Agricultural Production Systems Research Articles

Enhancing pakchoi (Brassica chinensis L.) agriculture with magnetized-ionized brackish water and organic fertilizers: A sustainable approach to soil quality and crop yield optimization

The scarcity of freshwater, the increasing use of brackish water (B) for irrigation, and the judicious application of organic fertilizers have significant research and practical value for environmental science, water resource management, and clean production. This study investigated the combined impact of B, magnetized-ionized brackish water (MIB), and organic fertilizer on pakchoi (Brassica chinensis L.) growth, yield, and soil quality. Over a two-year period (2022–2023), this study explored the impacts of two types of irrigation water (B and magnetized-ionized brackish water, MIB) in combination with varying rates of water-soluble bio-organic fertilizer (0, 20, 40, 60, and 80 kg/ha, corresponding to treatments 0 through 4, respectively). The findings indicated that the application of 60 kg/ha of organic fertilizer greatly improved the growth rate of pakchoi in terms of plant height, leaf area index, and fresh weight. Moreover, under MIB irrigation, the fresh weight growth rate of pakchoi was superior to that observed under B irrigation. Notably, B irrigation necessitated additional fertilizer to maintain elevated levels of alkali-hydrolyzed nitrogen (AN) and soil quality. Furthermore, the use of organic fertilizer substantially enhanced soil quality, with AN, available phosphorus (AP), organic matter (OM), and soil quality index (SQI) demonstrating a strong positive correlation (P < 0.05). Mantel test analysis showed significant correlations (P < 0.05) between soil OM, SWC, AP, and pakchoi growth and yield. According to the partial least squares path modeling analysis, the use of organic fertilizer had a relatively minor effect on the yield and quality of pakchoi under B irrigation, with path coefficients of 0.088 and 0.298, respectively. However, under MIB irrigation, organic fertilizer enhances yield and quality by improving soil quality (path coefficients of 0.914). In conclusion, the application of MIB irrigation coupled with organic fertilizer contributed to sustainable soil fertility, enhanced crop productivity, and mitigated the environmental impacts associated with conventional irrigation and fertilization methods. Our research underscores the importance of supporting agricultural research and development focused on sustainable irrigation and fertilization methods for farmers and policymakers. This integrated approach offers a harmonious solution for optimizing crop yields and enhancing water use efficiency, and the reduction of in chemical pollutants within agricultural production systems.

Maize cultivar mixtures increase aboveground biomass and grain quality via trait dissimilarity and plasticity

Despite being visually cryptic, conspecific cultivar mixtures increase diversity and can increase productivity in agricultural systems. However, the mechanisms underlying this increase are unclear. In natural systems, differences in traits among species and among ecotypes correspond with diversity-increased productivity, but whether these attributes are important in cultivar mixtures is still unclear. To explore how cultivar mixtures affect agroecosystem productivity and the roles of trait dissimilarity, we conducted a four-year (2017–2020) field experiment in Northeast China with maize. The experimental treatments included eight single cultivar monocultures, four two-cultivar mixtures, one four-cultivar mixture, one six-cultivar mixture and one eight-cultivar mixture. Experiments were arranged in a randomized complete block design with three replications. Across the four years, all cultivar mixture combinations increased aboveground biomass and crude protein in grain by 7.0% and 4.1%, respectively, compared to the average of the eight monocultures. Grain yield, aboveground biomass, and grain crude protein in overyielding cultivar combinations increased by 2.0–9.0%, 13.0–20.0% and 4.8–10.7%, respectively, compared to the average of the component monocultures of each mixture over four years. We calculated positive complementarity effects for grain yield, aboveground biomass and grain crude protein. All selection effects of cultivar mixtures were negative or neutral. There were strong positive correlations between complementarity effect and functional trait dissimilarity in cultivar mixtures, based on grain yields (P< 0.010), aboveground biomass (P< 0.001) and grain crude protein (P< 0.050), whereas there were no such positive relationships between selection effects and functional trait dissimilarity. Moreover, we found higher levels of trait dissimilarity for shoot diameter, leaf area and specific leaf area in cultivar mixtures than in monocultures. Also, the shoot diameter, leaf area and specific leaf area of specific cultivars were higher in mixtures than in monocultures. Our results indicated that niche complementarity derives from functional trait dissimilarity, and strong complementarity effects correlate with greater functional trait dissimilarity in cultivar mixtures. These findings provide evidence that plasticity in traits, rather than only inherent traits, contributed to the diversity effects, and the greater functional trait dissimilarity among cultivars in mixtures can increase crop productivity via increasing cryptic diversity in agroecosystems. Our results link changes to plant aboveground traits in cultivar mixtures, which shed light on yield advantages in diverse agroecosystems.

