Development Of Farming Systems Research Articles

Hazelnut mapping detection system using optical and radar remote sensing: Benchmarking machine learning algorithms

Mapping hazelnut orchards can facilitate land planning and utilization policies, supporting the development of cooperative precision farming systems. The present work faces the detection of hazelnut crops using optical and radar remote sensing data. A comparative study of Machine Learning techniques is presented. The system proposed utilizes multi-temporal data from the Sentinel-1 and Sentinel-2 datasets extracted over several years and processed with cloud tools. We provide a dataset of 62,982 labeled samples, with 16,561 samples belonging to the ‘hazelnut’ class and 46,421 samples belonging to the ‘other’ class, collected in 8 heterogeneous geographical areas of the Viterbo province. Two different comparative tests are conducted: firstly, we use a Nested 5-Fold Cross-Validation methodology to train, optimize, and compare different Machine Learning algorithms on a single area. In a second experiment, the algorithms were trained on one area and tested on the remaining seven geographical areas. The developed study demonstrates how AI analysis applied to Sentinel-1 and Sentinel-2 data is a valid technology for hazelnut mapping. From the results, it emerges that Random Forest is the classifier with the highest generalizability, achieving the best performance in the second test with an accuracy of 96% and an F1 score of 91% for the ‘hazelnut’ class.

ORGANIC FARMING: DEVELOPMENT PROSPECTS IN RUSSIA, TAKING INTO ACCOUNT THE INTERNATIONAL MARKET

The production of organic agriculture products has become one of the most growing areas of economic activity, with projected annual growth of 10-12%. At the same time, the demand for organic products significantly exceeds the supply, which is largely due to the lack of land that can be allocated for this production. Russia, which has significant areas of virtually unused land on which mineral fertilizers and pesticides have not been used for a long time, reaching 19.7 million. ha, has a significant potential for development in this direction. At the same time, considering that a significant part of unused territories is located within the zone of risky agriculture, and also has soils with a low level of natural fertility, degraded, arid, waterlogged, etc., the actual amount of land resources that can be involved in organic agriculture is significantly less. For the most complete introduction into circulation of unused agricultural lands, it is necessary to increase the knowledge intensity and manufacturability of organic agriculture, for which research work in the following areas is highly relevant: 1) optimization of the balance of humus and nutrients in soils, 2) breeding and seed production of crops for organic agriculture, 3) development of biological products for disease and pest control, 4) development of optimal farming systems taking into account local soil and climatic conditions, 5) optimization of agricultural landscapes based on increasing the diversity of agricultural land use. Along with the involvement of unused lands in the organic production system, the development of the industry largely depends on the system of training qualified personnel in this area, which should take into account the specifics of the technologies used, which differ significantly from traditional farming systems. To do this, it is necessary to update existing professional standards, which should include generalized labor functions related to the development and implementation of organic farming technologies, as well as knowledge and skills in organizing organic production. On the basis of updated professional standards, universities should form new professional competencies and a corresponding set of academic disciplines. The personnel training system for the industry should include various levels of training: agricultural classes, higher education, additional professional education.

Development, Simulation and Visualization of Autonomous Farm Vehicles

Abstract: A Research in Autonomous Agricultural Vehicle Technology is presented. With the coming of the Smart Farming Revolution the development of more complicated machines has begun. Agricultural machines are made with the capability of driving themselves, using GPS maps and electronic sensors, an approach that will lead to the development of futuristic Precise Autonomous Farming Systems. The basic issues to be addressed are autonomous path planning, obstacle detection and avoidance for which various sensors will be employed such as GPS, laser-based sensors, ultrasonic sensors, IMU sensors and Camera sensors whose data has to be constantly monitored using Dead Reckoning algorithm and constant Pose Estimation. In these sensors, Camera, Ultrasonic, Laser-Based Sensors are used as Detection sensors while the IMU and GPS sensors are used as Localization sensors. Global Avoidance Subsystem which examines the whole environment of an autonomous vehicle mission-level path planner that pre-plans paths around all known obstacles. While Local Avoidance Subsystem/Reactive planner consists of an obstacle filter and an obstacle avoidance algorithm and re-plans a short way for the vehicle to navigate. With the ROS framework and all sensors data, a vehicle can guide itself through an unknown environment. This will help the farmer to undercut the labour shortage and improve the precision in farming which in turn improves the output to meet the growing demands

