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A study of the influence of farming practices in the Middle Ages (X–XV AD) on the activities of 11 hydrolytic enzymes involved in the biogeochemical cycles of major elements in soils has been carried out. Agrostratozems of Medieval agricultural terraces in Dagestan mountains (Plaggic and Hortic Anthrosols) were chosen as objects of study. In all cases, the enzymatic activity of the studied soils decreased in all soil layers in the following sequence: alkaline phosphatase > phosphodiesterase > acid phosphatase > pyrophosphatase ≥ leucine aminopeptidase > arylsulfatase > chitinase > β-glucosidase > xylanase > α-glucosidase > cellobiohydrolase. The enzymatic activity of the studied soils was primarily determined by the amount of microbial biomass (Cmic). Thus, the activity of enzymes of various groups depended on Cmic by 61–94%. Agricultural practices associated with ploughing, manuring, and irrigation induce the convergence in the activity of nitrogen cycle enzymes in soils of the mountain zone, which is associated with similar features of the nitrogen cycle in agrogenic soils, regardless of bioclimatic conditions. The addition of organic materials has led to an increase in the physiological efficiency of microbial communities and the rate of enzyme production, and high levels of biological activity can persist in soil for about 1000 years. Ploughing with the application of organic fertilizers in the past led to an increase in enzymatic activity expressed per unit of microbial biomass (specific activity), therefore, this indicator can be used as an indicator of agrogenic transformation of soils in the past. [ABSTRACT FROM AUTHOR]

This paper identified the intangible aspects (IA) that generate impacts in companies of the agricultural sector in the different stages of the companies life cycle. This paper is based on a systematic review methodology to identify intangibles in the agricultural sector. Studies on the life cycle of companies were analyzed to classify the impact of intangible aspects according to the reality of companies. Identify the intangible aspects that impact the agricultural sector through a review of the scientific literature. How intangible aspects affect each stage of the life cycle of companies in the sector shows that they have a different impact depending on the period in which the company is located. Although, much of the previous literature has suggested that intangible aspects have positive effects on a variety of performance variables, there are no scientific studies that specifically address the importance of these intangible aspects in the life cycle of companies in the agricultural sector. [ABSTRACT FROM AUTHOR]

Community science bioassessment has great potential to inform comprehensive stream management plans, but regional analytical tools are needed to evaluate macroinvertebrate data collected through community science programs. To this end, we modified a pre-existing professional index of biotic integrity (IBI) to create a community science IBI (CS-IBI), designed for stream macroinvertebrate data collected by community scientists with minimal training. We used data collected by both professional and community scientists to develop, calibrate, and validate the CS-IBI at 76 stream sites in the Puget Lowland and Willamette Valley ecoregions of the Pacific Northwest in the United States. Community science data were taxonomically coarser and more variable than data generated by professionals; however, IBI scores and assemblage data were statistically similar between community science and professional data. Stream impairment categories classified by family-level CS-IBI scores matched genus-level professional classifications 65% of the time and never diverged by >1 category. CS-IBI scores were negatively related to the percentage of agriculture and land development in the watershed, although this relationship was weaker than for professional IBI scores. Despite increased variability in data generated by community scientists, our findings suggest the CS-IBI performs similarly to a professional IBI across a gradient of human influence. Although we do not advocate using the CS-IBI in regulatory settings, we believe the development of community science IBIs enhances, expands, and strengthens public partnerships, thereby supporting environmental managers' efforts to monitor and restore degraded streams and rapidly respond to pollution events. Our hope is that the CS-IBI will improve the applicability of community science bioassessment data and serve as a model for how agencies can develop regionalized macroinvertebrate IBIs for use in comprehensive watershed management plans. [ABSTRACT FROM AUTHOR]

Niche construction theory has played a prominent role in archaeology during the last decade. However, the potential of niche construction in relation to agricultural development has received less attention. To this end, we bring together literature on the forms and sources of agronomic variability and use a series of examples to highlight the importance of reciprocal causation and ecological inheritance in trajectories of agricultural change. We demonstrate how niche construction theory can inform on emergent mutualisms in both inceptive and established agronomic contexts, the recursive relationships between humans and their agronomic environments, and bridges between the past and present. [ABSTRACT FROM AUTHOR]

In Peru, formal and informal organizations are key actors in promoting agroecological farming and related social goals but struggle to make significant changes for gender equality. In this study, I seek to understand how organizations conceptualize their role in gender equality throughout project design, implementation, and presentation. While the organizations designed their projects around organizational change, the implementation and presentation of their work focused on improving financial security and agricultural literacy for individual women rather than systemic conditions. Despite this, their efforts underscored the importance of women’s contributions and furthered the conversation about gender in Peruvian agriculture. [ABSTRACT FROM AUTHOR]

Lynchets are ridges formed by erosion and sediment accumulation downstream of agricultural plots and offer valuable insights into past agricultural activity. These microtopographies cover vast areas and serve as indicators of historical changes in land use. As a result, their ubiquity across Europe makes them particularly interesting. In this study, we propose a geoarchaeological approach to analyze six lynchets, four in the Vosges Mountains and two on the Lorraine Plateau (France). The lynchets can be considered soil archives with no stratigraphic organization or chronological sequence from bottom to top, making it difficult to determine the age of the lynchets and identify changes in land use over time. To this end, we propose the analysis of historical and geo‐historical archives combined with the "pedosedimentary" archives of lynchets through charcoal identification and dating combined with near‐infrared spectroscopy to determine the age, vegetation, and past land use changes associated with lynchet landscapes. By combining these multiple data sources, we are better able to show the chronological development of these ancient agricultural systems and uncover valuable information on landscape history. Charcoal dating suggests a higher frequency of fires from the Middle Ages. The dating aligns with the regional dynamics of anthropogenic fires, indicating a potential use of fire for cultural purposes. We also demonstrate the difficulty of extrapolating the dating of a lynchet to the entire lynchet system. Our results highlight the difficulties of interpreting the formation and dating of lynchets and the lynchet system on the sole basis of charcoal analysis. However, we highlight the value of applying pedoanthracology to lynchets to determine the dynamics of land use change in former fields. [ABSTRACT FROM AUTHOR]

