Development Of Sustainable Agricultural Practices Research Articles

Nonlinear associations and threshold effects between agricultural industrial development and carbon emissions: insights from China

Abstract With the inevitability of global climate change, it has become increasingly important to understand the relationship between Agro-industrial Development (AID) and Agricultural Carbon Emissions (ACE) to promote the development of low carbon production in agriculture. Using a panel of datasets, as based on the ‘element-structure-function’ framework of 30 Chinese provinces over the period from 2011–2021, the entropy weight method was used to calculate the level of AID in each province. With this approach, it was possible to assess correlations and mechanisms between AID and ACE. Here, with use of fixed-effect, regulatory and threshold models, we determined some of the critical factors contributing to the effects of AID and ACE. Our findings revealed: (1) AID displays an inverse U-shape relationship with ACE, as verified through endogeneity and robustness assessment, (2) A review of the mechanisms suggests that the crossing of the turning point of the inverted u-curve can be accelerated by the moderating effect of agricultural finance. and (3) As based on the threshold effect analysis, a two-tier effect of the digital economy, rural human capital and farmers’ net income on AID, with facilitating effects on carbon emission reductions was obtained after the threshold crossing. The significance of this effect increases as a function of the post-threshold interval. Taken together, these findings demonstrate the long-standing interplay between AID and ACE. Thus, additional insights and empirical evidence that can inform the ongoing development of sustainable agricultural practices can be realized.

Editorial for the virtual special issue (VSI) “metal and metalloid contamination in soil and vegetables”

BackgroundIndustrial growth and population expansion have led to increasing contamination of soils and plants by metals and metalloids. Toxic elements such as lead, cadmium, and arsenic persist in the environment, presenting significant risks to both ecosystems and human health. This editorial introduces the Virtual Special Issue, which compiles recent studies on the infiltration of these contaminants into soils and their bioaccumulation in plants. ObjectivesThis special issue aims to explore the interaction between human activities and metal/metalloid contamination, highlight key bioaccumulation mechanisms, transfer dynamics, and assess the risks posed to human health by contaminated soils and plants. MethodsThe contributions to this issue include a variety of methodologies, both in laboratory and field settings, such as soil contamination assessments, bioaccumulation studies in plant species, and risk estimations for human exposure. ResultsThe compiled studies demonstrate significant contamination levels in soils and plants, especially in regions of Africa and Asia, where cadmium, mercury, zinc, and arsenic frequently exceed safety guidelines. These findings emphasize the urgent need for stricter contamination controls and further investigation in underrepresented regions. ConclusionThis issue provides crucial insights into metal and metalloid contamination in agricultural systems, offering evidence that can inform environmental policies and support the development of sustainable agricultural practices to mitigate contamination risks.

Drought Priming Promotes Nitrogen Use Efficiency in Wheat (Triticum aestivum L.) Under Drought Stress During Grain Filling

ABSTRACTDrought stress significantly challenges wheat production globally, and drought priming has emerged as an effective strategy to mitigate yield loss under drought stress events. However, the effect of drought priming on plant nitrogen use efficiency (NUE) remains insufficiently understood. This study investigates the effects of drought priming at the six‐leaf stage on NUE under drought stress during grain filling in four wheat varieties with distinct responses to drought priming. Our results indicate that there is no correlation between inherent drought tolerance and the effects of drought priming among the wheat varieties studied. In priming‐sensitive varieties, drought‐primed plants exhibited significant improvements in grain yield and NUE under drought stress compared to non‐primed plants. Conversely, priming‐insensitive varieties showed no significant differences in yield or NUE between primed and non‐primed plants under similar conditions. Notably, under drought stress, primed plants exhibited higher yield and NUE than non‐primed plants in drought priming positive variety, while the opposite trend was observed in drought priming negative response variety. The enhancement of NUE through drought priming was associated with improved nitrogen uptake efficiency and its allocation to spikes, with abscisic acid accumulation playing a pivotal role. These findings provide valuable insights into the mechanisms by which drought priming enhances NUE under drought stress, contributing to the development of sustainable agricultural practices amid climate change.

