Agricultural Management Research Articles

Role of methanotrophic communities in atmospheric methane oxidation in paddy soils

Wetland systems are known methane (CH4) sources. However, flooded rice fields are periodically drained. The paddy soils can absorb atmospheric CH4 during the dry seasons due to high-affinity methane-oxidizing bacteria (methanotroph). Atmospheric CH4 uptake can be induced during the low-affinity oxidation of high-concentration CH4 in paddy soils. Multiple interacting factors control atmospheric CH4 uptake in soil ecosystems. Broader biogeographical data are required to refine our understanding of the biotic and abiotic factors related to atmospheric CH4 uptake in paddy soils. Thus, here, we aimed to assess the high-affinity CH4 oxidation activity and explored the community composition of active atmospheric methanotrophs in nine geographically distinct Chinese paddy soils. Our findings demonstrated that high-affinity oxidation of 1.86 parts per million by volume (ppmv) CH4 was quickly induced after 10,000 ppmv high-concentration CH4 consumption by conventional methanotrophs. The ratios of 16S rRNA to rRNA genes (rDNA) for type II methanotrophs were higher than those for type I methanotrophs in all acid-neutral soils (excluding the alkaline soil) with high-affinity CH4 oxidation activity. Both the 16S rRNA:rDNA ratios of type II methanotrophs and the abundance of 13C-labeled type II methanotrophs positively correlated with high-affinity CH4 oxidation activity. Soil abiotic factors can regulate methanotrophic community composition and atmospheric CH4 uptake in paddy soils. High-affinity methane oxidation activity, as well as the abundance of type II methanotroph, negatively correlated with soil pH, while they positively correlated with soil nutrient availability (soil organic carbon, total nitrogen, and ammonium-nitrogen). Our results indicate the importance of type II methanotrophs and abiotic factors in atmospheric CH4 uptake in paddy soils. Our findings offer a broader biogeographical perspective on atmospheric CH4 uptake in paddy soils. This provides evidence that periodically drained paddy fields can serve as the dry-season CH4 sink. This study is anticipated to help in determining and devising greenhouse gas mitigation strategies through effective farm management in paddy fields.

Environmental Footprints of Yogurt Production: A Case Study of a Small-Scale Manufacturing Process in Sri Lanka

This study investigated the life cycle environmental impacts of yogurt production from cradle to gate at the Pulathisi milk factory in Polonnaruwa, Sri Lanka. The functional unit considered was one kilogram of yogurt produced in the factory using existing technology. The defined system boundary encompassed raw milk production and transportation, machinery fabrication, standardization of milk, and standard unit operations of yogurt production. Material and energy usage data were collected through a series of observations, literature and Ecoinvent 3.7.1 databases. The ReCiPe 2008 method was employed for impact analysis, considering eighteen impact categories with SimaPro software. The inventory analysis included material consumption for machinery fabrication, energy consumption, and emissions for each unit operation in yogurt production. Results were characterized using midpoint indicators, and normalized impacts were calculated. The characterized outcomes of the yogurt production process contributed 2.48 kgCO2eq to climate change, 0.0297 kgSO2eq to acidification, 0.0002 kgPeq to eutrophication, and 6.9199 kg 1,4-DBeq to human toxicity. The study identified hotspots, emphasizing the significant contributions of cow milk production and electricity usage to environmental impacts. Potential mitigations, such as improved waste management in dairy farming and switching to renewable energy sources, are proposed to address these impacts. The normalized impacts provided insights for decision-makers and stakeholders to compare environmental performances and guide sustainable practices in yogurt production. The total impact was recorded as 0.014-person equivalent per year per one kilogram of yogurt.