Farm Diversification Programmes in Haryana: A Review

The Green Revolution in the late 1960s enabled India to overcome a severe food shortage and achieve food grain self-sufficiency. Recent trends in crop farming witnessed a multifold shift towards paddy and wheat specialization in Haryana. The sustainability of the future agricultural production system in terms of soil, water, climate and market characteristics is threatened by continuous mono cropping of the rice-wheat cropping system. Increased rice-wheat mono cropping trend necessitates diversification on account of ecological concerns. So, farm diversification is an important strategy to maintain sustainability of the Haryana state agriculture. This article briefly discusses the various diversification initiatives performed in Haryana and their effects.

Digitalization in Agricultural Sector: Agriculture 4.0 for Sustainable Agriculture

Sustainable and resilient systems within the food industry play a key role in global growth and development. In recent years, negative effects such as drought caused by climate change, destructive natural disasters, and destruction of biodiversity and natural resource erosion, agricultural migration, aging agricultural population, and global epidemics have deepened the environmental concerns. Apart from the negative effects on the food supply, pressure on the demand side is created by the growing population, which makes it necessary to create a new agrarian policy. Technological development has affected agriculture and agricultural production systems. One of the most prominent approaches is the integration of a new generation of digital technologies into the agricultural system, ensuring maximum benefit from information and data. Digitalization and the use of digital data have fundamentally transformed the agro-food system. The aim of this paper is present in a systematic view the agricultural digital transformation in the Agriculture 4.0, in the framework of sustainable development of agriculture. The aforementioned imposes sustainable agriculture by adequate agricultural policy instruments.

The nitrogen fertilizer conundrum: why is yield a poor determinant of crops’ nitrogen fertilizer requirements?

The application of nitrogen (N) fertilizer both underpins high productivity of agricultural systems and contributes to multiple environmental harms. The search for ways that farmers can optimize the N fertilizer applications to their crops is of global significance. A common concept in developing recommendations for N fertilizer applications is the “mass balance paradigm” – that is, bigger crops need more N, and smaller less – despite several studies showing that the crop yield at the optimum N rate (Nopt) is poorly related to Nopt. In this study we simulated two contrasting field experiments where crops were grown for 5 and 16 consecutive years under uniform management, but in which yield at Nopt was poorly correlated to Nopt. We found that N lost to the environment relative to yields (i.e., kg N t-1) varied +/- 124 and 164 % of the mean in the simulations of the experiments. Conversely, N exported in harvested produce (kg N t-1) was +/- 11 and 48 % of the mean. Given the experiments were uniformly managed across time, the variations result from crop-to-crop climatic differences. These results provide, for the first time, a quantitative example of the importance of climatic causes of the poor correlation between yield at Nopt and Nopt. An implication of this result is that, even if yield of the coming crop could be accurately predicted it would be of little use in determining the amount of N fertilizer farmers need to apply because of the variability in environmental N losses and/or crop N uptake. These results, in addition to previous empirical evidence that yield at Nopt and Nopt are poorly correlated, may help industry and farmers move to more credible systems of N fertilizer management.

