Quality Of Agricultural Products Research Articles

Research on the Management Model and Performance Evaluation of Guangxi ASEAN Cross border Agricultural Product Supply Chain

With the proposal of the "Belt and Road Initiative", China's cross-border trade has been further developed. In order to comply with the development trend of "double cycle", the trade of agricultural products can make full use of "two resources and two markets" both at home and abroad. However, the supply chain of cross-border trade of agricultural products involves many links and has a wide range of chain coverage, showing relatively complex characteristics. In order to realize the sustainable development of cross-border agricultural products trade, an empirical study on the management model and performance evaluation of Guangxi-ASEAN cross-border agricultural products supply chain was carried out. On the basis of defining the concept of Guangxi-ASEAN cross-border agricultural product supply chain, this study first analyzed the management mode of Guangxi-ASEAN cross-border agricultural product supply chain, designed the performance evaluation model of Guangxi-ASEAN cross-border agricultural product supply chain according to the importance of cross-border logistics and demand of agricultural products, and then set evaluation indicators on the basis of target level and criterion level through the selection rules of evaluation indicators. Principal component analysis was used to evaluate the scores of each index, so as to obtain the evaluation level of Guangxi-ASEAN cross-border agricultural supply chain performance, and complete the empirical analysis of performance evaluation. The empirical analysis results are as follows: The logistics system of Guangxi-ASEAN cross-border trade is gradually improved, the delivery timeliness and accuracy of cross-border trade are constantly increasing, the quality of cross-border agricultural products is gradually enhanced, and the information exchange of cross-border trade is becoming more transparent. This improves the satisfaction of consumers, increases the profits of enterprises, reduces the customs clearance time and finished products of agricultural trade, and strengthens the close trade cooperation between Guangxi and ASEAN countries.

Research on the Network Equilibrium of Fresh Agricultural Product Supply Chain with Third Party Logistics Participation in Decision Making

Introducing Third-party logistics into the supply chain of fresh agricultural products can reduce the logistics cost of the supply chain and improve the freshness and quality of fresh agricultural products. Taking the fresh agricultural product supply chain network, which includes three decision-making entities: fresh agricultural product suppliers, 3PL service providers, and retailers, as the research object, a fresh agricultural product supply chain network equilibrium model is constructed using variational inequality theory. The impact of 3PL service providers' logistics service level on their equilibrium transaction volume and overall profit is studied. The research results show that when Third-party logistics is involved in the supply chain of fresh agricultural products, considering the logistics service level of 3PL service providers, with the improvement of service level, the overall profit of the supply chain of fresh agricultural products increases. It is a beneficial attempt to realize the profit of the supply chain of fresh agricultural products to improve the freshness and quality of fresh agricultural products through Third-party logistics; When the logistics service level rises to a certain level, and the service level continues to improve, the overall profit growth of the supply chain decreases. It is necessary to improve the impact of logistics service level on the freshness and quality of fresh agricultural products through other forms.

Sustainability and Quality: Analysis of the Benefits of Bee Pollination in Coffee

Theoretical benchmark: Coffee farming has a productive chain of economic, cultural, historical and social relevance for Brazil. Assisted pollination carried out by bees becomes an alternative in increasing productivity and coffee quality, in addition to contributing to biodiversity. In this context, this work was developed with the objective of analyzing the benefits of pollination by bees in coffee production, verifying the effects on quality by comparing physicochemical parameters of the grains. Method: Coffee samples were collected from two areas from pollinated and non-pollinated coffee trees, grouped together forming a sample for each treatment and subsequently dried in a suspended terrace until reaching 12% humidity. For physicochemical characterization of the grains, analyzes of Soluble solids, thousand grains mass, Titratable acidity, pH, Electrical conductivity, and Coloring were performed. Results and conclusion: In the pollinated area, the values of Soluble solids were higher with 31.49°Brix in raw grains and 23.20°Brix in cherry grains and in the Mass of a thousand grains with 113.35g in the raw grain. In the electrical conductivity, titratable acidity and pH parameters, lower values were observed in the pollinated area in the raw grains. For Coloring, better results were observed in coordinates L: 30.98; a: 0.44; b:11.39 in coffee from an area of assisted pollination. The obtained results were significant in pollinated area in the parameters Soluble solids in raw beans and cherry and in Mass of a thousand beans and Color (coordinate L) only in raw beans, when compared to non-pollinated coffee. Regarding titratable Acidity and Electrical conductivity in pollinated area, better analytical results were observed, which are more representative in terms of grain quality. Research implications: Generate scientific data and a reflection on the importance of pollination in sustainable production and its implications not only for agriculture and society, but for the entire balance of ecosystems. Originality and value: Research carried out at Fazenda Nove de Julho located in the municipality of Altinópolis, SP to verify the contribution of stingless bees to coffee production and the valorization of these pollinators as a decisive factor in increasing the productivity and quality of Brazilian agricultural production.

