Efficiency Of Agricultural Production Research Articles

Establishment of deep learning model for the growth of tea cutting seedlings based on hyperspectral imaging technique

The shoot and root growth not only serve as important indicators for measuring the quality of tea cutting seedlings, but also can provide scientific basis for agricultural production and fine seedling management. Currently, manual weighing is the main method used to measure shoot and root growth, which is both destructive and inefficient. The study proposes a method for monitoring the shoot and root growth in tea cutting seedlings using hyperspectral imaging. First, mature leaves and shoots spectra were extracted from tea cutting seedlings using Mask R-CNN (Epoch=20 and Learning-rate=0.001). The spectra were then preprocessed by MSC, S-G, 1-D filtering techniques, with feature bands screened by UVE (Optimal factor number=5), CARS (Monte Carlo sampling times=300), and SPA (Epoch=25). Finally, a CNN-GRU (Epoch=100 and Learning-rate=0.01) network was employed to predict shoot and root biomass, and compared with machine learning methods of SVR (Kernel function=Polynomial), RFR (Ntrees=200), and PLSR (Latent variable=16) and deep learning methods (Epoch=100 and Learning-rate=0.01) of CNN and LSTM. The results show that (i) Mask R-CNN can accurately extract the spectral of mature leaves (precision=97.8 %) and shoots (precision=91.5 %), (ii) The spectral feature bands of shoot (number=212) and root (number=105) biomass screened by UVE were more abundant than CARS and SPA, (iii) The UVE+CNN-GRU model (Rp2=0.90, RMSEP = 0.12, RPD=2.43) based on shoots spectrum provided the optimal estimation of shoot biomass. The SPA+LSTM model (Rp2 = 0.65, RMSEP = 0.05, RPD=1.67) based on the mature leaves spectrum provided the optimal estimation of root biomass. These findings demonstrate that hyperspectral imaging technology combined with deep learning algorithms can accurately monitor the growth of cutting seedlings quickly without causing damage. This not only provides a new data sources along with technical means for efficient screening excellent tea varieties, but also improves agricultural production efficiency and resource utilization.

From the Perspective of Digital Economy, the New Direction of Rural Development in Jiangxi

This study explores the impact of the digital economy on rural development and finds that the digital economy has become an important force in promoting my country's economic development. In Jiangxi, a major agricultural province, digital technology can help improve agricultural production efficiency, reduce production costs, promote agricultural productivity, optimize the agricultural industry chain, and increase farmers' income. However, Jiangxi's digital infrastructure construction is still insufficient, especially in remote and poor areas. Therefore, this study aims to provide targeted policy suggestions for policymakers, promote the transformation and upgrading of the rural economy, and provide a theoretical basis for realizing the rural revitalization strategy. In the context of the digital economy, Jiangxi Province actively promotes rural industrial innovation, financial popularization and digital governance improvements, laying a digital foundation for increasing the income of rural families and achieving the strategic goals of rural revitalization.

Towards Resilient and Sustainable Food Systems: Integrating Agricultural Production Efficiency and Food Security

This study explores the nexus between agricultural production efficiency and food security, globally and within Turkey. It analyzes agricultural data, emphasizing strategies to enhance productivity while ensuring access to nutritious food. Key areas include reducing food loss, promoting sustainable practices, ensuring safety, enhancing consumer awareness, and preserving resources. The article also outlines the six dimensions of food security availability, access, utilization, stability, agency, and sustainability and their policy implications. By integrating insights from diverse studies and emphasizing context-specific approaches, it advocates for holistic strategies tailored to each agricultural landscape’s unique challenges. Ultimately, the pursuit of agricultural efficiency and food security is positioned as both a moral imperative and an economic necessity. Through research, policy reforms, and stakeholder collaboration, nations can work towards resilient and sustainable food systems for present and future generations. In the study, it was determined that labor productivity was not taken into account sufficiently and the data was insufficient to measure labor and labor productivity in agricultural production. The study aims to contribute to strategic decision-making and local-global policies to increase agricultural and resource use efficiency.