Agricultural nonpoint source pollution (ANPS) can cause systemic pollution of the ecological environment, directly threatening sustainable agricultural development and human health and safety. Accurate estimation of ANPS loads, clarification of the sources and spatial distribution patterns of ANPS, and effective control and management of ANPS in the watershed require identifying critical source areas. This case study focuses on the Danjiang River basin, a critical water source for China's South-to-North Water Division and demonstrates the efficiency of ArcGIS's spatial statistical analysis methods in discovering the hidden spatial pattern of ANPS and extracting the causes associated with the spatial pattern, as well as the accuracy of identifying critical source areas of ANPS. In this study, two spatial statistical analysis methods, Anselin local Moran's I and hot-spot analysis (Getis–Ord Gi*), are applied to propose a method for accurately identifying critical source areas of ANPS based on the spatial distribution of ANPS loads. The results of the study are as follows: (1) based on the MIKE LOAD model, the annual ANPS loads of chemical oxygen demand (COD), ammonia nitrogen (NH4), total nitrogen (TN), and total phosphorus (TP) in the Danhan River basin are calculated as 182,530.15, 16,137.39, 58,285.92, and 2,962.84 t/yr , respectively. (2) Clusters are mainly distributed in the southwestern part of the watershed, and the spatial pattern is directly related to land use and rural population; the spatial pattern of outliers is related to agricultural modes and geographical characteristics. (3) Hot spot clusters are concentrated in the hinterland of Hanzhong Plain; the regional specialty of agriculture is the dominant factor in determining the spatial pattern of cold-spot and hot-spot clusters. (4) Based on these findings, seven critical subbasins and one critical source area of ANPS that need to be prioritized for control in the study area are identified. Agricultural nonpoint source pollution (ANPS) is a significant cause of ecosystem pollution, which directly threatens the sustainable development of agriculture, human health, and safety. The Dan–Han River Basin is a crucial water source in China for the South-to-North Water Diversion Project and provides water to 140 million people. It is essential to ensure that the water quality of the Dan-Han River remains unpolluted. The ANPS as a major source of water pollution in the watershed is difficult to identify and control. Accurately identifying the sources and spatial distribution patterns of ANPS pollutants is a prerequisite for maintaining water quality and controlling ANPS. Our study offers a new perspective on methods to reveal the hidden spatial pattern and identify critical source areas of ANPS in watersheds. This research demonstrates the effectiveness of ArcGIS's spatial statistical analysis methods in discovering the hidden spatial pattern of ANPS, extracting the causes associated with the spatial pattern, and accurately identifying critical source areas of ANPS. These methods can also be applied to study nonpoint source pollution in other watersheds. [ABSTRACT FROM AUTHOR]

BACKGROUND: A variety of environmental factors can disrupt biotic interactions between plants, insects and soil microorganisms with consequences for agricultural management and production. Many of these belowground interactions are mediated by volatile organic compounds (VOCs) which can be used for communication under appropriate environmental conditions. Behavioral responses to these compounds may likewise be dependent on varying soil conditions which are influenced by a changing climate. To determine how changing environmental conditions may affect VOC‐mediated biotic interactions, we used a belowground system where entomopathogenic nematodes (EPNs) – tiny roundworm parasitoids of soil‐borne insects – respond to VOCs by moving through the soil pore matrix. Specifically, we used two genera of EPNs – Heterorhabditis and Steinernema – that are known to respond to four specific terpenes – α‐pinene, linalool, d‐limonene and pregeijerene – released by the roots of plants in the presence of herbivores. We assessed the response of these nematodes to these terpenes under three moisture regimes to determine whether drier conditions or inundated conditions may influence the response behavior of these nematodes. RESULTS: Our results illustrate that the recovery rate of EPNs is positively associated with soil moisture concentration. As soil moisture concentration increases from 6% to 18%, substantially more nematodes are recovered from bioassays. In addition, we find that soil moisture influences EPN preference for VOCs, as illustrated in the variable response rates. Certain compounds shifted from acting as a repellent to acting as an attractant and vice versa depending on the soil moisture concentration. CONCLUSION: On a broad scale, we demonstrate that soil moisture has a significant effect on EPN host‐seeking behavior. EPN efficacy as biological control agents could be affected by climate change projections that predict varying soil moisture concentrations. We recommend that maintaining nematodes as biological control agents is essential for sustainable agriculture development, as they significantly contribute not only to soil health but also to efficient pest management. © 2024 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

Emerging climate-development processes jeopardize water supply, especially in the Global South. In the Vietnamese Mekong Delta, disrupted water flows driven by climate change and hydropower development have caused water scarcity, threatening agricultural systems in both upstream and coastal areas. Based on insights from desk reviews, stakeholder workshops and interviews with local informants, this paper argues that while grey (engineered) solutions take precedence in addressing water scarcity, securing water sustainability (water retention) for agricultural resilience demands integrated 'grey–green' (engineered-nature-based) solutions. This paper suggests demands for translating this approach into the water governance framework for the delta's agricultural development. [ABSTRACT FROM AUTHOR]

Scientific measurement of Agricultural Carbon Emissions (ACE) and its formation mechanism is of great significance for the effective formulation of high-quality agricultural development strategies. Therefore, the objectives were to study the characteristics of ACE, its formation mechanism, and its economic relevance in Chongqing by adopting the IPCC and 1997-2019 data, and with LMDI index and Decoupling index. The empirical analysis shows that the total ACE presents an M-shaped trend of "rising-steady fluctuation-falling". Energy structure, energy intensity, and population size have a negative driving effect on ACE, but economic activity is the main factor. The decoupling elasticity characteristics of ACE and economic growth are mainly weak decoupling and strong decoupling, of which the relationship is significantly coordinate. Therefore, to consolidate and enhance the goal of ACE reduction, it is necessary to strengthen the research and development of agricultural low-carbon production technology and promotion. We will continue to deepen supply-side structural reform in agriculture. We will improve the ecological environment in agriculture and rural areas. [ABSTRACT FROM AUTHOR]

Soil moisture plays a crucial role in determining the yield of winter wheat. The Huang-Huai-Hai (HHH) Plain is the main growing area of winter wheat in China, and frequent occurrence of drought seriously restricts regional agricultural development. Hence, a daily-scale Non-stationary Standardized Precipitation Evapotranspiration Index (NSPEI), based on winter wheat crop coefficient (Kc), was developed in the present study to evaluate the impact of drought characteristics on winter wheat in different growth stages. Results showed that the water demand for winter wheat decreased with the increase in latitude, and the water shortage was affected by effective precipitation, showing a decreasing trend from the middle to both sides in the HHH Plain. Water demand and water shortage showed an increasing trend at the jointing stage and heading stage, while other growth stages showed a decreasing trend. The spatial distributions of drought duration and intensity were consistent, which were higher in the northern region than in the southern region. Moreover, the water shortage and drought intensity at the jointing stage and heading stage showed an increasing trend. The drought had the greatest impact on winter wheat yield at the tillering stage, jointing stage, and heading stage, and the proportions of drought risk vulnerability in these three stages accounted for 0.25, 0.21, and 0.19, respectively. The high-value areas of winter wheat loss due to drought were mainly distributed in the northeast and south-central regions. [ABSTRACT FROM AUTHOR]