Detection of early bruises on apples using near‐infrared camera imaging technology combined with adaptive threshold segmentation algorithm

AbstractApples are highly susceptible to bruising during picking, packing, and transportation, and early detection of apple bruises allows timely screening and treatment to reduce food safety risks. However, early bruises on apples, especially bruises of 30 min or less, with similar appearance to sound tissue, making manual sorting difficult. To address this problem, a near‐infrared (NIR) camera imaging technology combined with adaptive threshold segmentation algorithm for early apple bruise detection is proposed in this article. First, a NIR camera imaging system is built to acquire full‐band images of fruit face, fruit stem face and calyx face of sound apples and apples with single bruise and multiple bruises at 30 min of occurrence. Then, an adaptive threshold segmentation algorithm is proposed and an image processing algorithm, which includes high‐pass filtering, feature extraction, adaptive threshold segmentation and Hough circle detection, is developed and applied to full‐band images in response to the interference of apple stem and calyx on early bruising detection in this article. The results show that the proposed algorithm has an accuracy of 95.56% for the detection of sound apple samples and an F1‐score of 94.70% for the detection of early bruised samples, which is better than the commonly used image segmentation algorithms such as Otsu and fixed thresholding. This study shows that the combination of NIR camera imaging and the adaptive threshold segmentation algorithm proposed in this article can effectively detect early bruises on apples, providing a new idea for rapid and nondestructive detection of agricultural product quality.Practical applicationsDetecting early bruises on apples can achieve effective monitoring and control of apple supply chain, and guarantee the quality and safety of agricultural products. Most studies are based on conventional machine vision with RGB camera or hyperspectral imaging technology, while conventional machine vision based on RGB camera is difficult to detect apple early bruises that are not visible to the naked eye, and hyperspectral imaging has a large amount of data and redundant image data among wavelengths. Compared with previous studies, apple early bruise detection method proposed in this article combining NIR camera imaging technology and adaptive threshold segmentation algorithm can avoid the interference of bright spots, fruit stem and calyx on bruise segmentation while capturing a single channel image, providing a new method for accurate and rapid detection of early bruises on apples.

Content of proline and heavy metals in beekeeping prod ucts of different agro-ecological conditions of Ukraine

The production of beekeeping plays a crucial role in the population's nutrition. Bees yield valuable dietary products, such as honey, and provide raw materials for the food industry, such as beeswax. In addition to these primary products, bees produce royal jelly, flower pollen, propolis, homogenate of drone larvae, and bee venom. In regions with advanced agriculture, bees are utilized to pollinate entomophilous crops. Bee pollination enhances plants' similarity and yield, improving agricultural product quality. Honey-producing bees consume pollen, with flower pollen from nectariferous plants serving as the raw material, followed by bee bread, which is brought into the hive. However, the agroclimatic conditions in various regions of Ukraine only sometimes provide sufficient diversity of nectariferous plants to adequately meet the protein and mineral nutrition needs of bees. Minerals in animal organisms perform crucial functions, providing structural integrity to the skeleton and constituting essential components of organic compounds, vitamins, and enzymatic systems. In contemporary animal production, heavy metals threaten the health of both humans and animals. According to established norms, many of these metals are vital elements that must be included in the animal diet. Inadequate or excessive levels of these elements in the animal body can lead to the inactivation of enzymatic systems, impaired reproduction, decreased productivity, and reduced product quality. Heavy metals, especially mercury, lead, chromium, and nickel, are more dangerous toxins in living organisms at elevated concentrations. The chemical composition of living organisms and their impact on geochemical processes varies. To ensure normal vitality and the production of high-quality animal products, animals must be provided with a balanced diet and an optimal content of minerals that contribute to increased productivity and production efficiency. Therefore, studying the content of heavy metals such as iron, copper, zinc, lead, cobalt, and cadmium in honey obtained under different agroecological conditions in Ukraine is of significant economic importance. The research results indicate that the content of heavy metals in honey from the Western region, except iron and zinc, was higher than in the Southern region. Specifically, for copper, this advantage amounted to 86.725 mg/kg or 1.4 times, for lead – 50.203 mg/kg or 2.8 times, for cobalt – 57.865 mg/kg or 24.2 times, and for cadmium – 4.663 mg/kg or 2.7 times. Honey from the Southern region had a higher iron content of 0.237 mg/kg or 1.1 times, and zinc by 4.412 mg/kg or 5.5 times compared to honey from the Western region. Based on the obtained data, it is established that honey from the Western region has a higher content of heavy metals than honey from the Southern region, indicating more significant contamination of nectariferous plants in the Western region.

