Agricultural Safety Research Articles

Assessing Produce Growers’ Perceptions and Adoption of Agricultural Water Safety Practices in the United States

The Produce Rule regulates food safety among produce growers in the United States. Policy exemptions (e.g., for farms with average produce sales under USD 30,000 over three years) pose a threat to local food safety, particularly given exempt growers’ role in fresh produce production. Understanding exempt growers’ perceptions of food safety practices and the factors influencing their voluntary adoption is crucial. A cross-sectional quantitative survey was conducted to assess growers’ current engagement, their perceptions of agricultural water safety practices, and their influence on adoption decisions. The findings indicate inadequate engagement with agricultural water safety practices, with production water-related safety practices showing higher engagement compared to post-harvest water practices. Overall, growers reported favorable perceptions toward agricultural water safety practices. The perceived compatibility, relative advantage, and observability predicted adoption decisions among exempt growers, with the perceived compatibility being the strongest predictor. Policymakers and education professionals should design strategies and tailored educational interventions and messaging for exempt growers to emphasize the compatibility, relative advantage, and observability of agricultural water safety practices. Furthermore, it is recommended to explore policies and other mechanisms to increase the perceived relative advantage (immediacy of rewards and direct benefits) for exempt growers to promote voluntary adoption of these on-farm food safety practices.

Agricultural Health and Safety: Evaluating Farmers’ Knowledge, Attitude, and Safety Behavior in Northern Thailand

BackgroundAgriculture is vital for economic growth and livelihoods in northern Thailand, yet it is challenged by hazardous practices such as improper chemical use and machinery accidents. This study aimed to evaluate the risk and determine the relationship between pesticide exposure and knowledge, attitudes, and safety behaviors. MethodsThis cross-sectional study was conducted between October and December 2017 in the San Pa Tong district of Chiang Mai, Thailand. Data were collected through structured questionnaires and face-to-face interviews with 280 farmers. ResultsThe findings indicated that knowledge and safety behavior scores varied significantly with educational attainment and training received. Farmers with higher education levels or those who had undergone training exhibited better knowledge and safer behavioral practices, whereas income levels did not significantly affect knowledge or safety behaviors. The pesticide exposure risk level was associated with the study variables, with those recognizing a ‘normal’ risk level demonstrating greater knowledge and safer behaviors than those who reported the risk level as safe or at risk. A strong positive correlation between knowledge and safety behavior was observed, indicating that increased awareness can result in more cautious practices. These findings suggest that educational and training programs are crucial for promoting safer pesticide use among farmers. Although attitudes toward pesticide safety varied based on income, education, and training positively influenced knowledge and behavior. ConclusionThe study concludes that understanding farmers’ perceptions of pesticide risks is essential for designing and implementing effective educational interventions.

Selective Detection of Paraquat in Adulterated and Complex Environmental Samples Using Raman Spectroelectrochemistry.

Growing demand for pesticides has created an environment prone to deceptive activities, where counterfeit or adulterated pesticide products infiltrate the market, often escaping rapid detection. This situation presents a significant challenge for sensor technology, crucial in identifying authentic pesticides and ensuring agricultural safety practices. Raman spectroscopy emerges as a powerful technique for detecting adulterants. Coupling the electrochemical techniques allows a more specific and selective detection and compound identification. In this study, we evaluate the efficacy of spectroelectrochemical measurements by coupling a potentiostat and Raman spectrograph to identify paraquat, a nonselective herbicide banned in several countries. Our findings demonstrate that applying -0.70 V during measurements yields highly selective Raman spectra, highlighting the primary vibrational bands of paraquat. Moreover, the selective Raman signal of paraquat was discernible in complex samples, including tap water, apple, and green cabbage, even in the presence of other pesticides such as diquat, acephate, and glyphosate. These results underscore the potential of this technique for reliable pesticide detection in diverse and complex matrices.

