUP) combined with a regressive trend in unit nitrogen accumulation (NUA) in the grain versus the balance of soil available Mg (Mg_b). The studies clearly showed that obtaining grain that met the milling requirements was recorded only for NUA above 22 kg N t⁻¹ grain. This was possible only with the most intensive Mg treatment (NPK-KK+Ki and NPK-KK+Ki+ES). The study clearly showed that three of the six FVs fully met the three basic conditions for sustainable crop production: (i) stabilization and even an increase in grain yield; (ii) a decrease in the mass of inorganic N in the soil at harvest, potentially susceptible to leaching; and (iii) stabilization of the soil fertility of P, K, and Mg. Full article

The practice in agriculture of spreading polyethylene (PE) film over the soil surface as mulch is a common, global practice that aids in conserving water, increasing crop yields, suppressing weed growth, and decreasing growing time. However, these films are typically only used for a single growing season, and thus, their use and non-biodegradability come with some serious environmental consequences due to their persistence in the soil and potential for microplastic pollution, particularly when retrieval and disposal options are poor. On the microscale, particles < 5 mm from degraded films have been observed to disrupt soil structure, impede water and nutrient cycling, and affect soil organisms and plant health. On the macroscale, there are obvious and serious environmental consequences associated with the burning of plastic film and its leakage from poorly managed landfills. To maintain the crop productivity afforded by mulching with PE film while avoiding the environmental downsides, the development and use of biodegradable polymer technologies is being explored. Here, the efficacy of a newly developed, water-dispersible, sprayable, and biodegradable polyester–urethane–urea (PEUU)-based polymer was compared with two commercial PE mulches, non-degradable polyethylene (NPE) and OPE (ox-degradable polyethylene), in a greenhouse tomato growth trial. Water savings and the effects on plant growth and soil characteristics were studied. It was found that PEUU provided similar water savings to the commercial PE-based mulches, up to 30–35%, while showing no deleterious effects on plant growth. The results should be taken as preliminary indications that the sprayable, biodegradable PEUU shows promise as a replacement for PE mulch, with further studies under outside field conditions warranted to assess its cost effectiveness in improving crop yields and, importantly, its longer-term impacts on soil and terrestrial fauna. Full article

The detection of plant constituents is a crucial issue in precision agriculture, as monitoring these enables the automatic analysis of factors such as growth rate, health status, and crop yield. Tomatoes (Solanum sp.) are an economically and nutritionally important crop in Mexico and worldwide, which is why automatic monitoring of these plants is of great interest. Detecting leaves on images of outdoor tomato plants is challenging due to the significant variability in the visual appearance of leaves. Factors like overlapping leaves, variations in lighting, and environmental conditions further complicate the task of detection. This paper proposes modifications to the Yolov11n architecture to improve the detection of tomato leaves in images of complex outdoor environments by incorporating attention modules, transformers, and WIoUv3 loss for bounding box regression. The results show that our proposal led to a 26.75% decrease in the number of parameters and a 7.94% decrease in the number of FLOPs compared with the original version of Yolov11n. Our proposed model outperformed Yolov11n and Yolov12n architectures in recall, F1-measure, and mAP@50 metrics. Full article