Dampak Pertanian Organik dan Konvenional pada Biodiversitas dan Sifat Kimia Tanah pada Budi Daya Tanaman Padi Sawah

The phenomenon of leveling off and environmental degradation that occurs as a negative impact of the excessive use of chemical fertilizers and pesticides encourages the development of organic farming systems that can produce crop yields that are not contaminated and free from synthetic chemicals and maintain a healthier environment. The research was conducted from October to December 2022 by taking soil samples from farmers' paddy fields in Tegal Regency using an organic (Cawitali Village) and conventional or non-organic (Jembayat Village) farming system. Composite soil samples were taken from a soil depth of 0 to 20 cm from the soil surface using a soil drill on lowland rice fields with organic farming systems and conventional farming after harvest. The analysis of the chemical properties of the soil carried out was C-organic (Walkley and Black), N-total (Kjeldahl), CEC and soil bases (exch-Ca, exch-Mg, exch-K, and exch-Na), total P (25% HCl) and available P (Bray I), while the observed soil biological properties were the total number of microbial and fungal populations. The results showed that organic paddy soil's chemical and biological properties were relatively higher than conventional paddy soil's. Total fungi in organic lowland soils were lower than in conventional paddy fields. The nutrient status of C-organic and N-total in organic rice fields tended to increase compared to conventional rice fields, namely from very low to low and low to moderate, respectively. In contrast, the other nutrient statuses observed tended to remain relatively unchanged. Generally, soil biological and chemical properties were better in organic farming than in conventional farming systems. Keywords: leveling off, organic farming, conventional farming, nutrient status

Designing a user-centric mobile-based agro advisory system for sustainable development of smallholder farming systems in the eastern Himalayas, India

ABSTRACT The Interactive Information Dissemination System (IIDS), a unique mobile-based agro advisory system (MBAS), was put under study in the Design Science Research approach with 2820 farmers in Garo Hills of Meghalaya, India. The study aims to design and develop a user-centric MBAS (m4AgriNEI) for augmenting sustainable smallholder farming systems in hilly regions. The outcomes are critically analysed in the form of learning and experiences to make some necessary modifications to the design. The deployment of the initiative helped to make the m4AgriNEI more user-centric to satisfy the information demand of the resource-poor, smallholder tribal farming communities of the eastern Himalayas. A majority of beneficiaries (70.32%) provided positive responses on advisories through the IIDS generated feedback system. The study suggests the future scaling of MBAS initiative by adding a better knowledge management system, a robust feedback system, a way to track farmer-to-farmer (F2F) communication, and a public-private-community partnership (PPCP) approach.

Multi-Modelling Approach to Support Decision Making in Crop Protection

Abstract A more sustainable control of plant diseases is needed for the development of less intensive farming systems with reduced inputs of chemicals, including pesticides, and reduced use of natural resources. Integrated pest management (IPM) is currently the most effective method for sustainable disease control. IPM has higher complexity than conventional disease management and involves decision making at strategic, tactic, and operational levels, which is often challenging for farmers. Mathematical models are simplified representations of a crop system, which provide dynamic information about the crop status and can support decision making. In an IPM approach, plant disease models must be complemented with other models, such as models for crop growth and development, and models for fungicide dynamics. This case study describes the integration of mathematical models for plant disease, crop development, and plant protection products in a multi-modelling approach able to support multiple decision making in IPM. Downy mildew ( Plasmopara viticola) of grapevines ( Vitis ) is used as a successful story of multiple model combinations through a web-based decision support system. Information © The Author 2024

Цифровая экономика как определяющий фактор развития и эффективного функционирования регионального агропромышленного комплекса