Current application directions for the weathering rind of molybdenum deposits of Ukraine

Purpose. Justification of the new direction of using molybdenum ores from weathering rind of deposits of Ukraine. Research methodology. The research was carried out by general scientific and special research methods – theoretical (analysis, explanation, generalization, comparison), technical and economic evaluation. Research results. The conducted research made it possible to determine the main global approaches to the extraction and application of molybdenum in various areas of industry. The importance of the domestic industry's need for molybdenum-containing fertilizers is substantiated. The reasons why modern global methods for obtaining molybdenum-containing fertilizers are difficult have been revealed. It has been found that modern extraction of molybdenum occurs from native ores, and attempts to extract molybdenum from weathered ores are considered ineffective. The conducted studies indicate significant areas of weathering rinds in Ukraine, including on molybdenum ore occurrences. It is possible to use such weathering rinds as fertilizers directly, that is, bypassing the traditional production of concentrates. The reduction of molybdenum deficiency in Ukrainian arable soils can be achieved by using the weathering crust of molybdenum ore occurrences by soil exchange between enriched soils of ore deposit locations and depleted soils of seeded fields. The originality. For the first time, the regularity of correspondence between the mining term "significantly weathered molybdenum-containing ore" and the agricultural term "molybdenum-contaminated soil" was established. Significant volumes of such ore (soil) in Ukraine were confirmed, and the presence of signs of a promising molybdenum resource in it was also investigated. Practical value. The obtained data make it possible to partially solve the needs of Ukraine in molybdenum, which is currently not mined. The results of the research made it possible to substantiate the direction of the application of molybdenum weathering crust for the domestic agricultural industry, which increases the yield, quality of agricultural products, cultivated areas, income to the foreign currency budget due to the increase in the export of agricultural products, customs duties and taxes.

Classification of diseases in tomato leaves with Deep Transfer Learning

Plant diseases are important factors because they significantly affect the quality, quantity, and yield of agricultural products. Therefore, it is important to detect and diagnose these diseases at an early stage. The overall objective of this study is to develop an acceptable deep learning model to correctly classify diseases on tomato leaves in RGB color images. To address this challenge, we use a new approach based on combining two deep learning models VGG16 and ResNet152v2 with transfer learning. The image dataset contains 55000 images of tomato leaves in 5 different classes, 4 diseases and one healthy class. The results of our experiment are promising and encouraging, showing that the proposed model achieves 99.08% accuracy in training, 97.66% in validation, and 99.0234% in testing

Opening of the agricultural land market in Ukraine: advantages, disadvantages and ways to solve them