In the context of sustainable agriculture and biomaterial development, understanding and enhancing plant secondary cell wall formation are crucial for improving crop fiber quality and biomass conversion efficiency. This is especially critical for economically important crops like upland cotton (Gossypium hirsutum L.), for which fiber quality and its processing properties are essential. Through comprehensive genome-wide screening and analysis of expression patterns, we identified a particularly high expression of an R2R3 MYB transcription factor, GhMYB52 Like, in the development of the secondary cell wall in cotton fiber cells. Utilizing gene-editing technology to generate a loss-of-function mutant to clarify the role of GhMYB52 Like, we revealed that GhMYB52 Like does not directly contribute to cellulose synthesis in cotton fibers but instead represses a subset of lignin biosynthesis genes, establishing it as a lignin biosynthesis inhibitor. Concurrently, a substantial decrease in the lint index, a critical measure of cotton yield, was noted in parallel with an elevation in lignin levels. This study not only deepens our understanding of the molecular mechanisms underlying cotton fiber development but also offers new perspectives for the molecular improvement of other economically important crops and the enhancement of biomass energy utilization. [ABSTRACT FROM AUTHOR]

In light of the environmental pollution resulting from the excessive use of chemical fertilizers, several methods, including the analysis of morphological and cultural characteristics as well as ITS rDNA sequencing, were utilized to identify the strain and evaluate its phosphate solubilizing capacity. A controlled greenhouse pot experiment was then conducted to assess the effects of the phosphate solubilizing bacteria strain Y-5 on crop growth and soil fertility. The identification results revealed that the phosphate solubilizing strain, Y-5, belongs to Pseudomonas donghuensis. Under liquid culture for 5 days, the ratio of the phosphate solubilizing ring's diameter to the colony's diameter (D/d) was 3.51. Notably, strain Y-5 exhibited exceptional phosphate solubilization efficiency, with a maximum phosphate solubilizing amount of calcium phosphate reaching 432.25 mg/L. Furthermore, the highest phosphate soluble content of lecithin was 116.37 mg/L, highlighting its robust phosphate solubilizing capacity. The pot experiment results revealed that the modified biochar of strain Y-5 effectively enhances the content of available phosphate and organic matter in soil. Additionally, the modified biochar of the Y-5 strain exerted a significant growth-promoting effect on corn seedlings. Based on the indices of maize seedling growth and soil property changes, it was determined that the optimal application ratio of Pseudomonas donghuensis modified biochar was approximately 10 g/kg. This research result significantly reduced the cost of popularizing and applying phosphate solubilizing bacteria modified biochar and served as a new agricultural material with good prospects for popularization and application, potentially contributing to the green and sustainable development of agriculture in the future. [ABSTRACT FROM AUTHOR]

Agricultural and industrial production activities generate GDP and greatly improve the quality of life of residents. At the same time, these activities also lead to increased energy consumption and emit large amounts of pollutants, which affect public health. However, there has been little past research focused on all the above associations. This study innovatively proposes a parallel two-stage EBM-DEA model to re-measure health production efficiency. The objective is to conduct a joint analysis of the economic development, pollutant emissions and human health of agriculture and industry in 30 provinces in China from 2016 to 2020, and calculate the health production efficiency, stage efficiency (agricultural production efficiency, industrial production efficiency and health efficiency) and environmental pollution efficiency. The research shows that the health production efficiency in other provinces has not reached the efficiency frontier except in Beijing, Fujian, Zhejiang, and Ningxia. In addition, there is room for improvement to varying degrees. In terms of geographical disparity, agricultural production efficiency and health efficiency are distributed in the trend of east > west > central, whereas industrial production efficiency is distributed in a ladder shape from east > central > west. Health efficiency contributes to overall efficiency, whereas agricultural and industrial production efficiencies drag down overall efficiency. The discharge efficiency of various pollutants shows that China's environmental control policies have achieved good results, but environmental problems in some provinces are still serious. Moreover, areas with higher pollutant discharge efficiency values have higher tuberculosis incidence efficiency values. Furthermore, provinces should pay attention to improving the efficiency of medical and health fund utilization. [ABSTRACT FROM AUTHOR]

Reducing and sequestering agricultural carbon is a crucial measure for achieving carbon neutrality and carbon peak, as well as an integral component of agricultural modernization. This study uses the super-efficiency Slack-based measure-Data envelopement analysis (SBM-DEA) and Exploratory spatial data analysis (ESDA) models to examine the spatiotemporal differentiation characteristics of agricultural ecological efficiency (AEE) in 38 districts and counties of Chongqing. The results indicate that the CRR-DEA model disregards the impact of undesirable output factors and overestimates the actual utilization of agricultural resources, whereas the super-efficiency SBM-DEA model is more consistent with the actual agricultural production process. Chongqing's AEE was at a high level of efficiency and the distribution of spatial pattern is uneven, displaying a development pattern of "The urban agglomeration in the Three Gorges Reservoir area of Northeast Chongqing (UTC)>Main urban metropolitan area (MUA) > Wuling Mountain urban agglomeration in southeast Chongqing (WUC)", and there is a significant agglomeration characteristic among various districts and counties. The High-High (H-H) agglomeration is primarily concentrated in the central urban area and the Low-Low (L-L) agglomeration area is primarily located in the eastern portion of UTC. Consequently, all regions in Chongqing should combine their own agricultural development characteristics, maximize their strengths, compensate for their weaknesses, and thereby enhance the AEE. [ABSTRACT FROM AUTHOR]

The adoption of green control technologies in agriculture is an important approach to ensure the quality and safety of agricultural products, address agricultural pollution from its source, and promote increased productivity and income in agriculture, thereby driving high-quality agricultural development. This paper is based on production and operation data from 2,155 tea farmers in 16 major tea-producing provinces in China. Using an endogenous transformation model from the perspective of the value chain, it empirically analyzes the impact of adopting green control technologies on tea farmers' income and draws three conclusions. First, the adoption of green control technologies significantly promotes income growth for tea farmers. Second, the awareness of tea farmers regarding pesticide residue limits and the exchange of pest control techniques among tea farmers significantly enhance the adoption of green control technologies. Third, the income effects of adopting green control technologies differ across different stages of the value chain, with the income growth in the cultivation stage being lower than that in the processing and marketing stages. Finally, based on the analysis and relevant research by scholars, four targeted suggestions are proposed: (1) Increase efforts to promote the adoption of green control technologies and enhance farmers' willingness to adopt them. (2) Promote education and training on green control technologies for tea farmers. (3) Ensure fair distribution of benefits along the agricultural value chain. (4) Strengthen the promotion of green control technologies at the market and consumer end. [ABSTRACT FROM AUTHOR]