Theoretical Assessment of Agro-Waste for Biogas Production Based on Novel Methodology Related to Biochemical Potential

Agricultural and waste biomasses present viable solutions for utilization in the energy sector, achieving sustainable and long-term transformation into energy and fuel. However, it is important to carefully evaluate the competing applications for these feedstocks, considering both short- and long-term stability. Biomass for biogas production in agriculture and waste management is used due to its availability and ease of handling. Considering everything mentioned, evaluating the most suitable raw materials for biogas production is crucial for meeting sustainability criteria and promoting biomass as an energy source. In this paper, an examination of different biomass sources as possible feedstock to produce biogas by applying a theoretical approach to the proximate and final analysis results of those materials is presented. Based on data from the raw material analysis, the theoretical biochemical methane potential (TBMP) for the considered samples was calculated. Furthermore, the mass and energy balance for the case study biogas plant was also performed. According to the obtained results, the considered feedstocks show the validity of their use for biogas production considering the fulfillment of the raw material minimum quantity, mandatory residue arrangement, and achieving higher efficiency of the energy conversion process.

Vineyard maturity increases arbuscular mycorrhizal and decreases plant pathogen fungal relative abundance in bulk soil across a 1,000 km Chilean gradient

Societal Impact StatementWine production has a significant impact on the global economy. Despite this, the microbial composition of the terroir has not been studied sufficiently, particularly in the southern hemisphere. Here, we investigated how bulk soil fungal communities are affected by several abiotic and biotic factors across 1,000 km of Chilean vineyards. We found that geographical distance was the main driver of vineyard soil fungal communities. Irrespective of variety, older vineyards host a higher relative abundance of arbuscular mycorrhizal fungi (AMF) and a lower relative abundance of plant pathogenic fungi. This result could lead to significant recommendations on when to apply AMF‐based inoculants.Summary The microbial dimension of the terroir has been increasingly recognized as an essential factor determining vineyard productivity and quality. Despite this, few studies have analyzed the factors affecting soil fungal communities of vineyards in the southern hemisphere. Across a 1,000 km gradient encompassing 34 Chilean vineyards, we investigated the effects of grapevine variety, geographical distance, maturity, and soil chemical properties on the diversity and composition of soil fungi. We implemented standard soil chemical analyses and ITS‐based DNA metabarcoding of bulk soil. We found that the total soil fungal composition was significantly affected by geographical distance but not by grapevine variety and maturity. Soil chemical dissimilarity also significantly affected soil fungal composition. When analyzing specific fungal guilds, we found a contrasting successional pattern: arbuscular mycorrhizal fungal relative abundance was significantly higher at medium and old‐maturity vineyards compared with young vineyards, on which plant pathogenic fungi had a markedly lower abundance. Our results present several caveats: the molecular marker was not the most commonly used for arbuscular mycorrhizal fungi, bulk soil was sampled (instead of roots), and all abundances were relative. Still, this study constitutes one of the most extensive studies on soil fungi – both for vineyards and Chile – and might have practical implications, as knowing the drivers of fungal and mycorrhizal biodiversity can inform agricultural management decisions.

Impact of the Russian invasion on wheat biomass in Ukraine

Abstract Ukraine was the seventh-biggest worldwide producer of wheat in 2021 before the Russian invasion. The war caused a disruption of the global wheat market but the impact on the different levels of the production chain remains unclear. Here we leverage high resolution satellite imagery and crop modeling to analyze specifically the impact of the war on the evolution of the dry aboveground biomass in wheat fields. We compare the Kherson region, a battlefield occupied by the Russian army in 2022 with the Poltava region which was not invaded. We also compare the wheat biomass in both regions in 2022 with the two previous years before the war. We find that the wheat biomass sharply declined in the Kherson region in 2022 only. We interpret this result as a consequence of the abandonment of invaded land by farmers. The lack of agricultural management, in particular the lack of fertilization and irrigation could explain the reduced crop growth in summer, thereby contributing to shortages in the wheat production chain.