The directions of development of the agricultural sector, farming systems, processes of interaction between rural commodity producers and local self-government in the conditions of the digital economy are considered. Current problems of farming systems arising from the use of digital technologies in the agricultural sector are identified. The article notes that the development of farming systems in the digital economy is beginning to change the role of local government, and the participation of society in production processes is intensifying. The organization of production processes of land use, based on the use of artificial intelligence systems, the use of network technologies in management systems, electronic cadastres, is a factor that ensures increased efficiency of agricultural production and the elimination of corruption in resolving issues of distribution, use and accounting of land. In the digital economy, the formation of an institutional environment is ensured that facilitates the organization of effective interaction between business entities, the reduction of transaction costs, the introduction of innovative technologies, the development of social capital, and ensuring the growth of the economy of rural areas.

Dynamics of Soil Fertility Indicators in Protective Forest Plantations

The purpose of the work is to analyze the dynamics of soil fertility indicators under forest belts in comparison with the inter-belt space in the agricultural landscape due to soil transformation under the influence of adaptive landscape farming systems. A comparative analysis of the variability of soil fertility indicators in forest belts and agrocenoses revealed similar trends in its direction and intensity, which indicates the uniform nature of the soil-forming process. However, some features have been identified. The humus content in the soils of forest belts is on average slightly higher than in the space between the belts. This is caused by higher (2 times) rates of humus accumulation in them in the first period after the development of landscape farming systems. It is during this period that the weedy and rhizomatous stages of restorative succession of the herbaceous flora of forest belts are confined, characterized by a powerful vegetative mass of vegetation and, consequently, an equally significant supply of fresh organic matter, rich in nutrients, into the soil.

Intensity and Direction of Dynamics of Soil Fertility Indicators in Landscape Farming

The purpose of the work is to study the dynamics of soil fertility indicators after the development of adaptive landscape farming systems in the most eroded region of the Belgorod region since 1981. Based on 40 years of research at the model object “Turnip Log”, it is shown that the direction and intensity of the soil-forming process is changing. Four stages are distinguished: at the first until 1993 the decrease in humus content and alkalization of the soil environment, characteristic of washed away carbonate soils, continues; at the second stage, the rate of humus loss drops 10 times; the third ten-year period is characterized by a significant increase in organic matter and its stabilization subsequently, which accompanied by a transition in pHsol. to the area of neutral values. The dynamics of mobile forms of macroelements and agronomically valuable cations Ca2+ and Mg2+ indicate the cultivation of soils in general. At the same time, it is emphasized that there are no universal elements in the agricultural system; Along with the creation of an ecological framework of protective plantings, it is necessary to comply with the principles of adaptive placement of agricultural crops and a deficit-free balance of humus and nutrients in crop rotations.

Enhancing Crop Growth Efficiency through IoT-enabled Smart Farming System

The agricultural sector is facing significant challenges in meeting the increasing demands for food production while ensuring sustainability and resource efficiency. To address these challenges, the integration of Internet of Things (IoT) technology into farming practices has gained attention as a promising solution. This research focuses on the development and implementation of an IoT-enabled smart farming system aimed at enhancing crop growth efficiency. The proposed system leverages IoT sensors and devices to monitor and collect real-time data on various parameters such as environmental conditions, soil moisture levels, and crop health. The collected data is then analyzed using advanced analytics techniques to gain valuable insights and make informed decisions regarding irrigation, fertilization, and pest control. By utilizing IoT technology, farmers can optimize their resource utilization, reduce waste, and maximize crop productivity. This research aims to investigate the potential benefits and challenges associated with implementing the IoT-enabled smart farming system. In this paper, a cutting-edge Internet of Things (IoT) technology is explored for monitoring weather and soil conditions for efficient crop development. The system was built to monitor temperature, humidity, and soil moisture using Node MCU and several linked sensors. Additionally, a Wi-Fi connection is used to send a notification through SMS to the farmer's phone about the field's environmental state. The results will help in developing strategies and guidelines for the widespread adoption of IoT-enabled smart farming practices, ultimately leading to sustainable and efficient crop production to meet the demands of a growing population.

