Farm Scale Research Articles

Vertical Farms: A Sustainable Solution to Urban Agriculture Challenges

Vertical farms are considered to be a powerful response to the shortage of future agricultural cultivation space, which can achieve higher agricultural output in cities and alleviate food shortage. This paper focuses on the characteristics of vertical farms, takes the Plant vertical farm in Chicago as an example, describes its design and performance, analyzes its advantages and design principles, and raises some problems that need to be solved. Vertical farms can expand the yield of crops and simulate the environment required for crop growth and development. The success of The Plant is mainly due to the following aspects of the design: saving raw materials and waste disposal costs through the use of waste, staggered electricity consumption and the use of insulated structures to maximize the savings in energy costs, and ultimately enabling the vertical farm to achieve the ability to compete with traditional agriculture. The vertical farm finally achieved the ability to compete with traditional agriculture. It is worth noting that although the small-scale pilot projects of vertical farms have achieved some success, there are still many constraints to be overcome in expanding the scale of vertical farms because of their high construction and operation costs and high technical level.

Decision-making for circular economy implementation in agri-food systems: A transdisciplinary case study of cacao in Colombia

Sustainable food security represents a significant challenge in advancing the global agenda expressed in the Sustainable Development Goals, including feeding the growing world population while transitioning toward a circular economy. A growing body of literature is focused on developing concepts and documenting circular economic opportunities in agricultural food systems. However, the methodologies for implementing circular economy models at the farm level remain mostly theoretical. This study proposes a transdisciplinary based approach for evaluating circular economy alternatives in agri-food systems while enhancing farmers’ decision-making skills. The transdisciplinary based research methodology combines methods for simulating critical resource and production flows with multi-criteria decision-making, including training and obtaining feedback from farmers. We test the methodology on a cacao agri-food system in Meta (Colombia). Biomass waste and cost-benefit data allow evaluation for decision-making of four circular economy scenarios: composting, vermicomposting, drip irrigation, and valorization of cacao husks. Research outcomes recommend vermicomposting as a viable circular economy innovation for cacao farms to reduce biomass waste and improve economic income at farm level. Other outcomes include capacity building of farmers on circular economy –including resource flow analysis and cost-benefit calculation. Effective decision-making on circular economy adoption at farm level is evidenced by vermicomposting technology implementation. Policy recommendations call for transdisciplinary based approaches for promoting and scaling the transition towards a circular economy in agri-food systems at a farm scale involving farmers participation in operations research (analytics) modelling and interpretation. In addition, policy advise for circular economy technical assistance and finance, includes vermicomposting as a technology for scaling transition of agri-food systems such as cacao and comparable long-term crops.

Three-stage dynamic equivalent modeling approach for wind farm using accurate crowbar status identification and voltage differences among wind turbines

With increasing wind farm scale, dynamic modeling and simulating the low-voltage ride-through (LVRT) process of wind farms are time- and source-consuming. Thus, a dynamic equivalent model of a wind farm considering the LVRT process is necessary and vital for power system analysis. However, the crowbar status of each doubly-fed induction generator (DFIG), voltage, and wind speed differences among will influence the LVRT process and equivalent results. To consider these three factors comprehensively and eliminate the error, this paper proposes a three-stage dynamic equivalent modeling approach, using accurate crowbar identification and voltage differences among DFIGs. Stage I: DFIGs are divided by crowbar status. A new accurate crowbar identification method is proposed to consider the interference from other DFIGs, using the experimental two-machine system and several dynamic simulations to correct fault voltage. Stage II: The often-overlooked voltage differences are considered, and DFIGs are divided into different clusters for accurate fault dynamics. Stage III: To eliminate errors resulting from wind speed differences, the DFIG active power reference is corrected based on the analytical function of the wind farm LVRT process. The proposed model can accurately identify crowbar status and consider the voltage and wind speed differences without detailed model simulation results, improving the accuracy. Case studies are undertaken on a wind farm with fifty DFIGs. Simulation results indicated that the proposed model can match the detailed model under different wind scenarios and fault voltages, and it also increases simulation efficiency, which is suitable for studying the effect of LVRT on power systems.

A new framework for evaluating water use reduction strategies using an integrated, holistic, and transparent approach (Urmia Lake basin case study)