Study of Machine Learning Techniques for the Estimation of Soil Moisture in Agriculture

Soil moisture is crucial in various fields and monitoring it to guide irrigation is challenging. Machine learning has emerged as a promising tool to predict soil moisture levels accurately. This study evaluates machine learning techniques for this task, training models with meteorological variables and direct soil moisture measurements. Four machine learning algorithms were implemented, highlighting the Gradient Boosting Regressor as the most effective. In addition, a processed data set that combines meteorological and soil moisture measurements is presented, hoping it will be helpful for future research. This approach seeks to improve the compression and predictability of soil moisture, which is crucial for agricultural planning and water management in agriculture

Management of soil phosphorous using phosphate solubilizing microorganisms: A sustainable approach

Phosphorus is crucial for plant growth and productivity, and its scarcity in soil negatively affects crop yields. A major portion of chemical phosphate fertilizer precipitates with soil minerals, making it unavailable for plant growth. Phosphate-solubilizing microorganisms play a pivotal role in enhancing phosphorus availability, facilitating better nutrient absorption, and ultimately boosting plant growth. This article presents a brief overview of the phosphorus status in Indian soil, discusses the various forms of phosphorus and its dynamics across different soil types, and analyses the factors involved, highlighting the importance of phosphorus management for sustainable agriculture. Physiological and molecular mechanisms of microbial phosphate solubilization provide deep insights into exploring PSMs for managing phosphorous in different soil types. It also provides a path for the necessity to explore the multifarious plant growth-promoting traits of PSMs underscoring its applicability for sustainable agricultural practices with viable economy. The mechanism of solubilization of phosphorus has been discussed to understand the role of microorganisms in different soils. The study highlights the role of significant microorganisms in developing tailored consortia of PSMs and other plant growth-promoting rhizobacteria (PGPR) based on the chemical composition of the soil, along with an integrated nutrient approach incorporating PSMs. This review offers valuable insights into harnessing PSMs and their practical applications, facilitating their broader adoption in agricultural systems to maintain soil health.

Author Correction: Uniting remote sensing, crop modelling and economics for agricultural risk management

Author Correction: Uniting remote sensing, crop modelling and economics for agricultural risk management

Unleashing the Dynamic Strategies in the Era of Change – A Spotlight on the ISPRS Student Consortium's Global Contributions

Abstract. ISPRS Student Consortium (ISPRS SC) has played a significant role in bringing students and young researchers closer to the field of remote sensing and photogrammetry in the evolving landscape of geospatial sciences. Innovative strategies and events have been employed by the ISPRS SC to address contemporary challenges and harness emerging opportunities in the field of photogrammetry and remote sensing. Through an analysis of the global contributions of ISPRS SC, ranging from research initiatives to the online webinar series, this paper underscores the consortium's commitment to fostering collaboration, innovation, and knowledge exchange among young scholars and professionals worldwide. The paper highlights key thematic areas addressed by ISPRS SC such as advancements in remote sensing technologies, geospatial data analysis, and applications in diverse domains including environmental monitoring, agriculture, urban planning, and disaster management. Moreover, in this paper, we emphasize the role of the consortium in nurturing future leaders in geospatial sciences through ISPRS SC mentorship programs, networking opportunities, and capacity-building initiatives. By highlighting the initiatives led by the ISPRS Student Consortium, this paper underscores the key role of youth-driven innovation for positive change and shaping the future of geospatial sciences on a global scale.

Diagnosis of Custard Apple Disease Based on Adaptive Information Entropy Data Augmentation and Multiscale Region Aggregation Interactive Visual Transformers

Accurate diagnosis of plant diseases is crucial for crop health. This study introduces the EDA–ViT model, a Vision Transformer (ViT)-based approach that integrates adaptive entropy-based data augmentation for diagnosing custard apple (Annona squamosa) diseases. Traditional models like convolutional neural network and ViT face challenges with local feature extraction and large dataset requirements. EDA–ViT overcomes these by using a multi-scale weighted feature aggregation and a feature interaction module, enhancing both local and global feature extraction. The adaptive data augmentation method refines the training process, boosting accuracy and robustness. With a dataset of 8226 images, EDA–ViT achieved a classification accuracy of 96.58%, an F1 score of 96.10%, and a Matthews Correlation Coefficient (MCC) of 92.24%, outperforming other models. The inclusion of the Deformable Multi-head Self-Attention (DMSA) mechanism further enhanced feature capture. Ablation studies revealed that the adaptive augmentation contributed to a 0.56% accuracy improvement and a 0.34% increase in MCC. In summary, EDA–ViT presents an innovative solution for custard apple disease diagnosis, with potential applications in broader agricultural disease detection, ultimately aiding precision agriculture and crop health management.