Comparisons between diversified multicropping systems in terms of crop productivity, economic benefits and carbon footprint in the Pearl River Delta region of South China

Increasing crop output while emitting fewer greenhouse gases (GHG) from limited farmland has been a major focus of research in world agricultural production. However, information on diversified multicropping systems involving forage in winter fallow fields has rarely been reported in South China. Therefore, in this study we designed three diversified multicropping systems, including maize−rice−fallow (MRF), maize−rice/ryegrass ​× ​milk vetch mixture (1:1) (MRM1) and maize−rice/ryegrass ​× ​milk vetch mixture (1:2) (MRM2), based on a field trial in the Pearl River Delta region of South China during 2021–2023. The annual crop productivity, economic benefits and carbon footprint (CF) of the diversified multicropping system were jointly analyzed. The results showed that the crop productivity of MRM1 and MRM2 was increased by 14.97% and 14.01%, respectively, compared with MRF, and the increase in MRM1 was significant (P ​< ​0.05). Compared with MRF, the economic benefits of MRM1 and MRM2 were increased by 10.15% and 10.29%, respectively, and the differences were not significant. It was found that the higher the planting index is, the lower the CF value. The CF values of MRM1 and MRM2 based on unit area, unit crop productivity and unit economic benefit decreased by 5.13%–22.83%, respectively; this was mainly due to the significant increase in soil organic carbon content by MRM1 and MRM2, which were 4.12% and 15.66% higher than MRF, respectively (P ​< ​0.05). In summary, the introduction of winter forage in the maize‒rice multicropping systems in the Pearl River Delta region of South China could improve crop productivity, increase economic benefits, and reduce the CF. MRM2, the recommended pattern based on the current results, has higher economic efficiency and lower carbon footprint per unit compared to MRM1. This study provides valuable information for the creation of diversified multicropping systems in South China and a reference for the development of sustainable farming systems in tropical subtropical regions worldwide.

A Review on Information Technologies Applicable to Precision Dairy Farming: Focus on Behavior, Health Monitoring, and the Precise Feeding of Dairy Cows

Milk production plays an essential role in the global economy. With the development of herds and farming systems, the collection of fine-scale data to enhance efficiency and decision-making on dairy farms still faces challenges. The behavior of animals reflects their physical state and health level. In recent years, the rapid development of the Internet of Things (IoT), artificial intelligence (AI), and computer vision (CV) has made great progress in the research of precision dairy farming. Combining data from image, sound, and movement sensors with algorithms, these methods are conducive to monitoring the behavior, health, and management practices of dairy cows. In this review, we summarize the latest research on contact sensors, vision analysis, and machine-learning technologies applicable to dairy cattle, and we focus on the individual recognition, behavior, and health monitoring of dairy cattle and precise feeding. The utilization of state-of-the-art technologies allows for monitoring behavior in near real-time conditions, detecting cow mastitis in a timely manner, and assessing body conditions and feed intake accurately, which enables the promotion of the health and management level of dairy cows. Although there are limitations in implementing machine vision algorithms in commercial settings, technologies exist today and continue to be developed in order to be hopefully used in future commercial pasture management, which ultimately results in better value for producers.

Effects of long-term rice-crayfish farming on soil CNP storage and stoichiometry

In recent years, traditional rice monoculture (RM) has led to agricultural intensification, resulting in loss of soil nutrients and the low fertility. Rice-crayfish (RC) integrated farming, as a sustainable agricultural system, could significantly enhance accumulation of soil C (carbon), N (nitrogen) and P (phosphorus) while improve soil fertility. However, it is still unknown how the characteristics of soil CNP stoichiometry and storage are influenced by long-term RC farming. This study examined the patterns of soil CNP storage and stoichiometry at 0–30 cm soil layers in RM and RC systems (1, 6, 10, and 15 years) scattered in Nanxian County, Hunan Province, China. Compared to RM system, soil C, N, and P storage increased by 4.1–10.9, 0.1–0.9, and 0.03–0.4 Mg ha−1 in 6, 10, and 15-year rice-crayfish (RC6, RC10 and RC15) systems, respectively. Meanwhile, compared to RM system, soil C:N, C:P and N:P ratio increased significantly in RC6, RC10 and RC15 systems. Besides, the principal component, redundancy analysis and structural equation model revealed that soil BD, pH, aggregates and nutrient altered by agricultural practices (no-tillage, feed and flooding) of RC system significantly affected CNP stoichiometry and storage of paddy soil. Although the accumulation of soil nutrient were showed in long-term rice-crayfish farming system, it is also necessary to pay attention to the negative impact of nutrient surplus on the environment. Based on these results, it is necessary to regulate input of fertilizer and improve efficient utilization of feed for guaranteeing soil nutrient balance and retention, so as to ensure sustainable development of rice crayfish farming system.