Ice core provides a valuable vertical timeline of past climates and anthropogenic activities. Environmental proxies have been widely used in these studies, but there are few biological indicators available. To address this gap, we investigated the bacterial community from a 74 m ice core of Muztag ata glacier on the Tibetan Plateau to link biological indicators with past climate and anthropogenic activities. By analyzing the portion of the ice core with environmental proxies available (corresponding to 1907 to 1991), we observed an increase in bacterial richness throughout the ice core, which was associated with higher NH4+, an indicator of agricultural development. The bacterial community was jointly determined by human activity, natural input, and air temperature, with a strong human influence after the 1950s. Furthermore, the relative abundance of animal gut-associated bacteria, including Aerococcaceae, Nocardiaceae, Muribaculaceae, and Lachnospiraceae, was associated with livestock number changes in the Central Asian region. Together with other bacterial lineages, they jointly explained 59.8% of the livestock number changes. This study provides quantitative evidence of the associations between bacterial indicators and past climate and human activities, highlighting the potential of using bacterial proxies for ice core studies. [ABSTRACT FROM AUTHOR]

Context: Rising demand from Vietnam for Lao goat meat has triggered a rapid increase in goat numbers in Lao Peoples Democratic Republic (Lao PDR). Despite the increased market opportunity for smallholder farmers in Laos, goat production remains low input within free-grazing management systems. Aims: Qualitative research was conducted to explore the role that goat production plays in farmers' livelihood strategies and farming systems, including the benefits and associated trade-offs, so as to inform development approaches to improve goat husbandry and productivity. Methods: Semi-structured interviews were conducted with 30 smallholder goat farmers across five villages in southern-central Laos. Interview transcripts were analysed using grounded theory methodology with the assistance of the Nvivo 12 software program. Key results: The interviews showed that goats were a profitable and liquid asset for farmers. Income from goats was used for small expenses that occurred frequently or at short notice, such as household loans or debts, utility and medical costs and buying food and clothing for family members. Goats had socio-cultural purposes, with some farmers preferring to consume goats during celebratory occasions over other livestock species. Managing goats was easy and benefited the wider farming system by providing goat manure to fertilise crop plantations. Conclusions: Goat productivity and goats' unique subsistence and socio-cultural roles can be enhanced by improving goat kid management, goat-house design and cleaning, and by implementing disease management. These activities can be low input. Implications: The government policy and future development projects in Laos should focus on increasing goat productivity rather than increasing the scale of farmers' goat enterprises. The majority of farmers may not benefit from significantly increasing the scale of their goat enterprises because of trade-offs associated with free-grazing management, including goats damaging crops or becoming lost or involved in accidents such as dog attacks and car accidents. Goats fulfil unique subsistence and socio-cultural roles in smallholder farmers' livelihoods in Laos. Increasing goat productivity can improve conditions of farmers' livelihoods, but it is unclear which approaches are most appropriate for resource-constrained farmers who balance multiple farming enterprises on small plots of land. Some approaches to increasing goat productivity are more applicable in Laos than are others. These approaches should be prioritised by the Government of Laos' policy and development projects to benefit the widest cohorts of farmers. This article belongs to the Collection Sustainable Animal Agriculture for Developing Countries 2023. [ABSTRACT FROM AUTHOR]

Agricultural endeavors, especially in developing nations, entail inherent risks. Amidst challenges related to capital and agricultural marketing, contract farming emerges as a highly effective strategy. It not only facilitates capital accumulation but also ensures consistent product sales, establishes fair pricing, and contributes to the overall balanced development of the agricultural sector. This concern has been a longstanding global consideration, with Iran now addressing it. Recognizing the paramount importance of implementing contemporary agricultural methodologies, including contract farming, this research systematically investigates factors influencing farmers' intentions in Iran. A survey methodology is employed for systematic information collection from a statistical population of 98,777 farmers in rural Markazi Province, Iran. Using the Karjesi and Morgan table for sample size determination, a representative subset of 383 farmers is selected through stratified random sampling, ensuring proportional assignment within strata. A researcher-made questionnaire, validated by expert panels and confirmed for reliability through Cronbach's alpha coefficient, serves as the research instrument. Data analysis was conducted using SPSS 27, and structural equation modeling was performed with SmartPLS4. The findings reveal that trust (0.528), awareness (0.332), and attitude (0.168), exert the most substantial causal influence on farmers' intention to embrace contract farming. Consequently, the research findings offer practical recommendations for the adoption of contract farming, providing valuable insights to policymakers and stakeholders for implementing targeted interventions aimed at boosting farmers' willingness to participate in contractual agreements. [ABSTRACT FROM AUTHOR]

Agricultural endeavors, especially in developing nations, entail inherent risks. Amidst challenges related to capital and agricultural marketing, contract farming emerges as a highly effective strategy. It not only facilitates capital accumulation but also ensures consistent product sales, establishes fair pricing, and contributes to the overall balanced development of the agricultural sector. This concern has been a longstanding global consideration, with Iran now addressing it. Recognizing the paramount importance of implementing contemporary agricultural methodologies, including contract farming, this research systematically investigates factors influencing farmers' intentions in Iran. A survey methodology is employed for systematic information collection from a statistical population of 98,777 farmers in rural Markazi Province, Iran. Using the Karjesi and Morgan table for sample size determination, a representative subset of 383 farmers is selected through stratified random sampling, ensuring proportional assignment within strata. A researcher-made questionnaire, validated by expert panels and confirmed for reliability through Cronbach's alpha coefficient, serves as the research instrument. Data analysis was conducted using SPSS 27, and structural equation modeling was performed with SmartPLS4. The findings reveal that trust (0.528), awareness (0.332), and attitude (0.168), exert the most substantial causal influence on farmers' intention to embrace contract farming. Consequently, the research findings offer practical recommendations for the adoption of contract farming, providing valuable insights to policymakers and stakeholders for implementing targeted interventions aimed at boosting farmers' willingness to participate in contractual agreements. [ABSTRACT FROM AUTHOR]

Background: Anthrax is a zoonotic disease that is still regarded as a public health issue in developing nations. This paper aims to discuss the epidemiology of anthrax in Africa, the current outbreaks in Ghana and Nigeria, clinical presentations, diagnosis, and treatment of anthrax, challenges associated with the transmission of the disease to both countries and recommendations to reduce this current outbreak and curb future outbreaks in Africa. Online databases (PubMed, and Google Scholar) and Nigeria Ministry of Agriculture report were used to provide detailed information on the paper. On June 1, 2023, two suspected human cases of anthrax were reported, via a letter sent to all stakeholders in the country, with one death in Binduri District, Upper East region of Ghana. The cases were due to the consumption of dead cattle. Four cattle were reported dead at the time, and eleven suspected human cases were identified through contact tracing. Afterward, on July 17, 2023, the Federal Ministry of Agriculture and Rural Development of Nigeria announced the first case of anthrax disease in Nigeria. The National Veterinary Research Institute confirmed the case from samples collected from a suspected livestock farm in Niger State, Nigeria. No human case has been reported. Short conclusion: Anthrax poses significant challenges to public health and requires cooperation between nations, especially in regions like Ghana and Nigeria, where animal movement and ecological changes can impact disease transmission. Challenges attributed to the spread of anthrax in both countries were discussed, focusing on the role of government and the general public in addressing this public health concern. Given the endemicity of certain transboundary animal diseases such as anthrax in sub-Saharan Africa, the control of animal movement across intra- and international borders in the region needs to be tightened. Regulations governing the transboundary movement of animals should be based on the World Organisation of Animal Health Terrestrial Code and should be strictly enforced to prevent ongoing and future outbreaks in Africa. [ABSTRACT FROM AUTHOR]