Insect Pests in Agriculture Identifying and Overcoming Challenges through IPM

Insect pests pose significant challenges to agricultural production worldwide, threatening food security and economic stability. Integrated Pest Management (IPM) offers a comprehensive approach to address these challenges sustainably. This abstract explores the principles and strategies of IPM, emphasizing its focus on minimizing environmental impacts and reducing reliance on chemical pesticides. Through biological control, cultural practices, mechanical control, and selective pesticide use, IPM aims to manage pest populations effectively while promoting biodiversity and long-term agricultural sustainability. By implementing IPM strategies, farmers can mitigate the impact of insect pests while fostering resilient and productive agricultural systems.&#x0D; Insect pests pose a significant threat to agricultural productivity worldwide. They can devastate crops, leading to substantial economic losses and threatening food security. Identifying and managing these pests effectively is crucial for sustainable agriculture. Integrated Pest Management (IPM) offers a comprehensive approach to address insect pest challenges while minimizing environmental impacts and reliance on chemical pesticides. Insect pests represent a persistent threat to agricultural productivity and food security globally. This abstract delves into the principles and practices of Integrated Pest Management (IPM) as a sustainable approach to address these challenges. IPM integrates various strategies, including biological control, cultural practices, mechanical control, and selective pesticide use, to manage pest populations effectively while minimizing environmental harm. By emphasizing monitoring, threshold levels, and selective interventions, IPM promotes the judicious use of pesticides and fosters ecosystem resilience. The abstract underscores the importance of IPM in promoting biodiversity, reducing chemical inputs, and ensuring the long-term sustainability of agricultural systems. Through the adoption of IPM principles, farmers can mitigate the impacts of insect pests while advancing environmentally conscious and economically viable agricultural practices.

Enrichment of ruminant meats with health enhancing fatty acids and antioxidants: feed-based effects on nutritional value and human health aspects – invited review

Optimising resource use efficiency in animal- agriculture-production systems is important for the economic, environmental, and social sustainability of food systems. Production of foods with increased health enhancing aspects can add value to the health and wellbeing of the population. However, enrichment of foods, especially meat with health enhancing fatty acids (HEFA) increases susceptibility to peroxidation, which adversely influences its shelf life, nutritional value and eating quality. The meat industry has been challenged to find sustainable strategies that enhance the fatty acid profile and antioxidant actions of meat while mitigating oxidative deterioration and spoilage. Currently, by-products or co-products from agricultural industries containing a balance of HEFA and antioxidant sources seem to be a sustainable strategy to overcome this challenge. However, HEFA and antioxidant enrichment processes are influenced by ruminal lipolysis and biohydrogenation, HEFA-antioxidant interactions in rumen ecosystems and muscle biofortification. A deep understanding of the performance of different agro-by-product-based HEFA and antioxidants and their application in current animal production systems is critical in developing HEFA-antioxidant co-supplementation strategies that would benefit modern consumers who desire nutritious, palatable, safe, healthy, affordable, and welfare friendly meat and processed meat products. The current review presents the latest developments regarding discovery and application of novel sources of health beneficial agro-by-product-based HEFA and antioxidants currently used in the production of HEFA-antioxidant enriched ruminant meats and highlights future research perspectives.

A Bibliometric Analysis of Chickpea Agronomic Practices in the World During 45 Years of Scientific Research

ABSTRACTChickpea (Cicer arietinum L.) cultivation practices underwent significant transformation in recent decades due to advancements in scientific knowledge and the need for sustainable, productive farming systems. In this study, a bibliometric analysis of scientific publications from 1977 to 2023 on chickpea agronomic practices was conducted, revealing critical insights. India, as the world's leading chickpea producer, plays a pivotal role, not only in production but also as a significant contributor to scholarly research and international collaborations. The choice of journals for publication is found to influence research impact.Analysis of research trends using co‐occurrence networks of keywords reveals evolving focuses, with a recent shift towards qualitative aspects, such as protein content and nutritional quality, as well as sustainable agricultural practices. The study also emphasizes the necessity for further research on chickpea quality characteristics, strategies to mitigate antinutritional factors, yield optimization, and the impact of climate change on chickpea cultivation. Ultimately, chickpea cultivation research holds great promise in contributing to global food security and environmental sustainability. This bibliometric analysis provides a comprehensive overview of chickpea cultivation research and offers valuable insights for researchers, policymakers, and stakeholders as they navigate the future of sustainable agriculture and the quest for protein‐rich food production while minimizing the environmental footprint.