The LTAR Cropland Common Experiment at Lower Chesapeake Bay.

The Lower Chesapeake Bay (LCB) Long-Term Agroecosystem Research (LTAR) Common Experiment (CE) located in Beltsville, MD, focuses on research of concern to producers of the major regional crops, which are corn (Zea mays L.), soybean [Glycine max (L.) Merr.], wheat (Triticum aestivum L.), and various forage species. Livestock production in the region includes broiler and laying chickens (Gallus gallus domesticus L.) and dairy and beef cattle (Bos taurus L.). The LCB region is among the most heavily populated in the United States. Urban development pressure is high for both farms and natural areas. The need to restore Chesapeake Bay water quality is a major influence on regional agricultural practices. Conservation practices such as cover cropping, no-till agriculture, and nutrient management planning are more common in the region compared to nationally. However, farmers still face management challenges implementing practices that address water quality and the rise of herbicide-resistant weeds. Researchers at the LCB site recognize the need to protect the Chesapeake and Delaware Bays and maintain farmer profitability. The LCB CE compares a 3-year crop rotation system featuring alternative crop management (cover crop intensification, crop rotation diversification, and integrated weed management [IWM]) with a prevailing 2-year system (no cover crops and no IWM), both under continuous no-tillage, to identify the optimal balance to promote the sustainability of regional cropping systems. The LTAR LCB site provides data-driven tools and solutions to support farmers in the mid-Atlantic region.

Smart technology-based microclimate control system for greenhouse

This study proposes an agricultural management system designed to enhance productivity by leveraging artificial intelligence and Internet of Things (IoT) technologies. It addresses the complex microclimate conditions within greenhouses by integrating microcontrollers and sensors to monitor parameters such as temperature, humidity, and soil moisture, enabling precise environmental management. Web and mobile applications provide interactive interfaces, allowing users to monitor real-time factors influencing the greenhouse environment. The system can execute actions like activating fans or irrigation pumps based on user inputs or predefined settings. In addition to improving yields, the system aims to create a dataset that can be used for assessing the effectiveness of future machine learning models. Important considerations include data privacy, training farmers to effectively use the technology, and integrating the system with traditional farming practices, thereby enhancing sustainability. Overall, this study aspires to continuously improve agricultural practices by combining modern technology with traditional knowledge, ultimately aiming for a more efficient and sustainable agricultural landscape.

Multi-omics reveal wild habitat is more favorable for the metabolite accumulation in Astragalus mongolicus

Astragalus mongholicus, a well-known traditional Chinese herbal medicine, has been widely used for more than 2000 years. Although previous studies have revealed that the medicinal quality of wild plants is superior to the cultivated plants, the regulatory mechanism responsible for the variations in metabolite accumulation between wild and cultivated A. mongholicus have not yet been conducted. Here, the roots and rhizosphere soils of cultivated, imitated wild and wild A. mongholicus were used for metabolite, transcript and microbiota analysis. The contents of calycosin-7-O-β-D-glucoside (CG) and astragaloside IV were achieved 0.47±0.02 mg/g and 1.17±0.06 mg/g in wild A. mongolicus, which were more than 1.49- and 1.98-fold higher compared to the cultivated A. mongolicus, respectively. Consistently, there were 424 genes differentially co-expressed at least two types of growth pattern, among which 23 genes (i.e. AmPAL, AmCHS, AmHMGS, AmSQE and AmOSC) directly involved in the biosynthesis of CG and astragaloside were significantly higher expressed in wild/imitated wild plants than in cultivated plants. The soil composition differed by region with higher organic matter, available nitrogen in wild regions, while lower pH, available phosphorus and potassium in cultivated regions. Meanwhile, the microbial diversity in wild rhizosphere were significantly lower than that in cultivated rhizosphere. Notably, the high abundance of biomarkers (i.e. Variovorax, Rhizobium and Lysobacter) were observed in wild rhizosphere, which indirectly boosted the metabolite accumulation in wild plant. Taken together, a regulatory model of soil-plant-microbe in A. mongolicus was established by integrating multi-omics analysis, which were of great guidance on the cultivation of A. mongolicus with high medicinal quality via targeted agricultural management.