The role of carbon emissions resulting from land use change in the compilation of national greenhouse gas emission inventories is of paramount significance. This study is centered on the Mianyang Science and Technology City New Area located in Sichuan Province, China. We used the CLUE-S model and Sentinel-2A remote sensing data from 2017 to simulate and validate land use changes in 2022. Based on this validation, we established three simulation scenarios: a baseline scenario, an agricultural development scenario, and a construction development scenario. Using remote sensing data from 2022, we projected the land use for 2030. We also used CO2 concentration data collected in 2022 and 2023, processed the data using ArcGIS and Python, and conducted a quantitative analysis of carbon emissions under each scenario. Ultimately, the accuracy of both measured and predicted CO2 values for 2023 was juxtaposed and authenticated, thus concluding the investigative cycle of this study. Key findings include: (1) The accuracy of the CLUE-S model in the study area was assessed using overall accuracy, quantity disagreement and allocation disagreement indexes. In 2022, the overall accuracy is 98.19%, the quantity disagreement is 1.7%, and the allocation disagreement is 2.2%. (2) Distinct land resource utilization characteristics in scenarios, highlighting potential impacts on economic development and pollution. (3) Increased carbon emissions across scenarios, with construction development showing the highest rise (4.170%) and agricultural development the lowest (0.766%). (4) The predictive accuracy of the validation group's CO2 concentration values can reach 99.5%. This study proposes precise CO2 prediction at the county level, thus laying the groundwork for future research endeavors. Such findings are indispensable for informing carbon policy formulation and promoting low-carbon development strategies. [ABSTRACT FROM AUTHOR]

Nowadays, metal oxide semiconductor gas sensors have diverse applications ranging from human health to smart agriculture with the development of Internet of Things (IoT) technologies. However, high operating temperatures and an unsatisfactory detection capability (high sensitivity, fast response/recovery speed, etc.) hinder their integration into the IoT. Herein, a ternary heterostructure was prepared by decorating WO3 nanoplates with Au and SnO2 nanoparticles through a facial photochemical deposition method. This was employed as a sensing material for 3-hydroxy-2-butanone (3H-2B), a biomarker of Listeria monocytogenes. These Au/SnO2–WO3 nanoplate-based sensors exhibited an excellent response (Ra/Rg = 662) to 25 ppm 3H-2B, which was 24 times higher than that of pure WO3 nanoplates at 140 °C. Moreover, the 3H-2B sensor showed an ultrafast response and recovery speed to 25 ppm 3H-2B as well as high selectivity. These excellent sensing performances could be attributed to the rich Au/SnO2–WO3 active interfaces and the excellent transport of carriers in nanoplates. Furthermore, a wireless portable gas sensor equipped with the Au/SnO2–WO3 nanoplates was assembled, which was tested using 3H-2B with known concentrations to study the possibilities of real-time gas monitoring in food quality and safety. [ABSTRACT FROM AUTHOR]

The object of the study is the determination of ecological and economic efficiency in relation to the production of organic niche products. The strategic perspective of the production and export of organic niche products in Ukraine is considered as one of the ways to overcome economic challenges exacerbated by global instability and geopolitical tensions. The production of organic products is outlined as a strategically important direction of the country’s agricultural sector, which has significant export potential, especially to the countries of the European Union, where there is a steady increase in demand for organic products. A comprehensive approach to strategy implementation is proposed, which includes market research, production development, marketing and branding, as well as optimization of logistics and export processes. The dynamics of the main indicators of the development of organic agriculture in Ukraine from 2010–2021, the volume of imports of organic products to the countries of the European Union by exporting countries were analyzed. To date, only 1 % of agricultural crops are «eco», the volume of organic products has significantly increased, and the yield of organic products has increased by 5–20 % with a corresponding reduction in material costs. Since the end of the 1990s, the agricultural sector of Ukraine began to focus intensively on organic production, taking into account the growing global trend towards the sustainable development of the agro-industrial complex, etc. Given their uniqueness, growing niche crops can offer advantages such as minimal competition and the potential for significant profits, especially when the products find widespread use. A comparative analysis of the production of organic products on the domestic and foreign markets of Ukraine was conducted. A SWOT analysis of the production of organic products in Ukraine was developed to determine the strengths and weaknesses. The practical value is providing advice to producers on growing niche crops, creating market demand, attracting foreign partners to implement such projects in Ukraine, which will contribute to strengthening the economic potential of agricultural producers. This will help increase the competitiveness of domestic enterprises in the local and global markets, make them more resistant to economic challenges and help reduce risks, etc. [ABSTRACT FROM AUTHOR]

Purpose: This study empirically examines the impact of climate change and agricultural research and development (R&D) as well as their interaction on agricultural productivity in 12 selected Asian and Pacific countries over the period of 1990–2018. Design/methodology/approach: Various estimation methods for panel data, including Fixed Effects (FE), the Feasible Generalized Least Squares (FGLS) and two-step System Generalized Method of Moments (SGMM) were used. Findings: Results show that both proxies of climate change – temperature and precipitation – have negative impacts on agricultural productivity. Notably, agricultural R&D investments not only increase agricultural productivity but also mitigate the detrimental impact of climate change proxied by temperature on agricultural productivity. Interestingly, climate change proxied by precipitation initially reduces agricultural productivity until a threshold of agricultural R&D beyond which precipitation increases agricultural productivity. Practical implications: The findings imply useful policies to boost agricultural productivity by using R&D in the context of rising climate change in the vulnerable continent. Originality/value: This study contributes to the literature in two ways. First, this study examines how climate change affects agricultural productivity in Asian and Pacific countries – those are most vulnerable to climate change. Second, this study assesses the role of R&D in improving agricultural productivity as well as its moderating effect in reducing the harmful impact of climate change on agricultural productivity. [ABSTRACT FROM AUTHOR]