Environmental Prediction Model of Solar Greenhouse Based on Improved Harris Hawks Optimization-CatBoost

Solar greenhouses provide a favorable climate environment for the production of counter-seasonal crops in northern China. The greenhouse environment is a key factor affecting crop growth, so accurate prediction of greenhouse environment changes helps to precisely regulate the crop growth environment and helps to promote the growth of fruits and vegetables. In this study, an environmental prediction model based on the combination of a gradient boosting tree and the Harris hawk optimization algorithm (IHHO-Catboost) is constructed, and in response to the problems of the HHO algorithm, such as the fact that the adjustment of the search process is not flexible enough, it cannot be targeted to carry out a stage search, and sometimes it will fall into the local optimum to make the algorithm’s search accuracy relatively poor, an algorithm based on the improved Harris hawk optimization (IHHO) algorithm-based parameter identification method is constructed. The model considers the internal and external environmental and regulatory factors affecting crop growth, which include indoor temperature and humidity, light intensity, carbon dioxide concentration, soil temperature and humidity, outdoor temperature and humidity, light intensity, carbon dioxide concentration, wind direction, wind speed, and opening and closing of upper and lower air openings of the cotton quilt, and is input into a prediction model with a time series for training and testing. The experimental results show that the MAE (mean absolute error) values of temperature, relative humidity, carbon dioxide concentration, and light intensity of the model are reduced to 49.8%, 35.3%, 72.7%, and 32.1%, respectively, compared with LSTM (Long Short-Term Memory), which is a significant decrease in error. It shows that the proposed multi-parameter prediction model for solar greenhouse environments presents an effective method for accurate prediction of environmental data in solar greenhouses. The model not only improves prediction accuracy but also reduces dependence on large data volumes, reduces computational costs, and improves the transparency and interpretability of the model. Through this approach, an effective tool for greenhouse agriculture is provided to help farmers optimize the use of resources, reduce waste, and improve crop yield and quality, ultimately leading to a more efficient and environmentally friendly agricultural production system.

Evaluating the Agricultural Production Systems sIMulator (APSIM) wheat module for California

Context Computer-based crop simulation models are important tools for agricultural research and management. APSIM (Agricultural Production Systems sIMulator) is commonly used around the world but has not been widely validated in North America. Aims The objective of this work was to evaluate the reliability of APSIM for simulating wheat production in California, with the aim of providing guidance for future field research aimed at model calibration and validation. Methods Environmental and management data from state-wide wheat variety trials of common wheat (Triticum aestivum L.) were used to parameterise the APSIM-Wheat module (ver. 7.10 r4220). Simulated yield and protein data were compared with observed field trial results to test the reliability of APSIM simulations. Key results The most reliable simulation of grain yield had a root-mean-square error of 1040 kg/ha and normalised root-mean-square error of 16% relative to actual field data. Preliminary calibration of the model for Californian wheat varieties did not improve simulation accuracy or precision. Conclusions The accuracy or precision of the simulations was comparable to that of other tests of the APSIM-Wheat module in environments where it has not been previously calibrated but was considered too low to be reliable. The lack of reliability was due to the poor representation of local Californian wheat genotypes by existing APSIM cultivars, as well as possible lack of precision and accuracy of field data. Implications APSIM could be a valuable tool for wheat research and management in California; however, further research is needed to generate suitable field data for model calibration and validation.

Participatory Analysis of Impacts of Agricultural Production Systems in a Watershed Depicting Southern Brazilian Agriculture

The objective of this study was to propose a multidimensional model capable of evaluating, in a participatory method, the pressures agricultural production systems cause to aquatic ecosystems. The model was structured with information compiled from scientific articles, doctoral theses, public documents, and field research performed with the participation of stakeholders through interviews, questionnaires, and group evaluations. The evaluation matrix combines seven criteria and twenty-five sub-criteria with different weights to evaluate two main aspects: (i) land occupation and soil management and (ii) agricultural waste production and disposal. The model was tested in 14 agricultural farms, representing four productive arrangements, in a large watershed (2400 km2) in southern Brazil. The geophysical characteristics of the site (18.3%), land use and occupation (28.2%), management practices (soil and water) (25.4%), manure and fertilizers (12.6%), pesticides (14.1%), agricultural waste and discards (1.4%) were the criteria and their respective weights used in the structure of the proposed evaluation model. The evaluation showed that the combination of the fragility of cultivated environments and the absence of conservation practices represented the greatest risks (72.9%) to maintaining the sound environmental conditions of aquatic ecosystems. For future research, it is recommended that a cost-effectiveness analysis be carried out to evaluate environmental conflicts.