Pengelolaan limbah rumah kemas sayur melalui produksi pupuk organik cair

Background: The growth of the agricultural sector in Cipanas District, Cianjur Regency, West Java has increased the production of organic waste from vegetable packaging houses. This study aims to explore the method of converting vegetable waste into Liquid Organic Fertilizer (POC) for waste management and sustainable agriculture. Methods: This descriptive study evaluated the process of converting vegetable waste into POC in Cipanas District. The process includes soaking rice grits, mixing ingredients (rice soaking water, brown sugar solution, coconut water, vegetable waste), anaerobic fermentation for three weeks with periodic stirring, and harvesting. Findings: The study resulted in a description of the process of making POC from vegetable waste. POC has the potential to improve soil fertility holistically (physically, chemically, biologically) and has been proven effective in increasing the productivity of various types of vegetables. Conclusion: Utilization of vegetable waste as POC offers a sustainable solution for waste management and environmentally friendly agriculture. Although there are challenges in quality standardization and infrastructure, its economic potential and long-term benefits make this approach worthy of consideration in future agricultural strategies. Novelty: This study highlights the potential use of vegetable waste from packaging houses in Cipanas for POC production, integrating the concept of circular economy in agricultural waste management and the development of sustainable agricultural practices.

Interplay between denitrifying and sulfate-reducing bacterial communities under acid mine drainage stress

Acid mine drainage (AMD) pollution leads to the enrichment of sulfate in paddy soil. The interplay between denitrifying and sulfate-reducing bacteria across varying soil depths, and their response to AMD pollution is not yet fully understood. The responses of denitrifying and sulfate-reducing bacteria(SRB) to AMD pollution were analyzed by collecting soil samples at four depths (0–10 cm, 10–20 cm, 20–40 cm, 40–60 cm) under two treatments (AMD-polluted and control soil). AMD pollution resulted in a significant decrease in pH value, elevated SO42- and metal concentrations. Compared to the control soil, denitrifying and sulfate-reducing bacteria in AMD-polluted soils were more sensitive to environmental fluctuations. Co-occurrence analysis revealed that there were more microbiological linkages and nodes in control soil than in polluted soil. Denitrifying and sulfate-reducing bacteria can maintain part of N and S cycle under long-term AMD pollution by increasing the negative correlation in ecological network. Desulfobacca exhibited a positive correlation with nitrate and held a significant position in the symbiotic network, suggesting its potential important role in inhibiting nitrogen loss. This study revealed the intricate ecological network of functional communities, which could have important implications for environmental management and the development of sustainable agricultural practices in areas affected by AMD pollution.

Bacillus, Pseudomonas and Serratia control Meloidogyne incognita (Rhabditida: Meloidogynidae) and promote the growth of tomato plants