In the present era, the characteristics of agricultural development most exposed to the effects of global warming and irregular precipitation patterns remain scantily understood in the regions. The latest study aimed to identify the target regions with different degrees of variation in the average temperature, followed by their resource potential, conditions, strengthening, and production efficiency. Based on their groups through statistical studies, three groups of Russian regions attained partition (using a sample that included 77 Russian regions), with low (Group I - 20 regions), medium (Group II - 25 regions), and high (Group III - 32 regions) estimates of the linear temperature trend. In Group III, 72% of the regions appeared favorable for agriculture, according to the classification approved by the Russian Government. In Group I, 60% of the regions emerged as unfavorable. Based on the statistical indicators, these established that Group III has a considerable resource potential for agriculture, comprising 30% of agricultural lands, 36% of all crops, up to 50% of the area of fruit and berry plantations, 40% of milk production, and 69% of meat and meat products manufacture intended in this group of different regions. In Group III, conditions and intensification of production are developing more dynamically (the volume of subsidies allocated during the study period has increased almost five times), efficiency is higher (profit per 100 ha of agricultural land in Group I is 0.2 million rubles, whereas, in Group III, it equals 1 million rubles), with significant labor and human potential gathered there. This circumstance requires the development of a program for the adaptation of these regions to emerging climate changes. [ABSTRACT FROM AUTHOR]

To build the foundation of food security and accelerate the pace of building a strong agricultural country, it is necessary to promote the high-quality development of agriculture. This is not only the core path of Chinese-style modernization, but also the key to meeting international and domestic development challenges. In the great journey towards Chinese-style modernization, we must deeply realize that the development of the times, the international situation and domestic demand have jointly shaped the important position of building a strong agricultural country. At present, it is necessary not only to enhance the comprehensive agricultural production capacity, but also to promote the rural economic revitalization and enhance the consumption capacity of rural residents. In addition, it is necessary to give full play to the diversity of agricultural science and technology, improve the sustainable development of rural environment and enhance the competitiveness of agriculture. Therefore, promoting the construction of a powerful agricultural country is an urgent need to pay equal attention to the yield, quality, and safety of food. To promote the construction of a strong agricultural country and consolidate the foundation of food security with Chinese-style modernization, the following measures should be taken: Optimizing the food security system to ensure national food security, accelerate scientific and technological research and realize technological innovation of grain production, explore the diversified development model of agriculture and promote the transformation and upgrading of agricultural industrial structure, promote the construction of agricultural management organizations and improve the efficiency of agricultural management, empowering opening to the outside world and enhancing the competitiveness of Chinese agricultural products in the global market. [ABSTRACT FROM AUTHOR]

Animal husbandry is one of the pillar industries for agricultural and rural development, which has a significant impact on ensuring food safety. Under the promotion of the rural revitalization strategy, the construction of a Chinesestyle animal husbandry power has achieved certain results. The pace of transformation and upgrading of Chinese animal husbandry industry has accelerated, production capacity has continued to improve, and quality, efficiency, and competitiveness have continued to improve. The continuous growth of the animal husbandry industry greatly drives rural development and increases farmers' income. Technological support has been strengthened, the green development process has been comprehensively promoted, and significant achievements have been made in the construction of a Chinese-style animal husbandry power. Based on this, the construction of a Chinese-style animal husbandry power needs to practice the concept of green development, adapt to the specific embodiment of high-quality development requirements, and promote the key path and core task of common prosperity. The development of animal husbandry needs to fill the industry's shortcomings, comprehensively improve the quality of development, adhere to expand domestic demand, and effectively drive the accelerated growth of agriculture and rural economy. We should deepen technological reform, empower the green transformation and upgrading of the animal husbandry industry, and provide useful references for driving the construction of a Chinese style animal husbandry power. [ABSTRACT FROM AUTHOR]

Ensuring that marginalized populations become empowered in agriculture is vital to the success of global agricultural development goals. However, these populations have reported lacking access, power, and voice. Perhaps one strategy researchers can use to address this issue is through visual Q methodology. In this methodological paper, I argue that by combining the tenets of Q and visual methodologies, researchers can offer empirically grounded findings that evoke powerful, rich insight into the perspectives of marginalized populations in agriculture who may lack the communication skills to articulate their perspectives through words. To this point, however, the approach has lacked clear guidance, which has led to diminished quality in the published literature on visual Q methodology. In response, I offer six principles to guide visual Q methodological studies moving forward: (a) relationship-building with participants, (b) participant training, (c) concourse development, (d) Q set sampling, (e) data collection, and (f) data analysis and interpretation. [ABSTRACT FROM AUTHOR]

The spread of ill information with or without the intention of deceiving or causing harm has negatively impacted agricultural development both in social and digital spaces. This has led to a lack of trust in adopting new technologies and practices, which has hindered the process of facilitating agricultural development. Although the study of agri-food misinformation is still in its early stages, this paper draws on a scoping review of existing literature and lessons learned from other fields, such as political science and public health, which have extensive experience in combating misinformation in social settings. The article explores how Farmer Field Schools (FFS), a popular participatory and community-based approach, can incorporate media literacy education and how a local agricultural information hub, platform approach and a relatively new approach called technology stewardship in agricultural extension can help those working in the agri-food industry combat misinformation. [ABSTRACT FROM AUTHOR]

Gender assessments are often used to inform gender mainstreaming in agriculture for development programming and practices. However, they often lack true community engagement, integration of critical perspectives for structural transformation, and a systems approach to support gender equality. In our qualitative case study, we conducted a content analysis of gender policies and approaches for the largest funding and implementing organizations working in Honduras. Our findings indicate that some organizations address the known gaps in the effectiveness of gender analyses such as inclusion of masculinities and moving beyond economic empowerment to address other important domains for women's empowerment. However, the majority of organizations continued to approach participation as extractive rather than transformative, over-relied on the economic domain as the sole indicator of empowerment, failed to integrate critical contemporary theories such as intersectionality and masculinities, and inadequately addressed the fundamental structural inequalities in the systems that reinforce normative gender roles. Improving practices for participatory gender assessments and addressing dominant social norms during research is necessary to have significant gender transformative and sustainable impacts on agrifood systems. [ABSTRACT FROM AUTHOR]

As we race towards 2030, the target date for achieving the U.N. Sustainable Development Goals, it is critical that we examine our approaches to agricultural development research and practice. We should not expect extraordinary results by using the approaches we have always used. Rather, we must innovate. To that end, Advancements in Agricultural Development held a Symposium on Methods of Agricultural Development Research and Practice in October 2023 on the University of Reading campus, co-hosted by the School of Agriculture, Policy and Development. We invited recognized experts from around the world to develop papers focused on innovative methods of agricultural development practice or innovative methods of agricultural development research. We had ten papers presented that were authored by 26 researchers representing 13 universities/research institutes in 6 countries. Sixteen authors attended the symposium to present their papers. A healthy dialogue followed each presentation to help authors refine their papers, resulting in the articles published in this special issue. A summary of each article is provided. [ABSTRACT FROM AUTHOR]