Discuss on the Construction of Digital Rural Revitalization Information Service Platform in the New Era

If we want to assume digital rural areas, the focus must be on industrial prosperity, adhere to quality first, green agriculture, and take the structural reform of the agricultural supply side as a guide to further promote the construction speed of modern agricultural industrial system, management system, and production system, thereby improving agricultural productivity, competitiveness, and innovation, and promoting the realization of an agricultural power. In the new era, the system engineering of digital rural projects is relatively complex. It is necessary to adopt advanced system engineering ideas and methods, arrange top-level design, institutional setting, innovative technology, talent cultivation, and optimize operation modes, in order to achieve an information service platform and achieve digital rural revitalization.

Modeling long-term nitrogen utilization under alfalfa–corn rotation in Northeast China

ContextNortheast China is the main commodity grain base in China owing to its intensive corn (Zea mays L.) planting and heavy nitrogen (N) application. Alfalfa (Medicago sativa L.) and corn rotation have the potential to decrease N application and enable efficient N utilization, but its long-term impacts remain unclear. ObjectiveThis study utilized Agricultural Production Systems sIMulator (APSIM) to evaluate the N process of long-term alfalfa–corn rotation, including the soil N status and N legacy benefits of subsequent corn crops, and to optimize alfalfa–corn rotation. MethodsAPSIM was calibrated and validated utilizing datasets of crop N uptake (Nupt), soil inorganic N, and soil total nitrogen (TN) under continuous corn, continuous alfalfa, and rotations of three, four, and five years of alfalfa followed by two years of corn, defined as CC, CA, and 3A2C, 4A2C, and 5A2C treatments, respectively, which were collected from a field experiment in Quanyangou–Lishu, Jilin Province, China during 2014–2022. The validated APSIM was then utilized to simulate long-term (1981–2020) effects on N utilization under CC, 3A2C, 4A2C, and 5A2C treatments at Quanyangou–Lishu, Fujia–Lishu, Chaoyang, and Hailun in Northeast China. ResultsAPSIM effectively simulated the Nupt, inorganic N, and TN, with normalized root mean square errors of 5%–19%, 20%–30%, and 2.0%–4.2%, respectively, between the observed and simulated values. Compared with the CC treatment, alfalfa–corn rotation treatments reduced the N fertilizer application by 143 kg N ha−1 and significantly improved the net N mineralization and Nupt by 41 and 107 kg N ha−1, respectively, achieving increases of 50% and 517% in N use efficiency and N partial factor productivity based on corn equivalent yield, respectively. Alfalfa–corn rotation also consumed 94% of 200–500 cm inorganic N through alfalfa roots absorbing N after 9–14 years, which decreased the risk of soil inorganic N accumulation and N leaching. After 40 years, SON values of alfalfa–corn rotation treatments were 8% and 4% higher in the 0–20 and 20–60 cm soil layers and 1.6% lower in the 60–200 cm soil layer than those of the CC treatment at Quanyangou–Lishu, Fujia–Lishu and Hailun. The SON values of alfalfa–corn rotation treatments were 2.9% lower in three soil layers at 0–200 cm deep relative to those of the CC treatment at Chaoyang, with low precipitation of only 478 mm. Alfalfa–corn rotation also improved the first-year corn yield following alfalfa by 2.3%–8.8% at Quanyangou–Lishu and Fujia–Lishu. ConclusionsThe 4A2C treatment at Quanyangou–Lishu, Fujia–Lishu, and Hailun and the 3A2C treatment at Chaoyang are recommended in Northeast China to increase N use efficiency and N partial factor productivity by decreasing N fertilizer application, increasing SON, and absorbing inorganic N from the 200–500 cm soil layer during the alfalfa growing period and increasing mineral N during the corn growing period. ImplicationsOptimal alfalfa–corn rotations show great potential to reduce soil inorganic N residue and increase N use efficiency and SON in Northeast China.