Research Progress in Facility Agriculture and Lighting by Bibliometric Analysis Based on CiteSpace

Given the pressures of internation-al market competition, the dual constraints of domestic resources and the environment, and the uncertainties posed by climate change, bolstering agricultural infra-structure construction is a realistic demand and a crucial approach for implementing emerging grain security strat-egies, particularly in developing countries. Facility agriculture is characterized as a modern agricultural production mode that improves or creates favorable environmental conditions within a specific locality. With the rapid expansion of large-scale facility agriculture, there has been an increased demand for various types of energy, including electricity, gas, cold, and heat. Agricultural lighting equipment used in facility agriculture is a modern agricultural technique that applies engineering technology to regulate light supplementation in the production process. Facility lighting offers several advantages over traditional methods, such as higher photovoltaic conversion efficiency, adjustable spectrum, high photosynthetic efficiency, energy efficiency, environmental friendliness, long lifespan, monochromatic light, cold light source, and compact size. Promoting national food security, carbon neutrality, returning farmland to forests, and implementing low-carbon green agricultural policies all contribute to the favorable use of facility agriculture lighting. This study aims to provide a systematic summary of the relevant research conducted in the past decade using Citespace software. The advantage of facility agriculture for carbon sequestration capacity can effectively reduce net carbon emissions from facility agricultural production activities. In addition, the combination of agriculture and the Internet of Things can effectively improve agricultural production efficiency and economic returns. Combining artificial intelligence and other technologies with facility agriculture engineering, based on multi-source data fusion, intelligent early warning for facility agriculture energy internet can be used to prevent agricultural meteorological disasters. More importantly, it helps maintain global food security, eliminate hunger, and reduce economic inequality. The findings of this study will contribute to a deeper understanding of agricultural lighting equipment, serving as a new theoretical foundation for achieving agricultural emission reduction targets and promoting agricultural technical cooperation.

Moderate nitrogen application facilitates Bt cotton growth and suppresses population expansion of aphids (Aphis gossypii) by altering plant physiological characteristics.

Excessive application of nitrogen fertilizer in cotton field causes soil and water pollution as well as significant increase of aphid population. Reasonable fertilization is an important approach to improve agricultural production efficiency and reduce agriculture-derived pollutions. This study was aimed to explore the effects of nitrogen fertilizer on the Bt cotton physiological characteristics and the growth and development of A. gossypii, a sap-sucking cotton pest. Five different levels of Ca(NO3)2 (0.0 g/kg, 0.3 g/kg, 0.9 g/kg, 2.7 g/kg and 8.1 g/kg) were applied into vermiculite as nitrogen fertilizer in order to explore the effects of nitrogen fertilizer on the growth and development of Bt cotton and aphids. The results showed that the medium level of nitrogen fertilizer (0.9 g/kg) effectively facilitated the growth of Bt cotton plant and suppressed the population expansion of aphids, whereas high and extremely high nitrogen application (2.7 and 8.1 g/kg) significantly increased the population size of aphids. Both high and low nitrogen application benefited aphid growth in multiple aspects such as prolonging nymph period and adult lifespan, enhancing fecundity, and improving adult survival rate by elevating soluble sugar content in host Bt cotton plants. Cotton leaf Bt toxin content in medium nitrogen group (0.9 g/kg) was significantly higher than that in high (2.7 and 8.1 g/kg) and low (0.3 g/kg) nitrogen groups, but Bt toxin content in aphids was very low in all the nitrogen treatment groups, suggesting that medium level (0.9 g/kg) might be the optimal nitrogen fertilizer treatment level for promoting cotton seedling growth and inhibiting aphids. Overall, this study provides insight into trophic interaction among nitrogen fertilizer levels, Bt cotton, and cotton aphid, and reveals the multiple effects of nitrogen fertilizer levels on growth and development of cotton and aphids. Our findings will contribute to the optimization of the integrated management of Bt cotton and cotton aphids under nitrogen fertilization.