The paper covers the topic of opening the land market in Ukraine, in particular, focuses on the advantages, disadvantages and suggests ways to solve them. The author studies the main regulatory legal acts in the field of agricultural land. It is found that the quality of agricultural production and the overall food security of the state depend on the level of functioning of the land market. The authors examine the arguments and counterarguments for lifting the ban on land sales. It is concluded that the current moratorium only exacerbated the existing problems of the land market. The author analyzes the number of contracts for the sale and purchase of agricultural land plots by region. The analysis shows that due to the hostilities in Donetsk, Zaporizhzhia, and Kharkiv regions, this indicator is low compared to other regions. Both positive and negative aspects of the Law of Ukraine "On Amendments to Certain Legislative Acts of Ukraine Regarding the Terms of Agricultural Land Turnover" of July 01, 2021 are highlighted. In particular, the author focuses on problematic aspects, such as: lack of equal access to credit resources for all forms of business in the agricultural sector; lack of criminal liability of state registrars for registering land involved in fraudulent schemes; unregulated sale of agricultural land to foreigners and some others. It is found that only proper and clear legislative regulation will help to eliminate the existing gaps.

The impact of brand trust on consumers' behavior toward agricultural products' regional public brand.

The importance of agricultural products' regional public brands, owned by relevant organizations and jointly used by several agricultural production and operation entities, is increasing in contemporary marketing research. Based on a survey of 544 consumers, this study investigates the influence of brand trust, attitude, subjective norms, and perceived behavioral control on their purchase intention and behavior toward agricultural products' regional public brand. Through SEM, we find that brand trust toward agricultural products' regional public brand positively influences consumer attitude, purchase intention, and purchase behavior. In addition, attitude and purchase intention mediate the relationship between brand trust and purchase behavior. While attitude and perceived behavioral control positively affect purchase intention, no similar effect is found for subjective norms. Moreover, multigroup invariance tests demonstrate that consumer behavior can be influenced by factors such as gender, age, monthly income, marital status, previous visits to the region, and purchase purpose. We therefore recommend that to bolster competitiveness, regional public brand stakeholders maintain agricultural product quality, ensure reliable purchasing and transportation channels, and enhance brand trust.

SERS detection of triazole pesticide residues on vegetables and fruits using Au decahedral nanoparticles

Triazole pesticides are widely used in modern agricultural practices to improve agricultural production quality. Simultaneously, unreasonable and standardized use of triazole pesticides could induce a series of potential diseases of humans. Surface-enhanced Raman spectroscopy has attracted enormous research attention because of its label-free and fingerprint detection capability to noninvasively trace extremely low concentration analytes. To the best of our knowledge, there is a lack of systematic comparison regarding the Raman spectral information of triazole pesticides in existing literatures. In this work, we successfully captured the characteristic peaks of six different triazole pesticides individually and simultaneously using Au decahedral nanoparticles. The proposed method exhibited remarkable detection sensitivity, a wide dynamic range, and the capability for in-situ detection of multiple pesticide residues on bean, apple, and vegetable surfaces with satisfactory recovery rates. Therefore, our proposed SERS platform have great applications in agricultural products safety, environmental monitoring and other fields.

Machine learning for the identification of colour cues to estimate quality parameters of rocket leaves

Computer Vision Systems (CVSs) have proved to be a powerful tool to evaluate the quality of agricultural products in a non-destructive, contactless, sustainable and objective way. Machine learning techniques have proved to simplify the development of CVS and to provide better performance and greater flexibility in matching the requirements of different products and environmental characteristics, but they are often computationally complex and difficult to be understood by humans. It is desirable to develop methods that exploit the benefits of learning and generate simple and fast solutions that are also interpretable by humans. The approach described in this paper analyses a previously developed and effective machine learning model to extract the information useful to develop computationally light and easily understandable algorithms that evaluate the characteristics of interest on rocket leaves. A Random Forest model previously developed to classify visual quality and to estimate chlorophyll and ammonia contents in rocket leaves has been studied to identify a small set of visual characteristics (colours) that correlate with relevant properties of the product. These visual characteristics have been used as input for several simple, fast and easily understandable algorithms that classify visual quality (QL) and estimate chlorophyll and ammonia contents with lower computational complexities compared to the original Random Forest model. Results obtained by these methods are shown and compared with the ones provided by the original Random Forest model. All the algorithms provided a good separation between marketable and non-marketable samples. They required from 1ms to 22 ms to classify a new sample instead of the 25 ms of the original Random Forest model. Additionally, two methods provided good prediction of chlorophyll (R2v = 0.70) and ammonia (R2v = 0.72) contents requiring only 3 ms and 1 ms respectively.