Bridging the Gap: Factors Influencing Farmers' Willingness and Behaviour in Biopesticide Application

Replacing chemical pesticides with biopesticides is crucial for ensuring high-quality agricultural products and advancing environmental sustainability. This study examines farmers’ willingness and behaviors regarding the use of biopesticides. A survey of 127 farmers in Junagadh district, Gujarat, was conducted, and a logistic model was employed to analyze factors influencing deviations between farmers’ willingness and their actual behaviors. The findings revealed that 37% of farmers showed a discrepancy between their willingness to use biopesticides and their actual application. Factors significantly impacting this deviation included price affordability, peer influence, education level, land size, emergency conditions, awareness of biopesticides, knowledge of the harmful effects of chemical pesticides, and awareness of agricultural product safety and quality. The primary reason for the gap between willingness and behavior is the farmers’ insufficient knowledge about biopesticides and the incomplete market structure for these products. To address this issue, it is recommended to improve farmers’ professional skills, raise awareness about green production methods, and accelerate the development of the biopesticides market to boost their adoption.

Microplastics originated from agricultural mulching films affect enchytraeid multigeneration reproduction and soil properties

Microplastics (MPs) are increasingly entering agricultural soils, often from the breakdown of agricultural plastics (e.g., mulching films). This study investigates the effects of realistic MPs from different mulching films: two conventional polyethylene (PE-1 and PE-2) and two biodegradable (starch-blended polybutylene adipate co-terephthalate; PBAT-BD-1 and PBAT-BD-2). MPs were mixed into Lufa 2.2 soil at a concentration range from 0.005 % to 5 % (w/w dry soil), wide enough to reflect both realistic environmental levels and “worst-case scenarios”. Effects on Enchytraeus crypticus reproduction over two generations and six important soil properties were studied. PBAT MPs notably reduced enchytraeid reproduction in the F0 generation, with a maximum decrease of 35.5 ± 9.6 % at 0.5 % concentration. F1 generation was unaffected by PBAT contamination. PE MPs had a more substantial reproductive impact, with up to a 55.3 ± 9.7 % decrease at 5 % PE-1 concentration compared to the control, showing a dose-related effect except for 1 %. Both MP types also significantly affected soil water holding capacity, pH, and total carbon. Other soil properties remained unaffected. Our results highlight the potential negative impacts of MPs originating from real agricultural plastics on soil health and raise concerns about the role of agricultural plastics in sustainable agriculture and food safety.

Nutrient strengthening and lead alleviation in Brassica Napus L. by foliar ZnO and TiO2-NPs modulating antioxidant system, improving photosynthetic efficiency and reducing lead uptake

With the anticipated foliar application of nanoparticles (NPs) as a potential strategy to improve crop production and ameliorate heavy metal toxicity, it is crucial to evaluate the role of NPs in improving the nutrient content of plants under Lead (Pb) stress for achieving higher agriculture productivity to ensure food security. Herein, Brassica napus L. grown under Pb contaminated soil (300 mg/kg) was sprayed with different rates (0, 25, 50, and 100 mg/L) of TiO2 and ZnO-NPs. The plants were evaluated for growth attributes, photosynthetic pigments, leaf exchange attributes, oxidant and antioxidant enzyme activities. The results revealed that 100 mg/L NPs foliar application significantly augmented plant growth, photosynthetic pigments, and leaf gas exchange attributes. Furthermore, 100 mg/L TiO2 and ZnO-NPs application showed a maximum increase in SPAD values (79.1%, 68.9%). NPs foliar application (100 mg/L TiO2 and ZnO-NPs) also substantially reduced malondialdehyde (44.3%, 38.3%), hydrogen peroxide (59.9%, 53.1%), electrolyte leakage (74.8%, 68.3%), and increased peroxidase (93.8%, 89.1%), catalase (91.3%, 84.1%), superoxide dismutase (81.8%, 73.5%) and ascorbate peroxidase (78.5%, 73.7%) thereby reducing Pb accumulation. NPs foliar application (100 mg/L) significantly reduced root Pb (45.7%, 42.3%) and shoot Pb (84.1%, 76.7%) concentration in TiO2 and ZnO-NPs respectively, as compared to control. Importantly, macro and micronutrient analysis showed that foliar application 100 mg/L TiO2 and ZnO-NPs increased shoot zinc (58.4%, 78.7%) iron (79.3%, 89.9%), manganese (62.8%, 68.6%), magnesium (72.1%, 93.7%), calcium (58.2%, 69.9%) and potassium (81.5%, 68.6%) when compared to control without NPs. The same trend was observed for root nutrient concentration. In conclusion, we found that the TiO2 and ZnO-NPs have the greatest efficiency at 100 mg/L concentration to alleviate Pb induced toxicity on growth, photosynthesis, and nutrient content of Brassica napus L. NPs foliar application is a promising strategy to ensure sustainable agriculture and food safety under metal contamination.