Land Parcel Identification System (LPIS) data allows identification of crop sequence patterns and diversity in organic and conventional farming systems.

Farmers grow crops in specific sequences to lower disease pressure and boost crop productivity, particularly in organic farming where artificial pesticides and chemical fertilisers are prohibited. Knowledge about crop sequences used in organic and conventional farming will aid the development of future farming systems through optimising crop diversity and pre-crop effects for improved resource efficiency. This study aims to investigate crop diversity and patterns in organic and conventional crop sequences in Sweden. Large-scale LPIS field data managed by the European Union (EU) Integrated Administration and Control System (IACS) were used to monitor crop sequences on arable land in Sweden over 10 consecutive years (2005–2014). Individual fields (land parcels) could be followed on 40% of Sweden’s total arable area (349,891 fields extracted) over the 10 years. The LPIS data was combined with information from a database on which fields were farmed organically. Crop distribution, diversity of crop sequences and pre-crops to the main cereal crops (winter wheat, spring barley) were analysed in organic and conventional farming systems in the five agricultural productivity zones of Sweden. The results showed that in the most productive zone in southernmost Sweden, small-grain cereals (particularly winter wheat) were the most common crops (62%), followed by oilseeds (11%), ley and forage crops (9%) and sugar beet (8%), when excluding permanent grassland. In the least productive zone (at higher altitudes and/or latitudes), ley and forage crops dominated (67%), followed by spring cereals (barley, oats) (23%). Crop diversity was higher in the two more productive zones (mean 4.6 crop types) than in two less productive zones (3.4) and organic farms showed 9% higher crop diversity than conventional farms in the most productive zones. Overall, in all zones, the pre-crop to winter wheat was generally a different crop type (3 out of 5 times) e.g., young ley (1–2 years) or grain legume, while the pre-crop to spring barley was most often (4 out of 5 times) another cereal. For both these crops, pre-crop type was more diverse in organic than conventional systems. These findings demonstrate that LPIS data can offer valuable insights into agronomic trends and on-farm practices regarding crop choice and that analysis of field-level LPIS data on crop sequences at large scale can reveal information about organic and conventional cropping in different productivity zones across countries. This information can be used to understand the practical limitations in the use of crop diversity to maximise pre-crop effects. This could in turn support advisory service and policy makers to facilitate more sustainable, productive and resource efficient crop production.