Agriculture and food security have always faced challenges related to water scarcity, so agricultural water conservation is the most important strategy for overcoming this challenge. In this study, the REWAS tool developed by FAO and Future Water was used to evaluate the effects of technological and management strategies on real water savings (RWS) in the Zarrineh River sub-basin, Iran. Nine farms were investigated (wheat, corn, tomato, sugar beet), including control and treatment farms. According to changes in water consumption and return flows, RWS was calculated for various scenarios of field interventions. To assess the water consumption in Basin scale, REWAS was simplified the accounting framework for water consumption (consumed and unconsumed). In the Zarrineh River sub-basin, the use of the techniques applied in the treatment farm, compared to the control farm (according to farmer customary practices), resulted in a significant reduction of non-beneficial consumption. For example, according to the REWAS evaluation in West s17 farn, the treatment farm consumed the most useful water compared to the control farm (331 mm and 267 mm, respectively), which led to the most useful water consumption at basin scale (to the order of 3920 mm and 3166 mm). According to the results on the scale of the basin , the highest amount of recoverable discharge was also obtained in the control farm with an increase of 3774 MCM over the treatment farm. Using strategies to reduce water consumption resulted in apparent water saving (AWS) at the farm scale, but these AWS were very different from their RWS at the basin scale and the RWS at the basin scale (13%) was much lower than the AWS at the farm scale (38%). According to the results, apparent water savings (AWS) at the farm scale do not reduce water consumption, and may actually increase it when viewed in a basin scale. REWAS concepts indicate that significant amounts of “lost” water are actually recoverable return flows that can be used by downstream users or contribute to wetlands. According to REWAS concepts, real water savings can only be achieved by preventing non-recyclable backflows. Assessing RWS can help decision makers select sustainable interventions that will improve agricultural water productivity by providing information on farm flows, irrigation networks, and basin scales.

Hydrogen for harvesting the potential of offshore wind: A North Sea case study

Economical offshore wind developments depend on alternatives for cost-efficient transmission of the generated energy to connecting markets. Distance to shore, availability of an offshore power grid and scale of the wind farm may impede export through power cables. Conversion to H2 through offshore electrolysis may for certain offshore wind assets be a future option to enable energy export. Here, we analyse the cost sensitivity of offshore electrolysis for harvesting offshore wind in the North Sea using a technology-detailed multi-carrier energy system modelling framework for analysis of energy export. We include multiple investment options for electric power and hydrogen export including HVDC cables, new hydrogen pipelines, tie-in to existing pipelines and pipelines with linepacking. Existing hydropower is included in the modelling, and the effect on offshore electrolysis from increased pumping capacity in the hydropower system is analysed. Considering the lack of empirical cost data on offshore electrolysis, as well as the high uncertainty in future electricity and H2 prices, we analyse the cost sensitivity of offshore electrolysis in the North Sea by comparing costs relative to onshore electrolysis and energy prices relative to a nominal scenario. Offshore electrolysis is shown to be particularly sensitive to the electricity price, and an electricity price of 1.5 times the baseline assumption was needed to provide sufficient offshore energy for any significant offshore electrolysis investments. On the other hand, too high electricity prices would have a negative impact on offshore electrolysis because the energy is more valuable as electricity, even at the cost of increased wind power curtailment. This shows that there is a window-of-opportunity in terms of onshore electricity where offshore electrolysis can play a significant role in the production of H2. Pumped hydropower increases the maximum installed offshore electrolysis at the optimal electricity and H2 prices and makes offshore electrolysis more competitive at low electricity prices. Linepacking can make offshore electrolysis investments more robust against low H2 and high electricity prices as it allow for more variable H2 production through storing excess energy from offshore. The increased electrolysis capacity needed for variable electrolyser operation and linepacking is installed onshore due to its lower CAPEX compared to offshore installations.

Assessment of a Novel Real-Time Bio-Liquor Circulation System for Manure Management and Mitigation of Odor Potential in Swine Farming.

Recently, circulating biologically treated manure in slurry pits has been used as an odor reduction technology, but few successful results have been reported, due to the lack of proper control strategies for bioreactors. This study was conducted to investigate the performance of the developed real-time controlled bio-liquor circulation system (BCS) at farm scale. The BCS was operated sequentially as per swine manure inflow (anoxic, aerobic, and settling) circulation to the slurry pit. Each operational phase was self-adjusted in real-time using a novel algorithm for detecting the control point on the oxidation reduction potential (ORP) and pH (mV)-time profiles, the nitrogen break point (NBP), and the nitrate knee point (NKP) in the aerobic and anoxic phases, respectively. The NH4-N in the slurry manure was thoroughly removed (100%) in the bioreactor, optimizing the duration of each operational phase by accurately detecting real-time control points. The newly developed real-time BCS decreased the nitrogen and organic matter in the slurry pit by >70%, and the potential ammonia and methane emissions by 75% and 95%, respectively. This study highlights that improved BCS that utilizes ORP tracking and pH (mV)-time profiles can effectively optimize BCS operation, and thereby reduce malodor and GHG emissions from swine farms.

Synthetic turbulence modelling for offshore wind farm engineering models using coherence aggregation