Use of Probes and Sensors in Agriculture—Current Trends and Future Prospects on Intelligent Monitoring of Soil Moisture and Nutrients

Soil monitoring is essential for promoting sustainability in agriculture, as it helps prevent degradation and optimize the use of natural resources. The introduction of innovative technologies, such as low-cost sensors and intelligent systems, enables the acquisition of real-time data on soil health, increasing productivity and product quality while reducing waste and environmental impact. This study examines various agricultural monitoring technologies, focusing on soil moisture sensors and nutrient detection, along with examples of IoT-based systems. The main characteristics of these technologies are analyzed, providing an overview of their effectiveness and the key differences among various tools for optimizing agricultural management. The aim of the review is to support an informed choice of the most appropriate sensors and technologies, thus contributing to the promotion of sustainable agricultural practices.

A Novel Phenology-Based Index for Plastic-Mulched Farmland Extraction and Its Application in a Typical Agricultural Region of China Using Sentinel-2 Imagery and Google Earth Engine

Plastic-mulching technology has a crucial role to play in modern agriculture by optimizing crop growth environments and enhancing yields. Accurately detecting and mapping the distribution of plastic-mulched farmlands (PMFs) is essential for improving both agricultural management and production efficiency. By analyzing the temporal spectral characteristics of PMFs and crop phenological information, we developed a phenology-based plastic-mulched farmland index (PPMFI). This index, when combined with Sentinel-2 imagery and an automated high-precision extraction process via the Google Earth Engine platform, effectively distinguishes PMFs from other land cover types, especially in complex agricultural landscapes. Validation across areas varying in their background complexity and PMF coverage demonstrated that the proposed PPMFI consistently achieves an overall accuracy rate that exceeds 90%, showcasing its robust performance and significantly outperforming other comparative extraction methods. Applying the PPMFI to the Yudong agricultural region of Henan Province, China, further confirmed its capability for large-scale PMF monitoring, thereby offering critical technical support for sustainable agricultural management and environmental protection.

Mapping the Past Two Decades of Nutrition and Food Security in Iran: A Co-Word Network Analysis

Background: Food security in communities can prevent health complications, so investigators have made efforts to find its related factors through various fields. This study aims to draw a road map for nutrition and food security research in Iran. Methods: Web of Science, PubMed, Scopus, Embase, and Islamic World Citation Center were searched for eligible publications in nutrition and food security related to Iran for the two decades from 2001 to 2020. Content analysis was done by a co-word network technique using VOSviewer software. Results: Finally, 28,995 scientific publications among 50,444 search results were eligible to include in this study. The research map was drawn using 403,262 keywords obtained from the title and abstract of the papers. A 23.53% growth rate of publications was seen. Iranian articles were mainly published in scientific journals under 10 subject categories. The highly repeated keywords of "treatment", "plant", "age", "risk", and "consumption" were in publications. Moreover, the articles were categorized into thematic clusters of "environmental and climate change", "health ", "food industry and food safety", and "agriculture and water resources management" which were related to nutrition and food security. An increasing trend was observed in the number of publications during the past two decades in Iran. Conclusion: The relation of clinical nutrition, malnutrition, diet, and in recent years, food production and climate change with food security have been extensively studied by Iranian researchers. However, they have neglected studies on public health and policy in food and nutrition security, which reveals their dominant clinical or agricultural approach.

Chinese Patent Review of Integrated Management System for Agricultural Machinery

Background: With the rapid development of China's economy and the accelerating process of agricultural mechanization, agricultural machinery has become increasingly popular in agricultural production activities. At the same time, problems in agricultural machinery management have gradually been exposed, hindering the development of modern agriculture. Objective: This study aimed to discuss the development trend of agricultural management and modern agriculture by analyzing and discussing the related patents of agricultural machinery management systems. Methods: The development of agricultural machinery management was summarized, and the representative patents related to agricultural machinery management systems, agricultural machinery automatic control systems, and agricultural machinery terminals were analyzed. Results: By analyzing the existing patents of the agricultural machinery management system, the paper summarized their applications in agricultural management and obtained their future development trend. Conclusion: In agricultural machinery management, we should actively adopt complementary strategies to solve various problems and improve the management level of agricultural machinery. The continuous improvement of the agricultural machinery management system is of great significance to the automation of agricultural production and the modernization of agricultural management in China.