Unintended food safety impacts of agricultural circular economies, with case studies in arsenic and mycotoxins

For millennia, food systems worldwide have employed practices befitting a circular economy: recycling of agricultural and food waste or byproducts, environmentally sustainable production methods, and food preservation to reduce waste. Many modern-day agricultural practices may also contribute to a circular economy through the reuse of waste products and/or reducing agricultural inputs. There are, however, food safety impacts. This paper describes two sustainable agricultural practices that have unintended positive and negative impacts on food safety: alternative rice cultivation practices and no-till agriculture. We highlight how alternative rice cultivation practices have intended benefits of water conservation and economic savings, yet also unintended effects on food safety by reducing foodborne arsenic levels while increasing cadmium levels. No-till agriculture reduces soil erosion and repurposes crop residues, but can lead to increased foodborne mycotoxin levels. Trade-offs, future research, and policy recommendations are discussed as we explore the duality of sustainable agricultural practices and food safety.

The Use of Injury and Fatality Narratives to Convey Agricultural Safety and Health Messages and to Develop Effective Resources Through Collaborative, Multi-Disciplinary Approaches (Tell a Story, Save a Life)

ABSTRACT Objective Storytelling engages audiences, passes down traditions and history, educates, and helps people understand and interpret their environment. Many of those who work in agriculture have been part of the storytelling tradition since childhood. Research has demonstrated the emotional impact of personal stories and how prevention information is conveyed effectively “farmer to farmer” through this method of communication. Methods Since 2016, the Telling the Story Project has provided a space for those directly or indirectly involved in an agricultural incident to share their story and unique perspectives on how similar incidents can be avoided. Results This collaborative project, developed between the National Institute for Occupational Safety and Health (NIOSH) Agriculture Safety Centers, has resulted in 11 stories on a dedicated website, safety and health resources, and educational guides. The stories and educational guidelines have been marketed extensively through traditional and social media sources, employed in safety training, and embraced by educators in agricultural programs. The website has provided a national and international reach with more than 35,000 visits. Conclusion Qualitative thematic analysis of the stories provided data on the circumstances leading up to each incident, valuable information on how the storytellers interpreted the aftermath, and a novel perspective on how safety professionals can create messaging that will resonate with the farming community.

Learning from graduate students’ non-formal evaluation experiences in university-based centers

This paper examines graduate research assistants' informal applied learning experiences on the evaluation team at a university-based agricultural safety and health research center. The case study aims to identify the specific learning outcomes derived from the experience, as described by students, and the factors that facilitated them. The research team used a semi-structured focus group tool, and the focus group participants conducted their own analysis and interpretation of the data. An inductive qualitative analysis revealed that students had new perspectives on evaluation, greater evaluation knowledge, and comfort using evaluative tools. Students expressed that key factors like trust, respect, and reflective practice effectively fostered learning. These data were corroborated using deductive analysis using Fink’s Taxonomy of Significant Learning. Ultimately, the study supports the value of informal applied learning experiences for students, particularly in the field of evaluation, and describes a model of support to facilitate learning in various contexts.