Plant-parasitic nematodes cause significant losses in agriculture worldwide. Among these parasites, the root-knot nematode (Meloidogyne spp.) stands out. Consequently, control methods are being developed to combat this pest. Among these methods is biological control, the main agents of which are bacteria. This study aimed to evaluate the impact of 102 bacterial isolates on the mortality of Meloidogyne incognita J2 juveniles, hypothesizing that certain isolates could effectively control the nematode and promote tomato plant growth. Five experiments were conducted to test this hypothesis. First, the effect of the 102 bacterial isolates on J2 mortality was assessed under laboratory conditions. Second, five isolates (Bacillus cereus IBCBb130, Bacillus cereus IBCBb116, Pseudomonas aeruginosa IBCBb122, Bacillus proteolyticus IBCBb136, and Serratia sp. IBCBb118), which showed >68% J2 mortality, were evaluated over 72 h. Third, these isolates were tested at seven different concentrations. Fourth, their efficacy in controlling M. incognita on tomato plants was assessed in a greenhouse setting. Fifth, their potential to promote tomato plant growth without nematode inoculation was evaluated. The results revealed that the 102 bacterial isolates caused mortality ranging from 2 to 79.57% for M. incognita J2. At a 10% dilution, five isolates (B. cereus IBCBb130, P. aeruginosa IBCBb122, B. cereus IBCBb116, B. proteolyticus IBCBb136, and Serratia sp. IBCBb118) maintained mortality rates above 68%. Among these strains, B. cereus IBCBb130 and P. aeruginosa IBCBb122 were particularly effective, with B. cereus IBCBb130 showing high mortality rates under laboratory conditions and P. aeruginosa IBCBb122 significantly reducing nematode populations in greenhouse pots. Additionally, Serratia sp. IBCBb118 demonstrated notable potential for promoting tomato plant growth. In conclusion, specific bacterial isolates exhibit strong potential for the biocontrol of M. incognita and enhancement of tomato plant growth, suggesting a viable alternative to chemical nematicides. These findings provide insight into the development of sustainable agricultural practices through targeted manipulation of the soil microbiota. Future research should explore the underlying mechanisms of these interactions and their long-term effects on crop yield and soil health.

Potassium silica nanostructure improved growth and nutrient uptake of sorghum plants subjected to drought stress.

Recent advancements in nanotechnology present promising opportunities for enhancing crop resilience in adverse environmental conditions. In this study, we conducted a factorial experiment to investigate the influence of potassium nanosilicate (PNS) on sorghum plants exposed to varying degrees of drought stress A randomized complete block design with three replications was employed to subject the sorghum plants to different drought conditions. The three levels of stress were designated as non-stress (NS at -0.03 MPa), moderate stress (MD at -0.6 MPa), and severe stress (SD at -1.2 MPa). The plants were administered PNS at concentrations of 0 mM (control), 3.6 mM Si, and 7.2 mM Si. As drought stress intensified, we observed significant reductions in multiple plant parameters, including height, fresh weight, dry weight, leaf number, stem diameter, cluster length, seed weight, and nutrient uptake, with the most pronounced effects observed under SD conditions. Interestingly, nitrogen (N) and potassium (K) levels exhibited an increase under drought stress and PNS application, peaking at MD, alongside Si concentrations. Notably, PNS application facilitated enhanced nutrient uptake, particularly evident in the significant increase in nitrogen concentration observed at 3.6 mM PNS. Furthermore, the application of PNS significantly enhanced the fresh weight and nutrient concentrations (notably K and Si) in sorghum seeds under drought stress, despite varying statistical significance for other nutrients. These findings shed light on the mechanisms through which PNS exerts beneficial effects on plant performance under drought stress. By elucidating the complex interactions between PNS application, drought stress, and plant physiology, this study contributes significantly to the development of sustainable agricultural practices aimed at bolstering crop resilience and productivity in water-limited environments.

The LTAR Cropland Common Experiment at the Texas Gulf.

Texas Gulf is one of the 18 regional sites that is part of the USDA-ARS Long-Term Agroecosystem Research (LTAR) Network and focuses on cropland and integrated grazing land research in Central Texas, addressing challenges posed by soil characteristics, climate variability, and urbanization. This paper provides brief site descriptions of the two Cropland Common Experiments being conducted in the Texas Gulf LTAR region, emphasizing conservation tillage practices and precision agriculture techniques. The plot-scale study is located in Temple, TX, at the USDA-ARS Grassland, Soil and Water Research Laboratory and examines conventional tillage, strip tillage, and no tillage practices. The field-scale study, located in Riesel, TX, at the USDA-ARS Riesel Watersheds, assesses the impact of no tillage, cover crops, fertility management, adaptive management, and precision conservation on crop yield, profitability, and environmental footprint. Key measurements include soil and plant analyses, greenhouse gas fluxes, runoff water quantity and quality, and field operations recorded with precision agriculture equipment. Despite challenges posed by urban encroachment, future research aims to incorporate new technologies, such as unmanned ground vehicles, to enhance sustainability and productivity of the agricultural landscape. These experiments provide valuable insights for stakeholders, contributing to the development of sustainable agricultural practices tailored to the unique challenges within the Texas Gulf LTAR region.