The effect of different biopreparations on soil physical properties and CO2 emissions when growing winter wheat and oilseed rape

Abstract. The introduction of innovative technologies in agriculture is key not only to improving the efficiency of agricultural production and crop yields and quality but also to balancing energy use and preserving a cleaner environment. Biopreparations are environmentally friendly means of restoring the vitality of the soil in which plants can thrive. Biopreparations have an impact on soil health and alter greenhouse gas emissions. The aim of this study was to investigate the effects of different biopreparations on soil porosity, temperature, and CO2 (carbon dioxide) emissions from the soil in northeast Europe (Lithuania) when growing winter wheat and oilseed rape. The experimental studies were carried out over 3 years, and each spring, after the resumption of winter crops, the soil surface was sprayed with biopreparations of different properties or with mixtures of biopreparations under seven scenarios, with one scenario left as a control. Soil porosity, temperature, and CO2 emissions from the soil were measured regularly every month from April to August. The application of the biopreparations showed a cumulative effect on the soil properties. In the third year of the study, the total porosity of the soil was higher in all scenarios compared to the control, ranging between 51 % and 74 %. The aeration porosity of the soil was also higher in all years of the study than in the control, although no significant differences were obtained. The results of the studies on CO2 emissions from the soil showed that, in the first year, the application of the biopreparations increased emissions compared to the control. However, when assessing the cumulative effect of the biopreparations on soil respiration intensity, it was found that, in the third year, most of the biopreparations led to a reduction in CO2 emissions compared to the control. The lowest emissions were achieved with the biopreparations consisting of essential oils of plants, 40 species of various herbs extracts, marine algae extracts, Azospirillum sp., Frateuria aurentia, Bacillus megaterium, mineral oils, Azotobacter vinelandi, humic acid, gibberellic acid, sodium molybdate, Azototbacter chroococcum, Azospirillum brasilense, etc. Evaluating the effectiveness of biopreparations on soil porosity, temperature, and CO2 emissions from the soil, it can be stated that the best effect was achieved in all 3 research years in using biopreparations with Azotobacter chroococcum, Azotospirilum brasilense, various herbs, marine algae extracts, oils of plants, and mineral substances. The multiple-regression model showed that soil temperature has a greater influence on the variation of CO2 emissions than soil aeration porosity.

Spectral Heterogeneity Analysis and Soil Organic Matter Inversion across Differences in Soil Types and Organic Matter Content in Dryland Farmland in China

Soil organic matter (SOM) plays an important role in agricultural production and arable land quality improvement. Hyperspectral technology enables frequent surveys over large areas. In this study, we explored the spectral heterogeneity of differences in soil types and SOM content, and proposed a method for measuring SOM content in large areas using spectroscopy. The results indicate regional variations in factors affecting soil spectral absorption peaks, with noticeable latitudinal disparities. The first-order differential partial-least-squares method provided the best prediction for the SOM inversion. The coefficient of determination (R2) for the SOM inversion model was 0.93, and the root mean square error (RMSE) was 3.42, with an 8.49 g/kg difference in the SOM content. When the difference in SOM content fell between 8 and 15 g/kg, the inversion effect model performed best. The optimal model R2 exceeded 0.95, and the RMSE was less than 5. The comprehensive analysis showed that the organic matter content was an important factor affecting the SOM content estimate and must be considered in the real process. In addition, it is crucial to categorize soil samples on the basis of distinct soil types while maintaining a consistent range of SOM content within the same soil type, ideally between 8 and 15 g/kg. Subsequently, the first-order differential partial least squares method is applicable. These results are expected to contribute to the acquisition of high-quality information on variations in the SOM of complex large-scale areas.