From Farm to Fork: Enhancing Agricultural and Food Safety Monitoring with Laser-Engineered Graphene Sensors

In the critical fields of precision agriculture and food safety, the demand for accurate and sensitive monitoring tools for fertilizers, pesticides, and food-borne pathogens cannot be overstated. Our collaborative research with commercial entities seeks to overcome the challenges faced by current electrochemical ion-selective, enzymatic, and immunosensors, which often fall short in selectivity, stability, and sensitivity, particularly under field conditions. We showcase the tunable properties of Laser-Induced Graphene (LIG) – such as surface wettability, roughness/area, and electrical conductivity – and their instrumental role in enhancing the commercial viability of these sensor technologies.We demonstrate the conversion of hydrophilic Laser-Induced Graphene (LIG) to a near-superhydrophobic state using an innovative dual-laser process in ambient conditions. This method intricately sculpts the surface into micro and nanoscale structures reminiscent of a lotus leaf, resulting in nearly superhydrophobic characteristics. By modifying the laser's power, speed, and fluence, we can also fine-tune the electroactive surface area and electrical conductivity, significantly impacting sensor functionality. For solid contact ion-selective electrodes (SC-ISEs), enhancing the LIG surface with high hydrophobicity prevents water layer accumulation at the ion-selective membrane and electrode interface. This design expels water from within the membrane, fosters stronger membrane-electrode adhesion, and consequently, diminishes signal interference. Such improvements are instrumental in boosting the sensor's accuracy and extending its operational lifespan. In contrast, a hydrophilic LIG with a large surface area enhances catalytic efficiency and allows more biorecognition agents to adhere to its surface, thereby amplifying the sensitivity of enzymatic pesticide sensors. Lastly, a flat, hydrophilic LIG surface ensures an even distribution of antibodies, which enhances the performance of sensors detecting foodborne pathogens.These modifications to LIG and the resulting sensors have substantial commercial potential. We have developed ions sensors for nitrate, ammonium, potassium, calcium, and magnesium have demonstrated near-Nernstian sensitivities, extensive sensing ranges across four orders of magnitude, and the ability to detect concentrations as low as 1 ppm in soil and water samples. These sensors are currently being integrated into commercial soil moisture and temperature probes for monitoring in farm fields. The pesticide sensing capability of the sensor can reach an extremely low picomolar detect limit for organophosphates, the nanomolar regime for neonicotinoids, and micromolar regime for glyphosate in surface waters. These sensors are currently being interfaced with LIG-based mist/fog harvesting devices to monitor pesticide and spray drift in farm fields. Finally, the LIG-based Salmonella sensors are capable of monitoring bacteria such as Salmonella to about 10 CFU/mL in actual food matrices such as chicken broth without the need for sample preconcentration or costly lab analyses.This research forges innovative avenues in agriculture and food safety monitoring, laying the groundwork for mass production of efficient and economical sensors. We believe this technology will revolutionize field monitoring, significantly advancing sustainable agriculture and improving public health safety. Figure 1

Seasonal Patterns of Injury Characteristics Among Farmers and Ranchers in the U.S. Central States

ABSTRACT Objective In high-risk agricultural environments, tasks, weather, and work conditions vary throughout the year. Also, injuries peak during certain periods. The primary objective of this study was to examine operator- and farm-level characteristics as risk factors for injuries within each of the four seasons. The secondary objective was to examine seasonal differences in the incident location and primary cause of these injuries. Method We analyzed data from the 2018 and 2020 Farm and Ranch Health and Safety Surveys (FRHSS), conducted in seven U.S. states by the Central States Center for Agricultural Safety and Health (CS-CASH), which were collected using a stratified random sampling approach to ensure representativeness. The survey data were merged with operation-level data from the Farm Market iD database. We employed Generalized Estimating Equations (GEE) to examine the association of seasonal injuries with individual and operation-level characteristics. The chi-square test of independence was used to assess the association between injury incident location and season, as well as injury cause and season. Pairwise Z-tests of proportions were conducted to evaluate the differences in the proportions of injuries due to specific combinations of injury location and cause across each pair of seasons. Results Surveys conducted in 2018 and 2020 yielded a combined response rate of 15.9%, with 5,428 responses and 7,915 unique operators. Of these, 903 operators reported at least one injury during the past 12 months. Seasonally, most injuries occurred in spring (34.2%), followed by summer (24.7%). Male operators had higher injury odds in the spring (adjusted OR = 1.42) and summer (aOR = 2.41). Those managing both a farm and a ranch reported increased injury risks in winter (aOR = 1.73) and spring (aOR = 1.48). Operators in cow-calf operations faced higher springtime injury risks (aOR = 1.45). High stress and exhaustion were consistent risk factors across all seasons. The highest proportion of injury incidents occurred in the farmyard (43.6%), and livestock were the most common cause of injury (24.9%). Conclusion Results highlight the need for season-specific prevention and intervention strategies, considering farmers’ and ranchers’ risk characteristics, injury locations, and causes. These findings can inform targeted measures for high-risk populations at optimal times and locations.