Investigating the effect of climate factors on fig production efficiency with machine learning approach.

This study employs a machine learning approach to investigate the impact of climate change on fig production in Turkey. The eXtreme Gradient Boosting (XGBoost) algorithm is used to analyze production performance and climate variable data from 1988 to 2023. Fig production is a significant component of Turkey's agricultural economy. Therefore, understanding how climate change affects fig production is essential for the development of sustainable agricultural practices. Despite an observed increase in fig production between 2005 and 2020, potential yield may be negatively impacted by climate variables. Identifying the specific climatic factors affecting fig production efficiency remains a challenge. In the study, two different machine learning models are created: one for fig production yield per decare and another for fig production yield per bearing fig sapling. Eight climate variables (16 variables considering day and night values) serve as independent variables in the models. The models reveal that temperature change has the highest impact, with a percentage contribution of 41.30% in the first model and 43.90% in the second model. Thermal radiation (day and night) and 2 m temperature also significantly affect individually fig production. Wind speed, precipitation and humidity contribute to a lesser extent. This study illuminates the intricate interrelationship between climate change and fig production in Turkey. The utilization of machine learning as a predictive tool for future production trends and an instrument for informing agricultural practices is a valuable contribution to the field. © 2024 The Author(s). Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Bacillus subtilis promotes plant phosphorus (P) acquisition through P solubilization and stimulation of root and root hair growth.

Bacteria can be applied as biofertilizers to improve crop growth in phosphorus (P)-limited conditions. However, their mode of action in a soil environment is still elusive. We used the strain ALC_02 as a case study to elucidate how Bacillus subtilis affects dwarf tomato cultivated in soil-filled rhizoboxes over time. ALC_02 improved plant P acquisition by increasing the size and P content of P-limited plants. We assessed three possible mechanisms, namely root growth stimulation, root hair elongation, and solubilization of soil P. ALC_02 produced auxin, and inoculation with ALC_02 promoted root growth. ALC_02 promoted root hair elongation as the earliest observed response and colonized root hairs specifically. Root and root hair growth stimulation was associated with a subsequent increase in plant P content, indicating that a better soil exploration by the root system improved plant P acquisition. Furthermore, ALC_02 affected the plant-available P content in sterilized soil differently over time and released P from native P pools in the soil. Collectively, ALC_02 exhibited all three mechanisms in a soil environment. To our knowledge, bacterial P biofertilizers have not been reported to colonize and elongate root hairs in the soil so far, and we propose that these traits contribute to the overall effect of ALC_02. The knowledge gained in this research can be applied in the future quest for bacterial P biofertilizers, where we recommend assessing all three parameters, not only root growth and P solubilization, but also root hair elongation. This will ultimately support the development of sustainable agricultural practices.

Adding Machine-Learning Functionality to Real Equipment for Water Preservation: An Evaluation Case Study in Higher Education

Considering that the fusion of education and technology has delivered encouraging outcomes, things are becoming more challenging for higher education as students seek experiences that bridge the gap between theory and their future professional roles. Giving priority to the above issue, this study presents methods and results from activities assisting engineering students to utilize recent machine-learning techniques for tackling the challenge of water resource preservation. Cost-effective, innovative hardware and software components were incorporated for monitoring the proper operation of the corresponding agricultural equipment (such as electric pumps or water taps), and suitable educational activities were developed involving students of agricultural engineering. According to the evaluation part of the study being presented, the implementation of a machine-learning system with sufficient performance is feasible, while the outcomes derived from its educational application are significant, as they acquaint engineering students with emerging technologies entering the scene and improve their capacity for innovation and cooperation. The study demonstrates how emerging technologies, such as IoT, ML, and the newest edge-AI techniques can be utilized in the agricultural industry for the development of sustainable agricultural practices. This aims to preserve natural resources such as water, increase productivity, and create new jobs for technologically efficient personnel.