EVALUATION OF THE USE OF SUPPORT FINANCED IN SMALL AND MEDIUM SIZED ENTERPRISES UNDER THE SAPARD PROGRAM FOR AGRICULTURAL PROCESSING AND THE REGIONAL OPERATIONAL PROGRAM IN THE WARMIŃSKO-MAZURSKIE VOIVODESHIP

The aim of the article is to present the essence and assessment of the use of financial assistance for the SME sector from the SAPARD Program and the Regional Operational Program 2014-2020 in the Warmian-Masurian Voivodeship. The subject of the research was the assessment of EU subsidies as a source of enterprise financing. Their aim was to assess the strengths and weaknesses, opportunities and threats resulting from obtaining funds from the ROP for the development of SMEs in the Warmian-Masurian Voivodeship. SWOT analysis was used to achieve the research objective. The research was carried out using the interview method, in which the research tool was a standardized survey questionnaire. They were implemented among the beneficiaries of the Regional Operational Program of Warmia and Mazury for 2014-2020. In addition, classic methods and techniques developed in legal sciences were used. The basic method of research in this sphere was the formal dogmatic method. In addition, the source of data was information obtained from the Agency for Restructuring and Modernization of Agriculture. The SAPARD program gave processing plants in the Warmian-Masurian Voivodeship the opportunity to become familiar with the new support rules used in the EU structural funds. Projects implemented by the SME sector in the Warmian-Masurian Voivodeship have brought tangible benefits in terms of adapting quality and sanitary standards of agricultural processing production to EU requirements. In the case of the Regional Operational Program 2014-2020, the availability of EU funds in the Warmia and Mazury region was assessed by the respondents as insufficient. Due to the completed financial perspective 2014-2020 of the Regional Operational Program of Warmia and Mazury, the possibility of obtaining EU funds has decreased, which significantly limits the development of SME sector enterprises.

Greenhouse environmental control target constrained by discrete surface curvature and multi-objective optimization algorithm

Protected greenhouse provides a suitable micro-environment for crop growth, which enhances the quality and yield of agricultural products. How to optimize the greenhouse environment is currently a pressing issue in protected agriculture. In this research, we propose a new environmental control method from the perspectives of crop photosynthesis rate and environmental control cost. The photosynthesis rate data are collected from a nested experiment of tomatoes, and these data are combined with the support vector regression algorithm to establish a photosynthesis rate model. The cost function of greenhouse environmental control is established by theoretical calculation. The non-dominated solution sets of photosynthesis rate and control cost are obtained through an improved non-dominated sorting genetic algorithm Ⅱ. To determine the optimal solution among the numerous Pareto solutions, the geometric characteristics of the photosynthetic response surface are considered to constrain the control target. Then, a discrete surface curvature method is proposed to computer the constraint region. The intersection between the Pareto solutions and the constraint region is regarded as the environmental control target. The validation experiment demonstrates that the proposed method can effectively enhance photosynthetic accumulation and reduce control cost. Compared to the traditional saturation method, this method achieves a 53% cost reduction while still obtaining 89% photosynthetic accumulation. Compared to the U-chord method, this method increases photosynthetic accumulation by 12% with only a 3% increase in cost. The research has important implications for protected agriculture production.

Geographical origin discriminatory analysis of onions: Chemometrics methods applied to ICP-OES and ICP-MS analysis

Geographical origin is an important determinant of agricultural product quality and safety. Herein, inductively coupled plasma (ICP) analysis was applied to determine the inorganic elemental content of onions and identify their geographical origin (Korean or Chinese). Chemometric, including principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and orthogonal partial least square discriminant analysis (OPLS-DA) were applied to the ICP results. OPLS-DA distinguished each group, and 17 elements with variable importance in projection (VIP) values of ≥ 1 were selected. The receiver operating characteristic (ROC) curve had an area under the curve (AUC) of 1, indicating excellent discriminatory power. Differences in elemental content between groups were visually observed in a heatmap, and the country of origin was determined with 100% accuracy using canonical discriminant analysis (CDA). This method accurately distinguishes between Korean and Chinese onions and is expected to be beneficial for identifying agricultural products.

Comparison of the Efficiency of Hyperspectral and Pulse Amplitude Modulation Imaging Methods in Pre-Symptomatic Virus Detection in Tobacco Plants.