AI-based automatic identification and processing techniques for agricultural safety information

In the context of globalization, agricultural safety is directly linked to food security and human health. Modern agriculture’s challenge is effectively monitoring and processing vast agricultural safety information in the digital era. This study aims to achieve the automatic identification and intelligent processing of agricultural safety information within a digital media environment by applying artificial intelligence (AI) technologies. Initially, the background of AI applications in agriculture is explored, followed by an analysis of the urgent need for automated processing of agricultural safety information and an overview of current research in this field. It is demonstrated that, despite progress, existing methods still lack in-depth feature extraction and real-time capabilities of the data processing systems. A method based on multi-level feature fusion for identifying agricultural product safety is proposed to address these limitations alongside a decentralized AI Internet of Things (IoT) system for processing agricultural safety information. The multi-level feature fusion method can extract and integrate essential details on agricultural products from different dimensions and levels, thus enhancing the identification accuracy. Meanwhile, the decentralized AIoT system strengthens the efficiency and reliability of data processing, ensuring timely responses to agricultural safety information. Through deep neural networks, efficient recognition and classification of agricultural product images were achieved, enabling the automatic identification of agricultural safety information in a digital media environment. Utilizing deep learning algorithms, the system could learn and understand the characteristics of different agricultural products and accurately identify potential safety issues, such as pests, diseases, or spoilage, providing timely monitoring and management for agricultural production. The innovation of this research lies in the comprehensive utilization of multi-level data features and advanced Internet of Things (IoT) technology, significantly improving the level of intelligence in agricultural safety supervision.

Safety assessment of agricultural products and the pesticide regulation trend in China

The sustainable development of Chinese agriculture needs to coordinate the quality and quantity of agricultural products. To verify whether government regulation can promote agricultural development by controlling pesticides, the indices of government regulation, quantity and quality of agricultural products, and pesticide use per area of cropland were calculated, and a comprehensive evaluation index and the coupling degree and coordination degree of agricultural products were analyzed by coupling function. The results showed that the coupling and coordination degree of the quality and quantity of agricultural products and the comprehensive index are improving. The regulation of pesticide use per area of cropland is a key mechanism in promoting the coordinated development of agricultural product safety. The regulation trend of agricultural development in China is to reduce pesticide usage appropriately and expand the production-possibility frontier of agricultural products.Graphical abstract

Fluorometric detection of copper and imidacloprid using nitrogen-doped graphitic carbon dots: A promising method for environmental monitoring.

Pesticides in environmental samples pose significant risks to ecosystems and human health since they require precise and efficient detection methods. Imidacloprid (IMI), a widely used neonicotinoid insecticide, exemplifies these hazards due to its potential toxicity. This study addresses the urgent need for improved monitoring of such contaminants by introducing a novel fluorometric method for detecting IMI using nitrogen-doped graphite carbon dots (N-GCDs). The sensor operates by quenching fluorescence through the interaction of Cu2+ ions with N-GCDs. Subsequently, IMI binds to the imidazole group, chelates with Cu2+, and restores the fluorescence of N-GCDs. This alternating fluorescence behavior allows for the accurate identification of both Cu2+ and IMI. The sensor exhibits linear detection ranges of 20-100 nM for Cu2+ and 10-140 μg/L for IMI, with detection limits of 18 nM and 1.2 μg/L, respectively. The high sensitivity of this sensor enables the detection of real-world samples, which underscores its potential for practical use in environmental monitoring and agricultural safety.