Ayçiçeğinde Sclerotinia sclerotiorum (Lib.) De Bary’ye Karşı Bazı Bakteriyel Antagonistlerin In vitro ve In vivo Etkinliklerinin Belirlenmesi

This study was carried out in 2017-2018 to determine the in vitro and in vivo activities of some bacterial bioagents against Sclerotinia sclerotiorum, which causes root and root-collar rot in sunflower cultivation areas of Konya and Aksaray provinces. Against the two most virulent S. sclerotiorum (Hırkatol and Eskil) isolates selected as a result of pathogenicity tests after being isolated and diagnosed from diseased plants which were collected from sunflower cultivation areas in Konya and Aksaray provinces, the antifungal effects of 16 bacterial isolates from the soil in the rhizosphere region of the healthy sunflower plants from the same areas were evaluated. Primarily, the most effective bacterial bioagents were determined by dual culture tests. As a result of the in vitro tests, a total of 5 bacterial isolates constituting the largest zone diameter were molecularly identified according to 16S rRNA and were used in pot experiments. The bacteria were identified as Bacillus cereus, Bacillus simplex, Brevibacterium frigoritolerans, Bacillus toyonensis (2 isolates) and were coded using the BLAST program of the GenBank database (NCBI). As per in vitro, the highest effect in both isolates of S. sclerotiorum was observed in Bacillus cereus and Bacillus simplex with an inhibition rate of 49.19-57.95%. Except for Bacillus toyonensis (B1), one of the bacterial species which were tested in vivo, all the bacteria reduced or stopped lesion development compared to the control. As a result of the application, the biological control agent completely prevented the growth of both the isolates of Bacillus cereus and Bacillus simplex S. sclerotiorum in in vivo conditions (100%). Efficacy studies have shown that bacterial isolates both cause healthy growth of sunflower plants and significantly prevent disease formation in treated plants when compared to control plants. These results emphasize the importance of such studies as a tool for the development of sustainable agricultural practices that can be easily applied in our region, and also show that B. cereus and B. simplex in sunflowers can be potential bacterial bioagents that can be used in biological control against S.sclerotiorum. In addition, it will be useful to carry out studies on the development of commercial preparations of the bacterial isolates found in the study.

Modeling soil carbon accumulation in irrigated agricultural systems

In contemporary circumstances characterized by climate change and increased pressure on agricultural ecosystems, determining the impact of irrigation levels on soil carbon dynamics becomes a pertinent task. This study aims to determine the impact of irrigation rates on soil carbon dynamics using agricultural system modeling. The simulations were conducted by LPJ-GUESS Education 3.0. The results were analyzed using the analogy method. Changes in soil carbon accumulation were quantified in three agricultural systems representing the desert, semi-desert, and steppe zones of Russia. Results show an increase in soil carbon accumulation in all biomes and a decrease in ecosystem carbon exchange. These findings suggest that irrigation rates developed for desert, semi-desert, and steppe biomes were effective. The results of this study can be applied to irrigated and rainfed agriculture. The obtained data not only corroborate the positive influence of irrigation levels on carbon accumulation in soil across various biomes but also unveil prospects for the development of sustainable agricultural practices. This study aims at optimizing the utilization of water resources, which may contribute to fostering ecosystem resilience within the agricultural sector.

The Microbial Community Structure in the Rhizosphere of Theobroma cacao L. and Euterpe oleracea Mart. Is Influenced by Agriculture System in the Brazilian Amazon.