Assessing the Drivers of Sustained Agricultural Economic Development in China: Agricultural Productivity and Poverty Reduction Efficiency

Poverty eradication is a crucial element of SDG 1. Whether the financial resources invested by the Government provide a critical impetus for deeply impoverished rural areas needs to be studied by quantitative analysis. Therefore, this study presents a theoretical analytical framework for agricultural production–government poverty reduction. It divides the poverty reduction process into two stages, agricultural production and poverty reduction, from the perspective of sustainable agricultural development. The comprehensive measurement and spatio-temporal evolution analysis of China’s agricultural production and poverty reduction efficiency are conducted using a novel dynamic two-stage DEA model, which incorporates non-expected factors. The study found that (1) China’s agricultural production and poverty reduction efficiency exhibit overall poor performance, characterized by two poles of differentiation. (2) The agricultural production efficiency score is higher in the northern region than in the southern region, while the poverty reduction efficiency score is higher in the eastern region compared to the western region. (3) The coupling and coordination between China’s production efficiency and poverty reduction efficiency are inadequate.

Changing agricultural practices as a result of variable water resource availability in a hilly area of An Giang province, Vietnam

Abstract Located in the Southwest of the Mekong Delta in Vietnam, An Giang province is an important center of agricultural production, especially rice cultivation. Climate change impacts are one of several man-made factors affecting water resource availability for agriculture in the province. It is recognized that new solutions are crucial to adapt to the present and future conditions of a scarcer water supply. This paper explores climate factors affecting water resource availability in agriculture and some recent adaptations being adopted by farmers in one district of An Giang province. Hydro-meteorological data was collected together with in-depth interviews as a tool to point to proximate changes in water status and availability and to evaluate local inhabitants’ awareness of climate risks and adaptive strategies. The results noted that climate factors (temperature, humidity, annual rainfall) have altered over time, causing decreased availability of water supplies for agriculture. Recognizing this situation, both structural adaptation and non-structural solutions may occur simultaneously to maintain agricultural production efficiency. The types of crops, tolerant varieties, and irrigation projects suitable for various geographical areas were considered for more adaptive agriculture production locally. To address some of the problems that farmers face, water-saving technologies are an essential part of a range of potential solutions to maintain agricultural production and protect the environment in the future.

Study on Accelerating the Development of Agricultural Modernization by Fiscal Policies in the Context of "14th Five-Year Plan"

This paper analyzes the background of the study of agricultural modernization in Sichuan Province from the aspects of national policy background, and conducts research on agricultural modernization in Sichuan Province from the connotation and characteristics of agricultural modernization, analysis of the current situation, analysis of the influencing factors, and the choice of path. Through the study, in order to hope can provide help to promote the process of agricultural modernization in Sichuan Province. Under the background of the national vigorously promote the modernization of agriculture, in-depth study of the background and path selection of agricultural modernization in Sichuan Province, for improving the efficiency of agricultural production and the quality of agricultural products in Sichuan Province, to protect the national food security and to further promote the perfect solution of the three rural issues and economic development has its practical significance.

The impact of green and low carbon agricultural production on farmers’ income in minority areas: a case study of Y Town, Zhijin County, Guizhou Province

Developing green and low-carbon agriculture is an important and effective way to promote farmers’ income growth. Given the country’s “dual carbon” goal, the study of the impact of green and low-carbon agriculture on the income of farmers in ethnic minority areas is crucial for China to achieve the goals of socialist modernization and common prosperity. Taking Y Town, Zhijin County, Guizhou Province as an example, this paper uses the OLS regression method to empirically study the impact of green and low-carbon agricultural production methods on the income of farmers in ethnic minority mountainous agricultural areas based on the field survey data of 881 farmers. The regression results indicate that there is a positive correlation between green and low-carbon agricultural production and the household income levels of farmers; adopting green and low-carbon agricultural production technologies can effectively promote the growth of farmers’ household income. In addition, education level, health status, and the new rural social pension insurance have all had a significant effect on the income of rural households, however, due to the difficulty in establishing trust relationships, agricultural service outsourcing has reduced the household income level of farmers. As an example, the land transfer behavior in Y Town has no significant effect on increasing farmers’ incomes. Finally, it is recommended to increase fiscal and financial support as well as effectively enhancing farmers’ policy awareness and perception of green and low-carbon agricultural production technologies by improving farmers’ general trust and institutional trust by strengthening farmers’ agricultural education and skills training while cultivating technology-based farming. At the same time, it is necessary to break the geographical restrictions on land transfer scale and achieve moderate-scale land management while promoting the use and adoption of green and low-carbon agricultural production technologies, thereby improving agricultural production efficiency and product quality, and increasing the sustainable growth of farmers’ income. The main contribution of this study is to expand the research scope of green and low-carbon agriculture to ethnic minorities and mountainous agricultural areas.