Reasons for milking system adoption: The case of Switzerland

This paper studies the importance which farm managers attach to the investment in the milking system in terms of their (management) objectives and expectations. According to a survey of 455 Swiss farm managers, the main reasons for investment decisions for all milking systems were to reduce labour and physical stress. For parlours, income objectives and animal welfare were more important than for other milking systems. In the case of automatic milking systems (AMS), the focus was on making working hours more flexible and increasing family time. According to farm managers, these objectives were largely achieved. The study shows, that higher income or production volume become less important reasons over the observed time period and that AMS are implemented by older farm managers.

Consumer Safety and Pesticide Residues: Evaluating Mitigation Protocols for Greengrocery

The application of pesticides remains a necessary measure for pest management in agriculture, particularly in the cultivation of fruits and vegetables. After harvest, the presence of pesticide residues in greengrocery (fruits and vegetables) is significantly influenced by various factors, including storage conditions, handling practices, and subsequent processing methods. The mitigation of these residues to levels compliant with regulated maximum thresholds ensures the safety of raw and processed fruits and vegetables for consumption. A contemporary survey of pesticide residues in greengrocery has gathered considerable attention from consumers, driven by concerns over the potential health risk of pesticide exposure. Consequently, consumers want to be extensively informed about household processing techniques to minimize associated risks. Meanwhile, a critical question arises: does household processing effectively eliminate pesticide residues? A comprehensive review of the literature reveals that conventional methods, such as washing and soaking, offer only limited reduction in residue levels, while emerging treatments, suitable both at household and industrial scale, demonstrate increased efficiency in residues mitigation. This study aims to emphasise the ubiquitous use of pesticides in crop cultivation while providing recommendations for the implementation of efficient treatment protocols to address residue concerns. Following upon available evidence and database mining, the worldwide purpose must be to outline agriculturally and economically viable strategies that prioritize both the health and safety of consumers, as well as the green cultivation and processing of fruits and vegetables.

Copper sulfate-induced stress in Spinach: Metabolic pathway disruption and plant response

Copper sulfate (CuSO4) stress profoundly affects plant growth by interfering with key metabolic pathways. This disruption leads to significant alterations in various physiological parameters, ultimately impacting the overall health and productivity of the plant. This study assessed the impact of CuSO4 stress on spinach (Spinacia oleracea L.) through a pot experiment using CuSO4 concentrations of 0, 75, 125, and 175 ppm. We noticed that at 75 ppm, CuSO4 improved plant height and the concentration of soluble sugar and ascorbic acid compared to the control. Additionally, amino acid, phenol, proline, fresh weight, and moisture content peaked at 175 ppm. Conversely, at 125 and 175 ppm, plant height, dry weight, leaf area, and concentrations of ascorbic acid and sugar significantly decreased. Moreover, at 175 ppm, there were substantial decreases in chlorophyll a (14.8%), chlorophyll b (73.6%), carotenoids (15%), and photosynthetic rates compared to the control. However, the chlorophyll a to chlorophyll b ratio increased by 29.53% at 175 ppm. In addition, protein and phenol contents diminished at 75 and 125 ppm. Elevated CuSO4 levels increased non-protein thiol levels while reducing the activities of superoxide dismutase, catalase, ascorbate peroxidase, and glutathione peroxidase. Stress hormones such as abscisic acid, jasmonic acid, and ethylene increased with CuSO4 stress, whereas growth hormones indol-acetic acid and gibberellic acid declined. This study demonstrates that spinach shows improved growth and metabolic function at 75 ppm CuSO4, indicating tolerance to mild stress. However, higher CuSO4 concentrations (125 and 175 ppm) significantly reduce growth parameters, chlorophyll content, and enzyme activities, highlighting the need for careful CuSO4 management in agriculture to avoid adverse effects on plant health and productivity.