Precise and timely prediction of crop yields is crucial for food security and the development of agricultural policies. However, crop yield is influenced by multiple factors within complex growth environments. Previous research has paid relatively little attention to the interference of environmental factors and drought on the growth of winter wheat. Therefore, there is an urgent need for more effective methods to explore the inherent relationship between these factors and crop yield, making precise yield prediction increasingly important. This study was based on four type of indicators including meteorological, crop growth status, environmental, and drought index, from October 2003 to June 2019 in Henan Province as the basic data for predicting winter wheat yield. Using the sparrow search algorithm combined with random forest (SSA-RF) under different input indicators, accuracy of winter wheat yield estimation was calculated. The estimation accuracy of SSA-RF was compared with partial least squares regression (PLSR), extreme gradient boosting (XG-Boost), and random forest (RF) models. Finally, the determined optimal yield estimation method was used to predict winter wheat yield in three typical years. Following are the findings: 1) the SSA-RF demonstrates superior performance in estimating winter wheat yield compared to other algorithms. The best yield estimation method is achieved by four types indicators' composition with SSA-RF) (R2 = 0.805, RRMSE = 9.9%. 2) Crops growth status and environmental indicators play significant roles in wheat yield estimation, accounting for 46% and 22% of the yield importance among all indicators, respectively. 3) Selecting indicators from October to April of the following year yielded the highest accuracy in winter wheat yield estimation, with an R2 of 0.826 and an RAISE of 9.0%. Yield estimates can be completed two months before the winter wheat harvest in June. 4) The predicted performance will be slightly affected by severe drought. Compared with severe drought year (2011) (R2 = 0.680) and normal year (2017) (R2 = 0.790), the SSA-RF model has higher prediction accuracy for wet year (2018) (R2 = 0.820). This study could provide an innovative approach for remote sensing estimation of winter wheat yield, yield. [ABSTRACT FROM AUTHOR]

Real-time acquisition of location information for agricultural robotic systems is a prerequisite for achieving high-precision intelligent navigation. This paper proposes a data filtering and combined positioning method, and establishes an active screening model. The dynamic and static positioning drift points of the carrier are eliminated or replaced, reducing the complexity of the original Global Navigation Satellite System (GNSS) output data in the positioning system. Compared with the traditional Kalman filter combined positioning method, the proposed active filtering–Kalman filter algorithm can reduce the maximum distance deviation of the carrier along a straight line from 0.145 m to 0.055 m and along a curve from 0.184 m to 0.0640 m. This study focuses on agricultural robot positioning technology, which has an important influence on the development of smart agriculture. [ABSTRACT FROM AUTHOR]

Background: Drought is an important factor restricting the development of agriculture. In recent years, plant growth regulators have achieved more results in improving crop stress resistance. The physiological mechanism of exogenous application of mepiquat chloride on soybean seedlings has undergone significant changes under drought stress. Methods: In order to study the effect of exogenous chlorine on the physiology of soybean under drought stress., 'Heinong 65' was used as the experimental material, 15% PEG-6000 was used to simulate drought stress and different concentrations of mepiquat chloride solution (100, 300, 500, 700 mg/L) were sprayed at the three-leaf stage of soybean growth by pot method. The dry matter accumulation, auxin (IAA), zeatin (ZA), gibberellin (GA3), abscisic acid (ABA) content and superoxide dismutase (SOD), peroxidase (POD), catalase (CAT), ascorbate peroxidase (APX) activity of soybean were determined. Result: The results showed that the activities of antioxidant enzymes SOD, POD, CAT and APX in soybean leaves under drought stress were significantly increased by the treatment of appropriate concentration of mepiquat chloride solution. IAA, GA3 and ZA endogenous hormone levels increased, dry matter accumulation increased, root-shoot ratio and ABA endogenous hormone levels decreased significantly. It can be seen that mepiquat chloride treatment can improve the antioxidant capacity, promote the growth of soybean seedlings under drought stress and effectively alleviate the inhibition of drought stress on soybean growth and development. [ABSTRACT FROM AUTHOR]

Determining a suitable "dry sowing and wet emergence" water control program for cotton fields in the arid regions of Northwest China is of great significance in saving water resources, improving economic efficiency, and promoting sustainable development of agriculture. The objective of this study was to analyze the effects of different "dry sowing and wet emergence" water control treatments on dry matter accumulation, chlorophyll fluorescence, yield quality, and water productivity of cotton, and to determine the optimal "dry sowing and wet emergence" water control program for cotton growth in arid areas. A two-year experiment was carried out in 2021 and 2022 in mulched drip-irrigated cotton fields, with a total of 13 treatments of different seedling water quantities (2021: 67.5 mm, 90 mm, 112.5 mm; 2022: 6 mm, 10.5 mm, 15 mm) and different drip frequencies (frequencies means number of drops at seedling stage) (2021: one, two, three times; 2022: two times, four times) in the "dry sowing and wet emergence". Results indicated a positive correlation between increased seedling water quantity and growth indexes. High seedling water quantity treatment demonstrated a 14.33% higher cotton yield than the low seedling water quantity treatment. In comparison with low-frequency treatment, the high-frequency treatment exhibited significantly larger cotton plant height, dry matter accumulation, and yield. Over two years, the average values increased by 8.69%, 16.4%, and 15.91%, respectively, with a 14.55% increase in the coefficient of photochemical quenching of the leaf blade (qP). The high frequency and larger amount of seedling water quantity treatments showed significantly higher irrigation water productivity, with increases of 39.2% and 70.2% compared to the winter irrigation control treatment. In summary, the appropriate "dry sowing wet emergence" water regulation mode (the first drip: 15 mm, the second drip: 4.5 mm, the third drip: 22.5 mm, the fourth drip: 15 mm) can ensure crop yield quality under the premise of significantly reducing the agricultural irrigation water, which can provide certain theoretical support for the green, efficient, and sustainable development of the local cotton industry. [ABSTRACT FROM AUTHOR]

Duckweed growing in paddy fields (DGP) has substantially increased because of the effects of climate warming and/or eutrophication in irrigated water. Previous studies have primarily focused on investigating the effects of DGP as a nonchemical agent for enhancing rice productivity on nitrogen utilization in rice paddy fields. However, how DGP impacts rice yield remains poorly understood. Therefore, a field experiment with three representative rice cultivars was conducted to determine the effects of DGP on rice yield, considering ecological factors, photosynthetic capacity, spectral changes, and plant growth. The results showed that DGP significantly reduced the pH value by 0.6 and the daily water temperature by 0.6 °C, accelerated rice heading by 1.6 days and increased the soil and plant analyzer development (SPAD) and photosynthetic rate of leaves by 10.8% and 14.4% on average, respectively. DGP also markedly enhanced the values of various vegetation indices such as RARSc, MTCI, GCI, NDVI705, CI, CIrededge, mND705, SR705, and GM, and the first derivative curve of the rice canopy reflectance spectrum exhibited a 'red shift' phenomenon upon DGP treatment. Changes in the aforementioned factors may lead to average increases of 4.7% in plant height, 15.0% in dry matter weight, 10.6% in panicles m−2, 2.3% in 1000-grain weight, and ultimately a 10.2% increase in grain yield. The correlation observed suggested that the DGP-induced enhancement in grain yield can be achieved by reducing the pH and temperature of the paddy water, thus enhancing the SPAD value and photosynthesis of leaves and stimulating rice plant growth. These results could offer valuable theoretical support for the future sustainable development of agriculture and the environment through the biological synergy between rice and duckweed. [ABSTRACT FROM AUTHOR]