Measurement of Agricultural Eco-Efficiency and Analysis of Its Influencing Factors: Insights from 44 Agricultural Counties in Liaoning Province

Agricultural eco-efficiency (AEE) considers economic and environmental benefits and is a key indicator of green agricultural development. To achieve the multiple goals of improving agricultural production efficiency, reducing agricultural environmental damage, and reducing the input of agricultural resources, this study enriches the case study of agricultural production performance evaluation at the county level by measuring the AEE of 44 agricultural counties in Liaoning Province based on panel data and a super-efficient slacks-based measure model including undesired outputs. A two-way fixed-effects model was used to analyze the impact of agricultural development, macro-environment, and policy support on AEE. We found that the average AEE of the counties in Liaoning Province in 2014, 2016, 2018, and 2020 was 0.716, 0.735, 0.749, and 0.813, respectively, indicating a cumulative improvement rate of 13.55%. The average AEE levels gradually improved during the study period. Notably, the development of AEE among the counties was uneven. AEE was distributed in a “block-like” manner, and its local correlation presents a phenomenon of “small agglomeration and large dispersion”. In addition, the level of the agricultural economy, industrialization, and urbanization significantly promoted the improvement of AEE, and the promoting effects varied between different income levels and regions. Therefore, Liaoning Province needs to improve the AEE of each county according to local conditions and narrow the differences in AEE between counties. To continuously improve the level of rural economic development, lead the development of agricultural modernization with new urbanization, and comprehensively improve the overall AEE of counties. The research results are of guiding significance for deepening the study of AEE and can provide decision-making support for optimizing the mode of agricultural production and promoting the green development of regional agriculture.

A Two-Stage Approach to the Study of Potato Disease Severity Classification

Early blight and late blight are two of the most prevalent and severe diseases affecting potato crops. Efficient and accurate grading of their severity is crucial for effective disease management. However, existing grading methods are limited to assessing the severity of each disease independently, often resulting in low recognition accuracy and slow grading processes. To address these challenges, this study proposes a novel two-stage approach for the rapid severity grading of both early blight and late blight in potato plants. In this research, two lightweight models were developed: Coformer and SegCoformer. In the initial stage, Coformer efficiently categorizes potato leaves into three classes: those afflicted by early blight, those afflicted by late blight, and healthy leaves. In the subsequent stage, SegCoformer accurately segments leaves, lesions, and backgrounds within the images obtained from the first stage. Furthermore, it assigns severity labels to the identified leaf lesions. To validate the accuracy and processing speed of the proposed methods, we conduct experimental comparisons. The experimental results indicate that Coformer achieves a classification accuracy as high as 97.86%, while SegCoformer achieves an mIoU of 88.50% for semantic segmentation. The combined accuracy of this method reaches 84%, outperforming the Sit + Unet_V accuracy by 1%. Notably, this approach achieves heightened accuracy while maintaining a faster processing speed, completing image processing in just 258.26 ms. This research methodology effectively enhances agricultural production efficiency.