Early detection of pathogens can significantly reduce yield losses and improve the quality of agricultural products. This study compares the efficiency of hyperspectral (HS) imaging and pulse amplitude modulation (PAM) fluorometry to detect pathogens in plants. Reflectance spectra, normalized indices, and fluorescence parameters were studied in healthy and infected areas of leaves. Potato virus X with GFP fluorescent protein was used to assess the spread of infection throughout the plant. The study found that infection increased the reflectance of leaves in certain wavelength ranges. Analysis of the normalized reflectance indices (NRIs) revealed indices that were sensitive and insensitive to infection. NRI700/850 was optimal for virus detection; significant differences were detected on the 4th day after the virus arrived in the leaf. Maximum (Fv/Fm) and effective quantum yields of photosystem II (ΦPSII) and non-photochemical fluorescence quenching (NPQ) were almost unchanged at the early stage of infection. ΦPSII and NPQ in the transition state (a short time after actinic light was switched on) showed high sensitivity to infection. The higher sensitivity of PAM compared to HS imaging may be due to the possibility of assessing the physiological changes earlier than changes in leaf structure.

AGRI-FOOD PRODUCTS QUALITY AS EXPORTS COMPETITIVENESS DETERMINANT OF THE REPUBLIC OF SERBIA

Products quality and safety are important determinants of countries' export competitiveness. Issues of the quality of agri-food products are gaining more and more importance, bearing in mind modern challenges and consumer needs. This is very important for developing countries, including the Republic of Serbia, bearing in mind the importance of this sector for exports and overall economic development. On the other hand, these countries are lagging behind developed countries in terms of quality standards, due to the expensive certification and quality standardization procedures. The growth of competitiveness should be achieved through the improvement of product quality standards, product differentiation and introduction of innovations in the agri-food sector. The goal of the research is to examine the quality of the most important export agri-food products of the Republic of Serbia. The unit value (UV) index, as a measure of product quality, is used to analyse the quality of the most important agri-food products on the most important export markets, with using secondary ITC data. The multiple regression determined that the improvement of agricultural products quality has a positive impact on the growth of exports and competitiveness of agri-food sector of the Republic of Serbia. Namely, the competitiveness of agri-food sector will depend primarily on the ability of this sector to respond to the requirements related to food safety and quality standards, as well as the possibility of investing and innovating processing capacities, in order to create a high-quality final product with high value added.

Motion-Control Strategy for a Heavy-Duty Transport Hexapod Robot on Rugged Agricultural Terrains

Legged agricultural transportation robots are efficient tools that can autonomously transport goods over agricultural terrain, and their introduction helps to improve the efficiency and quality of agricultural production. Their effectiveness depends on their adaptability to different environmental conditions, which is especially true for heavy-duty robots that exert ground forces. Therefore, this study proposes a motion-control strategy for a heavy-duty transport hexapod robot. Two critical tasks were accomplished in this paper: (1) estimating the support surface angle based on the robot’s foot position and body posture, and accordingly determining the motion constraint conditions on this support surface and the body posture based on energy optimization; (2) proposing an adaptive fuzzy impedance algorithm for real-time force–position composite control for adjusting foot position, in order to reduce the steady-state force tracking error caused by terrain stiffness, thus ensuring body stability through tracking of variable foot-end forces. An element of hardware in the loop control platform for a 3.55-ton device was designed and compared with the current popular force-control methods under different external contact terrains. The results show that the proposed control method can effectively reduce force errors, establish support forces faster on less-stiff environments, and reduce the torso tilt during phase switching.

First report of leaf spot on sweet potato (Ipomoea batatas) caused by Alternaria alternata in Bulgaria

For the first time in Bulgaria, leaf spotting on sweet potatoes was investigated, and the causative agent, Alternaria alternata, was reported. The collected morphological data aimed to determine the identity of the fungus. According to Koch, the primary isolates from the damaged parts are identical to those produced from pathogenicity tests. In a laboratory we tested sixty-two leaves which had similar symptoms, with slight to medium-sized lesions with concentric circles and a yellowish halo. In general, the attack from Alt. alternate affected 7% of all plants and 32% of the examined leaves. The pathogen tests proved that the pathogen could also cause damage to tubers during storage. Knowing the etiology of diseases is essential for taking preventive measures and thus preserving the quality and quantity of agricultural production. Keywords: Alternaria alternata, sweet potato, leaf spots, pathogen, pathogenicity