К ВОПРОСУ РАЗВИТИЯ И ЭКОНОМИЧЕСКОЙ ЭФФЕКТИВНОСТИ МЕЛИОРАТИВНОЙ ОТРАСЛИ РЕСПУБЛИКИ ТАТАРСТАН

Sustainable and efficient production of agricultural products, regardless of the influence of weather and climate factors in the zone of risky farming, is largely possible only with the widespread introduction of land reclamation measures. The research was carried out with the aim of studying the current state of the reclamation industry in the Republic of Tatarstan and developing scientifically based ways of its development. In the course of the studies of the economic efficiency of irrigated agriculture in the republic, it was found that in potatoes production due to irrigation, the yield increases from 3.89 to 4.2 times, and the marketability of finished products due to improved quality and standardization of tubers by 2.58 times. It was revealed that with a potato marketability of 80%, the net income per 1 ha is 495.9 thousand rubles. The net income from 1 ha of corn for silage under irrigation is 52.4 thousand rubles. This suggests that one ruble spent on irrigation allows farms to receive up to 12 rubles of additional production in the production of grain crops. And in the production of vegetables and marketable potatoes - up to 40 rubles. The cultivation of perennial crops on irrigation makes it possible to obtain up to four full-fledged cuttings, which makes it possible to provide the livestock industry with a reliable fodder base. At this stage of development of the reclamation industry of the Republic of Tatarstan, about 1.5% of the arable land of the Republic is under irrigation reclamation, it produces up to 18.5% of the gross crop production. However, the widespread introduction of land reclamation elements by agricultural producers is limited due to a number of reasons. This series includes: the high cost of restoration, construction, operation and maintenance of reclamation facilities and their network, the lack of technical and financial resources for agricultural enterprises, the need for preliminary costly survey and design work to obtain design estimates (DED). According to expert estimates, to provide food for the inhabitants of the Republic of Tatarstan, it is necessary to have at least 150 thousand hectares of irrigated land, against the currently available 35 thousand hectares. Achieving the indicated value of irrigated lands is not possible without the adoption of a comprehensive program for the development of melioration and agrolandscape farming system, which should be adequately financially secured for the implementation of program activities.

Anthelmintic Activity of Tanacetum vulgare L. (Leaf and Flower) Extracts against Trichostrongylidae Nematodes in Sheep In Vitro.

Due to the high prevalence of gastrointestinal nematodes in sheep, the growing anthelmintic resistance, and the development of organic farming systems, sustainable alternatives are being sought. One such method is phytotherapy. This study aimed to evaluate the in vitro ovicidal and larvicidal activity of extracts of tansy (Tanacetum vulgare L.) growing in Latvia on gastrointestinal nematodes (Trichostrongylidae) in sheep. The leaves and flowers of the tansy were extracted separately in 70%, 50%, and 30% ethanol and acetone. Six concentrations were prepared from each extract 500 mg/mL, 200 mg/mL, 100 mg/mL, 50 mg/mL, 20 mg/mL, and 10 mg/mL. In vitro egg hatching test and micro-agar larval development test were performed. Extracts of tansy have strong larvicidal activity. The highest percentage of larvae inhibition for most of the extracts was 100%, but for egg inhibition, it was 95.8% for the 200 mg/mL concentration of 50% acetone and 93.3% for the 500 mg/mL concentration of 50% ethanol leaf extracts. All tansy extracts had ovicidal and larvicidal activity against Trichostrongylidae in sheep.

Understanding the role of scientific knowledge transfer in the women's participation and farmer activities in Central Java

The forest turns to agricultural land in the Serayu watershed in Central Java, Indonesia. The Strengthening Community-Based Forest and Watershed Management (SCBFWM) project aims to improve and expand the Indonesian government's community-based forest and watershed management programs. The study's objectives are: 1) investigate the factors that contribute to the successful implementation of scientific findings in everyday life; 2) analyze the potential impacts of alternative strategies for the development of farming systems in the watershed on rural livelihoods; and 3) analyze the rules and governance structure that organizes the action of actors and how decisions are made. We use the RIU (Research-IntegrationUtilization) Model to examine how scientific research can yield effective policy advice and decision-maker's role in transforming advice into effective problem-solving. The findings that emerged from the research demonstrated that the district government cares about the environment but does not prohibit upstream potato cultivation strictly. When the SCBFWM project was established, cultivation restrictions were implemented. The research on the importance of women's participation in watershed management was communicated to the district administration and included in the SCBFWM project's proposal, but the actual action was different. The RIU model demonstrated that high-quality science is insufficient without efficient integration and acknowledges the inherent divergent interests within science and policy

Performance of BARI-released gladiolus varieties under the climatic conditions of young Brahmaputra and Jamuna floodplain