Mechanism and Measurement of the Effects of Industrial Agglomeration on Agricultural Economic Resilience

This study investigates the potential of agricultural industrial agglomeration to bolster agricultural economic resilience and identifies the underlying pathways. We developed an analytical framework for agricultural economics that integrates the concept of “resilience”. This framework facilitates an examination of the influence of agricultural industrial agglomeration on agricultural economic resilience, focusing on two key aspects: enhancement of income and reduction of costs. Utilizing panel data from 30 provincial-level regions in China covering the period from 2006 to 2021, this research empirically assesses the impact, underlying mechanisms, and regional variations of agricultural industrial agglomeration on agricultural economic resilience. The findings reveal that agricultural industrial agglomeration significantly boosts agricultural economic resilience. This positive influence manifests through two primary channels: firstly, “agricultural industrial agglomeration → enhancement of socialized services → agricultural economic resilience” and secondly, “agricultural industrial agglomeration → improvement of agricultural production efficiency → agricultural economic resilience”. The contribution of agricultural industrial agglomeration to agricultural economic resilience is particularly pronounced in major grain-producing regions, notably enhancing capabilities for reconstruction and reinvention, as well as adjustment and adaptation. The study concludes with recommendations aimed at strengthening agricultural economic resilience. These recommendations emphasize the critical role of agricultural industrial agglomeration in fostering agricultural economic resilience, its contribution to the growth of rural economies and the enhancement of socialized services, and the need to consider regional disparities in the process of developing agricultural economic resilience.

Environmental viability and economic sustainability of tillage for wheat: Evidence from Croatia

A multidisciplinary field experiment was performed during three seasons for winter wheat in Croatia. The intention of this study was to examine and diagnose the effect of Tillage Systems (TS) on soil chemical properties (soil acidity, phosphorus, potassium, and organic matter content) as well as the outcome of economic indicators such as Gross Margin (GM), Rate of Profitability (ROP), cost-effectiveness (E) and productivity (P). TS were CT - plowing up to 30 cm depth; DT - disking up to 8-12 cm depth; LT - loosening up to 35 cm depth; NT - no-tillage. The experimental design was a randomised block design in four repetitions, where the basic TS plot was 540 m2. Soil sampling for 0-30 cm soil layer was done prior to setting up the experiment and after three seasons, a total of 320 soil samples and chemical analyses were performed according to standard pedological procedures. Economic indicators are calculated using economic equations and standards and statistical analysis was performed with SAS 9.3 and Microsoft Excel 2016. Generated results point that on systems with shallower tillage or no- tillage expressed accumulation of phosphorus and potassium appeared with distinct vertical stratification. At the same time, these TS ensured soil organic matter and soil fertility preservation. From the aspect of economic calculations, LT assigned the prime economic results. The ROP was in order CT (32.67%) < DT (37.39%) < LT (40.31%) < NT (42.29%). The same order was established for E, namely, CT (1.33) < DT (1.37%) < LT (1.40%) < NT (1.42%). NT established the best P because of the lowest costs of production, but due to significantly lower yield, NT has limited adoption in practice. The conservable and viable agricultural production by intermediation of reduced soil tillage systems has its capabilities and potency, firstly ecological, through providing soil degradation, and then economical by potentiating economic sustainability and financial efficiency of agricultural production.

A Three-Year Study on the Nutritional Composition and Occurrence of Mycotoxins of Corn Varieties with Different Transgenic Events Focusing on Poultry Nutrition.

Corn is one of the most produced cereals in the world and plays a major role in poultry nutrition. As there is limited scientific information regarding the impact of transgenic technology on the quality and nutrient composition of the grains, this study investigated the effect of three major transgenic corn varieties-VT PRO3®, PowerCore® ULTRA, and Agrisure® Viptera 3-on the field traits, nutrient composition, and mycotoxin contamination of corn grains cultivated in southern Brazil during three consecutive harvests. VT PRO3®, while demonstrating superior crop yield, showed susceptibility to mycotoxins, particularly fumonisins. In contrast, PowerCore® ULTRA, with the lowest yield, consistently exhibited lower levels of fumonisins. VT PRO3® had higher AMEn than the other varieties, while PowerCore® ULTRA had the highest total and digestible amino acid contents over the three years. The study's comprehensive analysis reveals the distinct impact of transgenic corn technologies on both productivity and nutritional levels. Balancing the crops yield, mycotoxin resistance, and nutritional content of corn is crucial to meet the demands of the poultry feed industry. Such insights are essential for decision-making, ensuring sustainability and efficiency in agricultural production as well as meeting the demands of the poultry industry.