Analysis of Whole-Genome for Identification of Seven Penicillium Species with Significant Economic Value.

The Penicillium genus exhibits a broad global distribution and holds substantial economic value in sectors including agriculture, industry, and medicine. Particularly in agriculture, Penicillium species significantly impact plants, causing diseases and contamination that adversely affect crop yields and quality. Timely detection of Penicillium species is crucial for controlling disease and preventing mycotoxins from entering the food chain. To tackle this issue, we implement a novel species identification approach called Analysis of whole GEnome (AGE). Here, we initially applied bioinformatics analysis to construct specific target sequence libraries from the whole genomes of seven Penicillium species with significant economic impact: P. canescens, P. citrinum, P. oxalicum, P. polonicum, P. paneum, P. rubens, and P. roqueforti. We successfully identified seven Penicillium species using the target we screened combined with Sanger sequencing and CRISPR-Cas12a technologies. Notably, based on CRISPR-Cas12a technology, AGE can achieve rapid and accurate identification of genomic DNA samples at a concentration as low as 0.01 ng/µL within 30 min. This method features high sensitivity and portability, making it suitable for on-site detection. This robust molecular approach provides precise fungal species identification with broad implications for agricultural control, industrial production, clinical diagnostics, and food safety.

Pilot Evaluation of a Co-Designed Gamified Farm Injury Prevention Educational Resource for Adolescents

ABSTRACT Objectives Adolescents are at-risk of fatal and non-fatal injuries in the farm environment. School-based agricultural safety and farm injury prevention education is likely to be more effective when utilizing co-designed and gamification principles; however, this needs to be tested. This study examined data from a pilot evaluation of a co-designed farm injury prevention gamified educational resource for adolescents. Methods Online, anonymous surveys were conducted with students studying agriculture in regional Australia who had previously participated in the co-design process to develop “Calm Your Farm”. Three courses were developed (vehicles, workshop, and water safety) and before and after playing each of the courses for the first time, students completed survey questions regarding self-reported knowledge on the course topic, and assessment of content, design, ease of play, and how much they learned. Survey data were analyzed using descriptive statistics, chi square tests of association, and independent sample t tests. Results We analyzed 66 responses (66.7% male; 60.6% aged 13 years). Staged course release meant all respondents assessed the vehicle and workshop courses, while 58% assessed the water safety course. Vehicle and workshop courses were rated 7.64 out of a possible 10 (SD = 1.85) and 7.65 (SD = 1.78), respectively, for the information presented, slightly higher than water safety (7.47 [SD = 1.91]). Statistically significant improvements in self-reported knowledge post play were seen among boys for the water safety course (63% said knowledge improved; X2 = 4.98; p = .026) and 13-year-olds for vehicles (35%; X2 = 4.31; p = .038) and workshop safety (50%; X2 = 4.29; p = .038). Respondents indicated being more likely to replay the game at school (M = 6.62 [SD = 2.96]) than at home (M = 5.57 [SD = 3.07]). Of respondents, 61% (n = 40) agreed that “Calm Your Farm” taught them more about farm safety and was more fun than other farm safety education previously received. Tractor safety (62%), chemical safety (58%), and firearm safety (58%) were the most popular topics suggested to be added to the game. Conclusion The co-design and gamification approach taken with “Calm Your Farm” appeared to be successful in improving self-reported knowledge around farm injury prevention and was perceived by 62% of the respondents as being fun and educational. Future expansion should incorporate student suggested topics.

High cadmium-accumulating Salix ecotype shapes rhizosphere microbiome to facilitate cadmium extraction