Justification of innovative technology for variety and phytocleaning in breeding and seed plantings of potatoes and vegetable crops

The purpose of the research is to substantiate theoretically the process of variety and phytocleaning in breeding and seed plantings of potatoes and vegetable crops using machine vision technologies and robotic elements. The article analyzes modern non-destructive methods for detecting diseases of biological objects; technological processes and machines for removing the fruits of vegetable crops from plants in a digital agricultural production system with elements of robotization in the operations of caring for plants and collecting marketable products. The relevance of developing innovative technology and technical means for removing infected potato and vegetable plants in breeding and seed production has been established. To carry out health-improving techniques for the production of vegetable and potato seeds, an innovative technology and machine have been developed for removing infected potato and vegetable crop plants in breeding and seed-growing plantings, providing movement across the field using machine vision technologies with the identification of an infected plant or a plant that does not correspond to the varietal characteristics with its subsequent removal. In the process of the research (2021-2022), a morphological matrix for selecting technical means of using functioning elements for implementing innovative technology for varietal and phytocleaning of vegetable crops and potatoes, as well as the theoretical foundations of innovative technology for removing contaminated biological objects, were developed. An indicator of the effectiveness of the implementation of innovative phytotype cleaning technology has been identified, taking into account the parameters of economic and agrotechnical indicators, as well as metal intensity, energy intensity, environmental friendliness and reliability. Analytical studies of machine technology and technical means for removing infected vegetable and potato plants are presented. A substantiation of the innovative technology for varietal and phytocleaning of vegetable crops and potatoes has been carried out, in terms of the exclusion of an unmanned aerial vehicle in the technology for detecting infected potato plants with a qualitative assessment of the feasibility of choosing technical means when using the functioning elements of the implementation of the developed technology according to the criteria of economic and agrotechnical assessment, as well as metal intensity, energy intensity and reliability . An assessment of the feasibility of choosing technical means for the functioning of elements of innovative technology showed that, according to a set of criteria, the process of varietal and phytocleaning of vegetable crops and potatoes is advisable to carry out without the use of an unmanned aerial vehicle, using an optical system for identifying infected plants in the design of the machine.

Quantitative analysis of soil degradation in response to land use change in the Guinea savanna zone of Ghana