Spatial-temporal characteristics and driving factors' contribution and evolution of agricultural non-CO2 greenhouse gas emissions in China: 1995-2021.

Comprehending the spatial-temporal characteristics, contributions, and evolution of driving factors in agricultural non-CO2 greenhouse gas (GHG) emissions at a macro level is pivotal in pursuing temperature control objectives and achieving China's strategic goals related to carbon peak and carbon neutrality. This study employs the Intergovernmental Panel on Climate Change (IPCC) carbon emissions coefficient method to comprehensively evaluate agricultural non-CO2 GHG emissions at the provincial level. Subsequently, the contributions and spatial-temporal evolution of six driving factors derived from the Kaya identity were quantitatively explored using the Logarithmic Mean Divisia Index (LMDI) and Geographical and Temporal Weighted Regression (GTWR) methods. The results revealed that the distribution of agricultural non-CO2 GHG emissions is shifting from the central provinces to the northwest regions. Moreover, the dominant driving factors of agricultural non-CO2 GHG emissions were primarily economic factor (EDL) with positive impact (cumulative promotion is 2939.61 million metric tons (Mt)), alongside agricultural production efficiency factor (EI) with negative impact (cumulative reduction is 2208.98 Mt). Influence of EDL diminished in the eastern coastal regions but significantly impacted underdeveloped regions such as the northwest and southwest. In the eastern coastal regions, EI gradually became the absolute dominant driver, demonstrating a rapid reduction effect. Additionally, a declining birth rate and rural-to-urban population migration have significantly amplified the driving effects of the population factor (RP) at a national scale. These findings, in conjunction with the disparities in geographic and socioeconomic development among provinces, can serve as a guiding framework for the development of a region-specific roadmap aimed at reducing agricultural non-CO2 GHG emissions.

Microalgae cultivation using ammonia and carbon dioxide concentrations typical of pig barns

ABSTRACT While global population growth drives increased production efficiency in animal agriculture, there is a growing demand for environmentally friendly practices, particularly in reducing air pollutant emissions from concentrated animal feeding operations. This study explores the potential of cultivating microalgae in photobioreactors (PBRs) as an eco-friendly and cost-effective approach to mitigate NH3 and CO2 emissions from pig barns. Unlike traditional physicochemical mitigation systems, microalgae offer a renewable solution by converting pollutants into valuable biomass. The research focused on Scenedesmus dimorphus growth under typical NH3 and CO2 concentrations found in the indoor air of pig barns. Four NH3 (0, 12, 25, and 50 ppm) and four CO2 concentrations (350, 1200, 2350, and 3500 ppm) were tested using photobioreactors. Results showed a maximum specific growth rate of 0.83 d−1 with 12 ppm NH3 and 3500 ppm CO2. The dry biomass concentration was significantly higher (1.16 ± 0.08 g L−1; p < 0.01) at 25 ppm NH3 and 2350 ppm CO2 than other test conditions. S. dimorphus demonstrated the peak NH3 and CO2 fixation rates (23.8 ± 2.26 mg NH3 L−1 d−1 and 432.24 ± 41.09 mg CO2 L−1 d−1) at 25 ppm NH3 and 2350 ppm CO2. These findings support the feasibility of using algae to effectively remove air pollutants in pig barns, thereby improving indoor air quality.

Research on the impact of water-saving technologies on the agricultural production efficiency of high-quality farmers------taking Jiangxi province and Guangdong province in China as examples

Research on the impact of water-saving technologies on the agricultural production efficiency of high-quality farmers------taking Jiangxi province and Guangdong province in China as examples

The inappropriate application of imidacloprid destroys the ability of predatory natural enemies to control pests in the food chain: A case study of the feeding behavior of Orius similis on Frankliniella occidentalis