This study tested the hypothesis that cocoa monoculture (MS) and cocoa-açai agroforestry systems (AFS) may influence the microbial community structure and populations of plant growth-promoting bacteria (PGPR). Accordingly, the aim was to analyze the microbial community structure and PGPR populations in different agroecosystems in the Brazilian Amazon. To achieve this, the rhizosphere microbial community of cocoa and açai plants in both Amazonian seasons (dry and rainy) was analyzed using culture-dependent (PGPR screening) and -independent methods [PCR-DGGE based on rrs, alp, nifH gene, and intergenic region (ITS) of fungi]. Concerning PGPR screening, out of 48 isolated bacterial strains, 25% were capable of siderophore production, 29% of mineralized organic phosphate, 8% of inorganic phosphate solubilization, and 4% of indole acetic acid production. Moreover, 17% of isolates could inhibit the growth of various phytopathogenic fungi. Statistical analyses of DGGE fingerprints (p < 0.05) showed that bacterial and fungal community structures in the rhizosphere were influenced by the seasons, supporting the results of the physicochemical analysis of the environment. Furthermore, as hypothesized, microbial communities differed statistically when comparing the MS and AFS. These findings provide important insights into the influence of climate and cultivation systems on soil microbial communities to guide the development of sustainable agricultural practices.

Evaluation of the Humic Acid Efficiency and the Bioagent Chaetomium globosum in Controlling Fusarium Wilt Disease in Tomato

Fusarium wilt disease presents a significant menace to tomato plants, necessitating effective preventative measures. Five isolates of Fusarium oxysporum f.sp. lycopersici from infected tomato plants from different regions in Missan province, each showing varying levels of pathogenicity. Differences in the ability of tomato seedlings to be infected by these isolates were also observed during a pot experiment, ranging from highly pathogenic to non-pathogenic. To address this issue, the efficacy of the bioagent Chaetomium globosum and humic acid in controlling the pathogenic fungus F. oxysporum f.sp. lycopersici and improving the growth indicators of tomato plants in the presence of the causative fungus. Two concentrations of humic acid (8 and 4 mL/l) were tested to determine their efficacy in reducing the growth of pathogenic fungi in vitro. We found that the growth of the pathogenic fungi decreased to 41.06% at a concentration of 8 ml/l, compared to the control, which showed no growth. Moreover, when used alone or in combination with humic acid, C. globosum significantly reduced the percentage and severity of infection. The treatment involving the interaction between the bioagent and humic acid at a concentration of 8 ml/l recorded an infection percentage of 14.4% and an infection severity of 11.87%, compared to the pathogenic fungus treatment that resulted in 53% infection and 43.80% severity, respectively. Moreover, the use of C. globosum and different concentrations of humic acid raised all growth indices in all treatments whether in the presence or absence of pathogenic funus. These improvements included increased fresh and dry weight of the shoot and root, enhanced plant height and leaf area, as well as a significant increase in the content of total phenols and total chlorophyll in the leaves. The findings of this study highlight the potential of C. globosum and humic acid as effective control measures against fusarium wilt disease in tomato plants. The results indicate their ability to suppress the pathogenic fungus and promote plant growth. These findings hold promise for the development of sustainable agricultural practices.

Soil physics matters for the land–water–food–climate nexus and sustainability

AbstractSoil is a complex ecosystem within which many species interact and where physicochemical and geological processes occur at different spatiotemporal scales, with strong interactions taking place between ecological and management processes. Soil processes affect the qualities of the food and water that we eat and drink, the regulation of greenhouse gases, and are the foundation of our habitation and transportation infrastructures. However, it is estimated that over 2 billion hectares of lands are degraded, with a further 12 million hectares degraded each year causing the annual loss of 24 billion tons of fertile soil. Soil degradation negatively affects the well‐being of over 3 billion people, costing more than 10% of the annual global GDP via the loss of ecosystem services, and reducing the productivity of 23% of the global terrestrial area. The sustainable management of soil ecosystems is, therefore, fundamental to global food, water, and energy security, especially under increasingly unpredictable weather patterns caused by climate change. The land–water–food–energy nexus is central to sustainable development and soil inextricably links these critical domains. Stakeholders and decision‐makers in all four domains are necessarily focusing on the effects of soil degradation on climate change, water resource management, and food production as key to the development of sustainable agricultural practices and policies. A properly integrated approach to managing rural soils is thus required to ensure global water, food, and energy security, whilst increasing and protecting biodiversity. This special issue collects 15 papers on recent advances on soil physical‐, hydrological‐, and biological processes, and linkages with agroecosystem sustainability across experiments, field observations, and methodological breakthroughs.