Soil degradation (SD) poses a significant challenge to tropical agricultural production systems due to its role in depleting soil nutrients. Recently, SD has threatened population growth by causing hunger and poverty among smallholder farmers in the Guinea savanna agro-ecological zone of Ghana. However, SD cannot be directly measured. Instead, assessment and modelling efforts rely on biological and physico-chemical indicators. This study sought to: (i) select a minimum dataset (MDS) using a multivariate statistical technique; (ii) identify SD processes, and evaluate the extent of degradation; and (iii) suggest strategies to monitor SD in the study area. Soil samples were collected using the Land Degradation Surveillance Framework (LDSF), specifically designed for sub-plot level (1000 m2) sampling. This scheme aligns well with the typical farm structure of smallholder farmers (<10 acres). Soil samples, taken from a depth of 0–20 cm, were analyzed to assess their physico-chemical properties. Principal component analysis (PCA) identified seven key SD processes: soil texture, pH, organic carbon (OC), total nitrogen (TN), available phosphorus (Av. P), base saturation (BS) and Effective Cation Exchange Capacity (ECEC). These identified processes lead to the loss of OC, deterioration of soil texture, reduction in soil nutrients, and increased soil acidity. There was a strong positive correlation (r = 0.70, p<0.05) between soil physical and chemical properties. PC1 explained 26.86% of the total variance, followed by PC2 at 15.31%, PC3 at 12.46%, and PC4 at 9.98%. Also, PC5, PC6, and PC7 accounted for 8.49%, 7.25% and 1.42% of the variance, respectively. The land-use systems we identified significantly affected the concentration of soil nutrients (p<0.001). In our computed Composite Soil Degradation Index (CSDI), CEC emerged as the most significant SD indicator with a weight of 0.328, followed by Si:CL ratio at 0.187. The results indicate that soil management activities should focus on increasing organic matter. Soil nutrient depletion primarily occurs through several processes. Land clearing and burning of organic materials during land preparation are primary causes. Furthermore, a total crop removal during harvest, inadequate manure application, and subsequent leaching and erosion aggravates SD, leading to nutrient-depleted soils. We conclude that the loss of nutrients, specifically CEC, OC, Ex. K and Av. P is the primary contributor to chemical SD. Therefore, implementing integrated soil fertility management (ISFM) strategies, such as applying organic (e.g., animal-based manures, green manure, crop residues, compost) and inorganic fertilizers (e.g., NPK + micronutrients) is crucial for increasing soil nutrient availability, enhancing SOM content, and promoting carbon sequestration in these farming systems. This study establishes a baseline for comparing and evaluating the effectiveness of land management interventions at the landscape level in northern Ghana. Consequently, soil nutrient management should be tailored to site-specific conditions, focusing on increasing the efficiency of N, P, K and micronutrient uptake by plants. Adopting such site-specific management strategies could significantly contribute to the sustainable intensification of agricultural production systems in the Guinea Savanna agro-ecological zone of Ghana.

Research on the Digital Transformation of the Whole Industry Chain of Guangdong Supply and Marketing Cooperative

Guangdong Supply and Marketing Cooperative serves as an important institution for the “Three Rural Areas” in the Guangdong-Hong Kong-Macao Greater Bay Area. Its digital transformation and optimization serve as powerful supports for rural revitalization. This paper systematically reviews the main practices and effectiveness of the digital transformation within the Guangdong Supply and Marketing Cooperative. It also analyzes the current development dilemmas faced in the construction of digital supply and marketing. Additionally, it proposes targeted solutions, including building a big data resource base, optimizing the digital supply and marketing cloud platform, developing digital public-type agricultural social service applications, establishing a new model of rural e-commerce, enhancing the traceability management system for agricultural products, and strengthening the construction of the digital human resources system. These proposals aim to further promote the strategy for revitalizing the countryside.

Comprehensive Survey on Applications of Internet of Things, Machine Learning and Artificial Intelligence in Precision Agriculture

A comprehensive, multidisciplinary analysis of the latest developments in digital agriculture is conducted with the use of artificial intelligence (AI), machine learning (ML), and the Internet of Things. By automation and the use of modern, scalable technology solutions that reduce risks, support sustainability, and give farmers predictive advice, traditional agricultural processes are being updated and improved to maximize production. In this paper, the applications of AI, IoT, and ML in agricultural production systems are discussed in detail. The applications that have been explored can be broadly categorized into three areas: soil management, livestock management, and crop management. Weed detection, disease identification, and yield forecasting are some of the applications for crop management. Two applications of livestock management are animal welfare and production. The use of AI, IoT, and ML will make it possible to collect data from agricultural activities for analysis and the extraction of insightful knowledge, facilitating prompt and accurate decision making to increase agricultural productivity. This will result in farming that is more exact and efficient while requiring less labour and producing high-quality produce.

The Roles of Plant-Growth-Promoting Rhizobacteria (PGPR)-Based Biostimulants for Agricultural Production Systems.