The experiment was conducted in the farmers’ field at the Farming System Research and Development site (FSRD), Atia, Delduar, Tangail during the Rabi season of 2018-19 and 2019-20 to evaluate the performance of BARI released gladiolus varieties and popularize these varieties among the farmers of Tangail region. BARI developed three varieties of gladiolus, namely BARI Gladiolus-3, BARI Gladiolus-4, and BARI Gladiolus-5. Among the three varieties, BARI Gladiolus-4 performed the best in terms of the spike (191009 piece ha-1) and corm (254322 piece ha-1) production from the average of 2018-19 and 2019-20. Though BARI Gladiolus-4 performed the best in terms of yield, the maximum economic return was obtained from BARI Galdiolus-5 due to a higher spike in demand and market price compared to the other two varieties. The highest gross return (Tk.2406215 ha-1), gross margin (Tk. 1402546 ha-1), as well as BCR (2.40), were also recorded in BARI Gladiolus-5 followed by BARI Gladiolus-4. The lowest gross return (Tk. 1837608 ha-1), gross margin (Tk. 833939 ha-1) as well as BCR (1.83), were obtained from BARI Gladiolus-3. The farmers under the AEZ-8 areas can become economically benefitted by the production of BARI Gladiolus-5 and BARI Gladiolus-4. Bangladesh J. Agri. 2023, 48(1): 10-18

Ecosystem Services at the Farm Level-Overview, Synergies, Trade-Offs, and Stakeholder Analysis.

The current geological epoch is characterized by anthropogenic activity that greatly impacts on natural ecosystems and their integrity. The complex networks of ecosystem services (ESs) are often ignored because the provision of natural resources, such as food and industrial crops, is mistakenly viewed as an independent process separate from ecosystems and ignoring the impacts on ecosystems. Recently, research has intensified on how to evaluate and manage ES to minimize environmental impacts, but it remains unclear how to balance anthropogenic activity and ecosystem integrity. This paper reviews the main ESs at farm level including provisioning, regulating, habitat, and cultural services. For these ESs, synergies are outlined and evaluated along with the respective practices (e.g., cover- and intercropping) and ES suppliers (e.g., pollinators and biocontrol agents). Further, several farm-level ES trade-offs are discussed along with a proposal for their evaluation. Finally, a framework for stakeholder approaches specific to farm-level ES is put forward, along with an outlook on how existing precision agriculture technologies can be adapted for improved assessment of ES bundles. This is believed to provide a useful framework for both decision makers and stakeholders to facilitate the development of more sustainable and resilient farming systems.

Periodization of the evolution of science about agricultural systems in Ukraine in the context of agricultural systems development

The periodization of the development of the doctrine of agricultural systems in the context of the evolution of agricultural management systems is outlined. The contribution of scientists and producers to the development of the scientific foundations of agricultural systems and their implementation in agricultural practice is highlighted. Attention is focused on the complex and long way of forming views on the need for theoretical foundations farming systems. In the evolutionary development of the theory of farming systems, scientists of Bila Tserka National Agrarian University distinguish three stages. The first stage (prerevolutionary, until 1917) includes three periods: the first (the emergence of the doctrine) covers the second half of the 18th century. (the founders of the doctrine were A.T. Bolotov, I.M. Komov, V.O. Levshyn, D.M. Poltoratskyi, I.I. Samarin), the second (laying the scientific foundations of agricultural systems) — the first half of the 19th century. (M.G. Pavlov, Yu.A. Linovskyi, S.M. Usov), the third (formation of the theoretical foundations of agricultural systems) — the second half of the 19th century. — the beginning of the 20th century (O.I. Skvortsov, O.V. Sovietov, O.M. Enhelhardt, O.P. Liudohovskyi, I.O. Stebut, O.S. Yermolov). The second (Soviet) stage includes two periods: the first lasted until the middle of the 20th century. (V.R. Villiams, D.M. Prianishnykov, M.M. Tulaikov, etc.), the second — until the 90s of the 20th century. (V.P. Nartsyssov, S.O. Vorobiov, D.I. Burov, O.M. Kashtanov, etc.). The third (modern) stage begins in the 90s of the 20th century. and continues to this day and is characterized by an agro-landscape approach to the development and improvement of farming systems. The opinion of those scientists who considered the farming system out of connection with agricultural management systems, justifying a set of agrotechnical measures only from natural and scientific positions and evaluating the effectiveness of farming systems only by their ability to maintain and increase soil fertility turned out to be wrong.