Digital mapping and spatial modeling of some soil physical and mechanical properties in a semi-arid region of Iran.

The soil's physical and mechanical (SPM) properties have significant impacts on soil processes, such as water flow, nutrient movement, aeration, microbial activity, erosion, and root growth. To digitally map some SPM properties at four global standard depths, three machine learning algorithms (MLA), namely, random forest, Cubist, and k-nearest neighbor, were employed. A total of 200-point observation was designed with the aim of a field survey across the Marvdasht Plain in Fars Province, Iran. After sampling from topsoil (0 to 30 cm) and subsoil depths (30 to 60 cm), the samples were transferred to the laboratory to determine the mean weight diameter (MWD) and geometric mean diameter (GMD) of aggregates in the laboratory. In addition, shear strength (SS) and penetration resistance (PR) were measured directly during the field survey. In parallel, 79 environmental factors were prepared from topographic and remote sensing data. Four soil variables were also included in the modeling process, as they were co-located with SPM properties based on expert opinion. For selecting the most influential covariates, the variance inflation factor (VIF) and Boruta methods were employed. Two covariate dataset scenarios were used to assess the impact of soil and environmental factors on the modeling of SPM properties including SPM and environmental covariates (scenario 1) and SPM, environmental covariates, and soil variables (scenario 2). From all covariates, nine soil and environmental factors were selected for modeling the SPM properties, of which four of them were the soil variables, three were related to remote sensing, and two factors had topographic sources. The results indicated that scenario 2 outperformed in all standard depths. The findings suggested that clay and SOM are key factors in predicting SPM, highlighting the importance of considering soil variables in addition to environmental covariates for enhancing the accuracy of machine learning prediction. The k-nearest neighbor algorithm was found to be highly effective in predicting SPM, while the random forest algorithm yielded the highest R2 value (0.92) for penetration resistance properties at 15-30 depth. Overall, the approach used in this research has the potential to be extended beyond the Marvdasht Plain of Fars Province, Iran, as well as to other regions worldwide with comparable soil-forming factors. Moreover, this study provides a valuable framework for the digital mapping of SPM properties, serving as a guide for future studies seeking to predict SPM properties. Globally, the output of this research has important significance for soil management and conservation efforts and can facilitate the development of sustainable agricultural practices.

Influence of rice-wheat and sugarcane-wheat rotations on microbial diversity and plant growth promoting bacteria: Insights from high-throughput sequencing and soil analysis

Wheat is a staple food crop, primarily grown in India's Indo-Gangetic plains, crucial for sustaining the region. Soil quality, vitality, and microbial inhabitants' interplay are pivotal. However, very little information is available on the impacts of agricultural practices, such as crop rotation and cropping systems, on the diversity of both bulk soil (BS) and rhizospheric soil (RS) microbiota. The impact of two different cropping systems, rice-wheat (RW) and sugarcane-wheat (SW) on soil properties, microbial diversity, and plant growth-promoting bacteria (PGPB) in wheat cultivation was investigated in the Indo-Gangetic plains of India. Microbial richness and diversity were analyzed using 16S rRNA sequencing, which reveals distinct clustering patterns between RS and BS, with higher diversity in BS of RW and higher richness in RS of SW. Notably, Proteobacteria dominated across all samples, along with Chloroflexi, Actinobacteria, Bacteroidetes, Acidobacteria, Gemmatimonadetes, Verrucomicrobia, Firmicutes, Planctomycetes, candidate division TM7, Cyanobacteria, and Nitrospirae. Intriguingly, the RS associated with the SW system exhibited the presence of 67 distinct genera, whereas the RS under the RW system showed 48 such genera. Within the realm of specific microbial genera exhibiting plant growth-promoting (PGP) activity, a higher abundance was noted in the RS (17.48%), as opposed to the BS (15.21%). Moreover, certain genera such as Haliangium, Iamia, Bacillus, Gaiella, Candidatus_Entotheonella, Anaerolinea, and Anaeromyxobacter, were found to be positively correlated with the availability of nitrogen, phosphorus, potassium, iron, and sulfur. The study sheds light on the intricate relationships between cropping practices, soil properties, and microbial dynamics, contributing to the development of sustainable agricultural practices for wheat cultivation.