Cadmium (Cd) contamination poses a significant threat to agricultural soils and food safety, necessitating effective remediation strategies. Salix species, with their high coverage and Cd accumulating capacity, hold promise for remediation efforts. The rhizosphere microbiome is crucial for enhancing Cd accumulating capacity for Salix. However, the mechanisms by how Salix interacts with its rhizosphere microbiome to enhance Cd extraction remains poorly understood. In this study, we compared the remediation performance of two Salix ecotypes: 51–3 (High Cd-accumulating Ecotype, HAE) and P646 (Low Cd-accumulating Ecotype, LAE). HAE exhibited notable advantages over LAE, with 10.80 % higher plant height, 43.80 % higher biomass, 20.26 % higher Cd accumulation in aboveground tissues (93.09 μg on average), and a superior Cd translocation factor (1.97 on average). Analysis of the rhizosphere bacterial community via 16S rRNA amplicon sequencing revealed that HAE harbored a more diverse bacterial community with a distinct composition compared to LAE. Indicator analysis identified 84 genera specifically enriched in HAE, predominantly belonging to Proteobacteria, Actinobacteria, and Firmicutes, including beneficial microbes such as Streptomyces, Bacillus, and Pseudomonas. Network analysis further elucidated three taxa groups specifically recruited by HAE, which were highly correlated with functional genes that associated with biosynthesis of secondary metabolites, glycan biosynthesis and metabolism, and metabolism of cofactors and vitamins. These functions contribute to enhancing plant growth, Cd uptake, and resistance to Cd in Salix. Overall, our findings highlight the importance of the rhizosphere microbiome in facilitating Cd extraction and provide insights into microbiome-based strategies for sustainable agricultural practices.

RT-DETR-Tomato: Tomato Target Detection Algorithm Based on Improved RT-DETR for Agricultural Safety Production

RT-DETR-Tomato: Tomato Target Detection Algorithm Based on Improved RT-DETR for Agricultural Safety Production

Ultralow Detection of Mancozeb Using Two-Dimensional Cobalt Telluride (CoTe2).

Pesticides are crucial in modern agriculture because they reduce pests and boost yield, but they also represent major risks to human health and the environment; therefore, it is important to monitor their presence in food. Reliable and precise detection techniques are possible ways to address this issue. In this work, we utilize atomically thin (two-dimensional) cobalt telluride (CoTe2) with a high surface area and charge as a template material to detect mancozeb using spectroscopic and electrochemical techniques. When mancozeb (MNZ) molecules interact with 2D CoTe2, spectroscopic analyses reveal distinctive spectral shifts that clarify the underlying chemical interactions and binding mechanisms. Furthermore, CoTe2's electroactive sites and their manipulation for improved sensitivity and selectivity toward certain MNZ molecules are investigated by electrochemical studies. The CoTe2/GCE electrode exhibits enhanced electrochemical activity toward the electrooxidation of MNZ. The developed sensing electrode shows a linear range from 0.184 mM to 18.48 μM and a limit of detection of about 0.18 μM. In addition, we employ density functional theory (DFT) first-principles calculations to validate the experimental findings and comprehend the mechanism behind the interaction between CoTe2 and MNZ molecules. The study highlights the effectiveness of 2D CoTe2 as a dual-mode sensing platform for qualitative and quantitative assessment of MNZ pollutants, demonstrated by the integration of electrochemistry and spectroscopy and the critical role that 2D CoTe2-based sensors can play in accurate and efficient pesticide detection, which is required for agricultural safety protocols and environmental monitoring.

Brand Image and Consumer Perceived Values on Purchase Intention of Organic Food: A Conceptual Study

Organic food is quickly developing in China as consumer wealth and consumption levels have grown in recent years; the Chinese government's "Healthy China Action (2019-2030)" promotes a balanced diet and works to raise the standard of agricultural output and food safety. Even though China has Asia's largest organic food market, organic food has a small market share and low consumer expenditure. As a result, decisive steps to boost the growth of China's organic food market are urgently needed. This study aims to explore the factors related to Chinese people’s purchase intention of organic food using the S-O-R model. Brand image and consumer perceived values are crucial because they influence customer purchase behavior. This study emphasizes brand image, perceived functional, emotional and social values on consumer purchase intention. Epistemic value and conditional value were excluded because they have detrimental impacts on consumer choice behavior. The contribution of this study is to enrich the existing literature by providing a deeper understanding of organic food consumer purchase intention in China through the application of brand image and consumer perceived values using the S-O-R model. It also provides Chinese policymakers and organic food suppliers with solutions to increase organic food sales to expand the Chinese organic food market.