Insecticides are an indispensable and important tool for agricultural production. However, the inappropriate application of insecticides can cause damage to the food chain and ecosystem. Orius similis is an important predatory and natural enemy of Frankliniella occidentalis. Imidacloprid is widely used to control pests, but will inevitably exert adverse effects on O. similis. In order to determine the effect of different imidacloprid treatments on the ability of O. similis to prey on the 2nd-instar nymphs of F. occidentalis, we determined the toxicity and predation of imidacloprid on different stages of O. similis under contact and ingestion treatments. In addition, we used the Holling disc equation to evaluate the ability of O. similis to search and exhibit predatory activity following contact and ingestion treatments. Analysis showed that the highest LC10 and LC20 values for imidacloprid contact and ingestion toxicity treatment were 17.06 mg/L and 23.74 mg/L, respectively. Both imidacloprid treatments led toa reduction in the predatory of O. similis on prey. The functional responses of the 3rd to 5th instar nymphs, along with female and male O. similis adults to the 2nd-instar nymphs of F. occidentalis were consistent with the Holling type II response following contact and ingestion with imidacloprid. However, following imidacloprid treatment, the handing time (Th) of O. similis with single F. occidentalis was prolonged and the instantaneous attack rate (a) was reduced after imidacloprid treatment. The predatory capacity (a/Th) of female O. similis adults when treated with the LC10 concentration of imidacloprid by ingestion was 52.85; this was lower than that of the LC10 concentration of imidacloprid in the contact treatment (57.67). The extent of predation of O. similis on the 2nd-instar nymphs of F. occidentalis was positively correlated with prey density, although the search effect was negatively correlated with prey density. The most extensive search effect was exhibited by adult O. similis females. Simulations with the Hessell-Varley interference model showed that an increase in the number of O. similis would reduce search efficiency regardless of whether they were treated with imidacloprid or not. Thus, O. similis, especially female adults, exhibited strong potential for controlling the 2nd-instar nymphs of F. occidentalis. The toxicity of ingestion following treatment with the same concentration of imidacloprid in O. similis was greater than that of contact treatment. When using O. similis to control F. occidentalis in the field, we should increase the number of female adults released, and prolong the interval between imidacloprid treatment and O. similis exposure. This strategy will improve the control ability of O. similis, coordinate both chemical and biological control, reduce the impact of pesticides on the environment, and improve the efficiency of agricultural production.

인공지능 기반 농작물 성숙도 체크와 농산물 시장가격 변동을 고려한 출하시기 결정시스템 연구

This study aims to develop an integrated agricultural distribution network management system to improve the quality, profit, and decision-making efficiency of agricultural products. We adopt two key techniques: crop maturity detection based on the YOLOX target detection algorithm and market price prediction based on the Prophet model. By training the target detection model, it was possible to accurately identify crops of various maturity stages, thereby optimizing the shipment timing. At the same time, by collecting historical market price data and predicting prices using the Prophet model, we provided reliable price trend information to shipping decision makers. According to the results of the study, it was found that the performance of the model considering the holiday factor was significantly superior to that of the model that did not, proving that the effect of the holiday on the price was strong. The system provides strong tools and decision support to farmers and agricultural distribution managers, helping them make smart decisions during various seasons and holidays. In addition, it is possible to optimize the distribution network of agricultural products and improve the quality and profit of agricultural products.

Global food loss and waste estimates show increasing nutritional and environmental pressures.

Accurate global food losses and waste (FLW) quantification remains challenging owing to limited harmonized global estimates, a lack of comprehensive quantification approaches and an absence of frameworks for addressing FLW challenges. Here we compile a country-level database that assesses FLW across global value chains and quantifies the nutritional and environmental impact of FLW for 121 countries and 20 composite regions. Between 2004 and 2014, FLW increased by a quarter, especially in sub-Saharan Africa and Southeast Asia, where increasing nutritional losses of ~550 cal per capita per day impact food security. Growing food imports in high-income countries and fast-growing economies worsened FLW and related environmental footprints in exporting low-income regions. Reducing overconsumption and FLW in high-income countries may have positive effects in middle- and low-income countries, where food exports largely drive farm-level losses. Policies should focus on promoting the profitable reuse of unavoidable FLW while enhancing agricultural production efficiency to improve water use and nutritional security.