Effect of Indole-3-Acetic Acid and Nano-Urea on Agronomic Properties of Radish Crops

This study aimed to evaluate the impact of nano-urea, indole-3-acetic acid (IAA), phosphorus (P), and potassium (K) on seed germination and various growth parameters of Raphanus sativus L. The experiment was carried out in a randomized block design with three replicates per treatment and a total of eight treatments. Both nano-urea and IAA were applied through foliar spray whereas P and K were given as in-soil treatment. The seed germination centage was measured on the 14th day after sowing. The results demonstrated that all treatments improved seed germination compared to the control. Nano-urea alone increased the germination percentage from 40.83% to 54.16%, while the combination of nano-urea and IAA further enhanced it to 67.5%. The highest germination percentage of 75.83% was achieved with the simultaneous application of nano-urea, IAA, P and K. Additionally, the treatments influenced the number of leaves at different stages of growth. The treatment with IAA, nano-urea, P and K resulted in the highest leaf count of 61.26. Moreover, the length of leaves, roots, and shoots were significantly affected by the treatments. The combination of foliar applications of IAA (auxin) and nano-urea; and in soil treatments of P and K resulted in the longest leaf, root, and shoot lengths. These findings highlight the positive effects of the tested treatments on seed germination and various growth parameters of Raphanus sativus L. The results contribute to our understanding of the potential applications of nano-urea, IAA, P and K in improving crop productivity and growth. This information can aid in the development of sustainable agricultural practices for enhanced crop performance and yield.

Flooding drives the temporal turnover of antibiotic resistance gene in manure-amended soil–water continuum

Rice paddy soil is a hotspot of antibiotic resistance genes (ARGs) due to the application of organic fertilizers. However, the temporal dynamics of ARGs in rice paddy soil and its flooded water during the growing season remain underexplored. In this study, a microcosm experiment was conducted to explore the ARG profiles in a long term (130 days) flooded two-phase manure-amended soil–water system. By using high-throughput quantitative PCR array, a total of 23–98 and 34–85 ARGs were detected in the soil and overlying water, respectively. Regression analysis exhibited significant negative correlations between ARG profile similarities and flooding duration, indicating that flooding significantly altered the resistome (P < 0.001). This finding was validated by the increased ARG abundance in the soil and the overlying water, for example, after 130 days flooding, the abundance of ARGs in CK soil was increased from 0.03 to 1.20 copies per 16S rRNA. The PCoA analysis further suggested pig manure application resulted in distinct ARG profiles in the soil–water continuum compared with those of the non-amended control (Adonis, P < 0.05). The Venn diagram showed that all ARGs detected in the pig manure were present in the treated soil. Twelve ARGs (e.g., sul1) were shared among the pig manure, manure-amended soil, and overlying water, indicating that certain manure- or soil-borne ARGs were readily dispersed from the soil to the overlying water. Moreover, the enhanced relationships between the ARGs and mobile genetic elements in pig manure applied soil–water continuum indicate that the application of organic matter could accelerate the emergence and dissemination of ARGs. These findings suggested that flooding represents a crucial pathway for dispersal of ARGs from the soil to the overlying water. Identification of highly mobile ARGs in the soil–water continuum is essential for assessing their potential risk to human health and promoting the development of sustainable agricultural practices to mitigate their spread.