The application of biostimulants has been proven to be an advantageous tool and an appropriate form of management towards the effective use of natural resources, food security, and the beneficial effects on plant growth and yield. Plant-growth-promoting rhizobacteria (PGPR) are microbes connected with plant roots that can increase plant growth by different methods such as producing plant hormones and molecules to improve plant growth or providing increased mineral nutrition. They can colonize all ecological niches of roots to all stages of crop development, and they can affect plant growth and development directly by modulating plant hormone levels and enhancing nutrient acquisition such as of potassium, phosphorus, nitrogen, and essential minerals, or indirectly via reducing the inhibitory impacts of different pathogens in the forms of biocontrol parameters. Many plant-associated species such as Pseudomonas, Acinetobacter, Streptomyces, Serratia, Arthrobacter, and Rhodococcus can increase plant growth by improving plant disease resistance, synthesizing growth-stimulating plant hormones, and suppressing pathogenic microorganisms. The application of biostimulants is both an environmentally friendly practice and a promising method that can enhance the sustainability of horticultural and agricultural production systems as well as promote the quantity and quality of foods. They can also reduce the global dependence on hazardous agricultural chemicals. Science Direct, Google Scholar, Springer Link, CAB Direct, Scopus, Springer Link, Taylor and Francis, Web of Science, and Wiley Online Library were checked, and the search was conducted on all manuscript sections in accordance with the terms Acinetobacter, Arthrobacter, Enterobacter, Ochrobactrum, Pseudomonas, Rhodococcus, Serratia, Streptomyces, Biostimulants, Plant growth promoting rhizobactera, and Stenotrophomonas. The aim of this manuscript is to survey the effects of plant-growth-promoting rhizobacteria by presenting case studies and successful paradigms in various agricultural and horticultural crops.

The Use of Financial Tools in Small-Scale Irrigated Crops to Assess Socioeconomic Sustainability: A Case Study in Tocantins-Araguaia Basin, Brazil

To expand financial knowledge and promote the socioeconomic sustainability of agricultural production systems, this work applied financial instruments to small-scale irrigated crops, making use of agricultural projects from the Bom Sucesso/Santa Cruz Settlement, located in the Tocantins-Araguaia basin, Brazil. The economic viability indicators of two irrigated okra production systems (furrow and drip) were calculated using the following indicators: Net Present Value, Modified Internal Rate of Return, Cost–Benefit Index, Discounted Payback, and Average Cost of Production. And a risk assessment through sensitivity analysis, a tornado chart, and Monte Carlo simulation was performed in a simplified financial model. The economic viability results showed that both irrigated systems were economically viable, although the okra drip system had lower indicators and reduced financial resilience, with a 58% probability of success, while the furrow system’s was 89%. The crops’ financial return was mainly influenced by okra’s sale price and productivity, followed by harvesting and planting costs. The financial tools applied in this study demonstrated some key factors to assess socioeconomic sustainability, such as the necessity to increase producers’ organizational capacity and to achieve technical improvements, which could result in market power, competitive sale prices, lower input costs, and greater productivity. The applied instruments increased financial management and have the potential to the build economic and social strength in the area of small-scale irrigated crops, and they can be replicated using simplified tools for producers, companies, and policy makers.

Determination of the main agricultural crops for the Metropolitan Puebla-Tlaxcala area using the Papadakis Methodology

agricultural crops in the Puebla-Tlaxcala Metropolitan Area (ZMPT). Design/methodology/approach: From April to June 2022, the classification process for identifying the main crops in the ZMPT was conducted. This process utilized monthly climatic data from the Mexican Institute of Water Technology (IMTA), analyzed through the Papadakis methodology (1970). Subsequently, the results were mapped using the Weighted Overlay (WO) tool in ArcGIS v.10.2. Results: The Papadakis methodology identified 10 seasonal crop types, particularly for summer and winter. The WO tool categorized potential areas into five classes: optimal, highly suitable, acceptable, and unacceptable for the establishment of several crops. Limitations on study/implications: This study has limitations due to incomplete and scarce databases and the complexity and cost associated with the software used. However, the implications for agriculture include the potential to enhance and diversify agricultural production by identifying optimal areas for establishment, especially in urban-peri-urban agricultural areas (UPAs). Findings/conclusions: This study successfully identified the main crops cultivated in the ZMPT and highlighted potential areas for their establishment. The generated cartographic information enables the strategic distribution of productive agricultural systems, particularly in UPAs, to adapt to regional climate fluctuations in the short, medium, and long term. Besides, an adequate distribution in the implementation of productive agricultural systems, particularly in UPAs, depending on fluctuations in the climatic conditions of the region.