Ensuring the security of germplasm resources is of great significance for the sustainable development of agriculture and ecological balance. By combining the morphological characteristics of maize seeds with hyperspectral data, maize variety classification has been achieved using machine learning algorithms. Initially, the morphological data of seeds are obtained from images, followed by the selection of feature subsets using Recursive Feature Elimination (RFE) and Select From Model (SFM) methods, indicating that features selected by RFE exhibit better performance in maize seed classification. For hyperspectral data (350–2500 nm), Competitive Adaptive Re-weighted Sampling (CARS) and the Successive Projections Algorithm (SPA) are employed to extract feature wavelengths, with the SPA algorithm demonstrating superior performance in maize seed classification tasks. Subsequently, the two sets of data are merged, and a Random Forest (RF) classifier optimized by Grey Wolf Optimization (GWO) is utilized. Given the limitations of GWO, strategies such as logistic chaotic mapping for population initialization, random perturbation, and final replacement mechanisms are incorporated to enhance the algorithm's search capabilities. The experimental results show that the proposed ZGWO-RF model achieves an accuracy of 95.9%, precision of 96.2%, and recall of 96.1% on the test set, outperforming the unimproved model. The constructed model exhibits improved identification effects on multi-source data, providing a new tool for non-destructive testing and the accurate classification of seeds in the future. [ABSTRACT FROM AUTHOR]

Private land protection is an important and growing tool to address biodiversity loss and climate change. Thus, better empirical evidence on the effectiveness of private land protection and organizational practices, such as targeting of lands for protection and choice of protection mechanism (i.e., fee simple land acquisition and conservation easements), is needed. We addressed this gap by estimating the impacts of The Nature Conservancy's (TNC) (a large nongovernmental organization with relatively decentralized management) conservation land acquisitions and easements from 1988 to 2016 in three regions of the United States (Mid‐Atlantic, New England and New York, and California). We estimated impact in terms of avoided conversion by comparing natural land cover on 3179 protected parcels with matched unprotected parcels. Nineteen of 21 ecoregional plans used threats of agriculture and development to identify priorities for protection. When regions and protection mechanisms were pooled, on average there was no evidence of avoided conversion from 1988 to 2016. Accounting for mechanisms, TNC land acquisitions avoided conversion and easements did not. TNC's easements on parcels acquired by conservation partners did avoid conversion. Limitations of these results include focus on a single measure of impact, inability to capture future avoided conversion, and low land cover change accuracy in California. Our results suggest that private land protection managers who seek to avoid land conversion in the near to medium term should increase focus on areas with higher threats. Special attention should be paid to strengthening accountability and the role of partners, improving or clarifying how easements are used, and facilitating the flow of resources to work with the greatest potential impact. [ABSTRACT FROM AUTHOR]

The adverse impacts of climate change and the disparity between water availability and demand in agriculture necessitate the development of water-efficient irrigation schedules. The empirically derived crop water stress index (CWSI) is a popular tool for the detection of water stress in crops and the scheduling of water-efficient irrigation regimes. But the sensitivity of the empirical CWSI to the input parameters, i.e., air temperature (Ta), canopy temperature (Tc), and relative humidity (RH), is rarely studied. This study is conducted on wheat crops in the Uttar Pradesh province of India where four irrigation scheduling strategies/treatments are experimented with to study CWSI and its sensitivity to Tc and meteorological parameters (Ta and RH). Two irrigation scheduling strategies correspond to drip irrigation and the remaining two correspond to flood irrigation. The mean CWSI values, derived by empirical approach, are 0.11 and 0.03 for drip irrigated treatments and 0.29 and 0.31 for flood irrigated treatments. To observe the sensitivity of the empirical CWSI to the input parameters, initially, the accuracies of the research-grade equipment, used for taking Tc, Ta, and RH observations, are used as error values in the input parameters. This resulted in 3.5 to 7% errors in the empirically derived CWSI values. A maximum error of 2.7% was observed in CWSI values when an error of 10% was introduced in the RH data. The maximum error in CWSI (52%) was observed for the case when a combined error in Ta, Tc, and RH by −1 °C, 1 °C, and 10%, respectively, were introduced. A random error in the range −1 to 1 °C in Tc resulted in a maximum CWSI error of 21%. Out of the three input parameters, CWSI was found to be least sensitive to RH and with sensitivity to both Ta and Tc showing similar trends. A common pattern of decreasing error in CWSI values for increasing vapor pressure deficit (VPD) was observed for all the studied cases. The results show that the water stress, as reflected by the CWSI values, was significantly lower for the drip irrigation treatments as compared to the flood irrigation treatments. Also, small errors in the input parameters may combine to result in significant errors in empirically derived CWSI. Hence, data quality is critical for the studies that utilize CWSI for irrigation scheduling, especially in humid climatic conditions. [ABSTRACT FROM AUTHOR]

In the present study, headspace gas chromatography coupled with mass spectrometry (HS–GC/MS) was applied to profile volatile components of Bunium persicum samples (rhizomes, roots, stems, leaves, flowers and unripe & ripe seeds), which were collected from two locations of Indian alpine Himalaya. Thirty-six different volatile metabolites were characterized in all samples, representing (77.9-96.9%) of the total oils. Extracted volatile oils (VOs) were dominated by monoterpenes (37.9-94.8%), oxygenated monoterpenes (0.1-28.8%) and sesquiterpenes (0.2-24.3%) hydrocarbons. γ-Terpinene (6.0-64.1%), α-terpinolene (1.1-43.7%), p-cymene (0.4-8.9%), o-cymene (1.4-14.8%), sabinene (0.1-12.3%), β-pinene (0.7-14.2%), β-myrcene (1.2-11.0%), limonene (1.3-9.3%), sylvestrene (3.1-7.7%), and cymen-7-al (6.9-10.9%) were key volatile components identified in different parts of B. persicum using HS–GC/MS. These findings revealed a very high quantitative variation of VOs composition among the samples. The multivariate statistical analysis also classified these variations within the plants and their parts at two locations. HS-GC/MS technique can be utilized for the quality assessment and discrimination analysis of B. persicum, especially its essential oil (BEO). Further, essential oils of both the seed samples showed significant antioxidant activity in DPPH and ABTS assay. The current methodology will help to monitor the varietal development and smart agriculture practices as quality perspectives. [ABSTRACT FROM AUTHOR]