AbstractTurbulent wind fields are known to be a major driver for structural loads and power fluctuations on offshore wind turbines. At the single‐turbine scale, there exist well‐established design standards based on wind spectra and coherence functions calibrated from years of measurements, which are used to generate multiple 10‐min wind field realisations known as synthetic turbulence boxes, themselves used as input to turbine‐scale aero‐hydro‐servo elastic codes. These methods are however not directly applicable at farm scale. When analysing the dynamics of large offshore wind farms, measurements reveal the importance of large, low‐frequency turbulent vortices for power fluctuations and hence for wind farm control and grid integration. Also, farm‐scale wind fields are needed as input to farm‐scale aero‐servo‐elastic codes for the modelling of wake dynamics, affecting structural loads. These new concerns motivate an upgrade in the original turbine‐scale wind field representation: (1) spectral models need to be based on farm‐scale measurements, (2) the frozen‐turbulence assumption merging temporal and along‐wind coherence must be lifted, (3) simplifications are needed to reduce the number of degrees of freedom as the domain becomes excessively large. This paper suggests models and algorithms for aggregated farm‐wide corrrelated synthetic turbulence generation—lumping the wind field into space‐averaged quantities—adapted to the aero‐hydro‐servo elastic modelling of large offshore wind farms. Starting from the work of Sørensen et al. in the early 2000s for grid integration purposes, methods for structural load modelling (through wake meandering and high‐resolution wind field reconstruction) are introduced. Implementation and efficiency matters involving mathematical subtleties are then presented. Finally, numerical experiments are carried out to (1) verify the approach and implementation against a state‐of‐the‐art point‐based—as opposite to aggregated—synthetic turbulence generation code and (2) illustrate the benefit of turbulence aggregation for the modelling of large offshore wind farms.

Status, evaluation, and influencing factors of biosecurity levels in pig farms in China

BackgroundAnimal diseases have always been a serious threat to livestock breeding, and the establishment of a biosecurity barrier is important for disease prevention and control. Based on the investigations conducted in seven provinces located farms, this study aimed to explore the current biosecurity levels of farms in China, construct a biosecurity evaluation system, calculate the biosecurity levels of farms using the rank sum ratio comprehensive evaluation method, and develop an empirical analysis of the factors influencing biosecurity levels.ResultsThe results show that the greater the cost of biosecurity invested, the greater the level of biosecurity. Male farmers, educational attainment and participation in technical training had a significant positive effect on biosecurity levels. In addition, biosecurity levels first decreased and then increased as the scale of farming increased. The study also found that the more people in the household engaged in farming, the higher the biosecurity level of the farm. And farms that joined cooperatives had higher levels of biosecurity.ConclusionThe rank sum ratio method can evaluate the index system, so as to obtain a comprehensive index RSR value that can be compared, and the operation steps are simple and effective. By taking measures such as improving the comprehensive quality of farmers and increasing the investment in human, material and financial resources for biosecurity, the biosecurity level of farms can be effectively improved and animal diseases can be effectively prevented and controlled.

SMART GROW – Low-cost automated hydroponic system for urban farming

Urban farming has gained popularity in recent years, as more people have become interested in locally grown food and reducing their carbon footprint. Smart hydroponic systems can be an important tool for urban farming as they allow for precise control over plant growth and require less space and resources than traditional farming methods. Urban areas often lack access to land suitable for farming, making hydroponic systems a viable option for growing crops in limited space. Readily available hydroponic systems in the market are costly and not cost effective, thus hydroponic systems are usually only installed in larger scale farming. The challenge here is to connect multiple low-cost sensors to microcontrollers and to any store-bought hydroponic set. This paper describes the development of smart Internet of Things (IoT) hydroponic system integrated with an Android mobile application for small scale urban farming.The new set up of IoT hydroponic set, coined as SMART GROW, is used to monitor and control various aspects of the system based on the basic parameters important in growing a healthy plant. The challenges faced during this build were irregular reading of the analog sensor when connected to a single board microcontroller (ESP32). This issue was resolved. SMART GROW currently is capable of monitoring basic parameters such as pH, EC and water level and can cater to additional sensors for monitoring other parameters if required. SMART GROW can easily be replicated and built at home and customized to the needs of the plant’s requirement. SMART GROW is versatile as it can be used to grow a wide variety of plants, including herbs, vegetables, and fruits, and offers several benefits over traditional soil-based growing methods such as automated regulation of the water level.

Review of livestock biosecurity resources and trainings: Local, state, federal, and international organizations

PurposeThis study evaluates the accessibility and availability of publicly accessible biosecurity resources in the Fall of 2021, as part of the IN-PREPared and Gearing Up for Safety program. The research into the quantity of material underscores the importance of these resources for disease threat awareness and highlights the need for improved biosecurity resource development for small-scale farming communities and overall biosecurity resources which impact global agricultural operations and food security. Design/methodology/approachThis review consisted of resources on agricultural biosecurity literature, websites, and training materials, involving over 125 agencies and organizations. This analysis provides insights into the distribution of resources across different regions and their availability based on farm scale and production type. FindingsOur research reveals both a geographic distribution trend of material that favors Midwestern states and significant disparities in available materials. Additionally, there are more resources that have content that focus on “general biosecurity’ and are focused on larger operations than that of small-farm biosecurity operations. International resources generally focus on overall importance of biosecurity and aspects of One Health. Practical ImplicationsThis review underscores the crucial role of biosecurity resources in enhancing disease threat awareness and safeguarding the food supply and global impact of international trade within agriculture. This emphasizes the need to address resource deficiencies for small-scale farms, particularly regarding specific livestock concentrations. Theoretical ImplicationsThe study confirms with previous research on limited resources, emphasizing the need for a more equitable approach to disseminating biosecurity information, especially for small-scale farming. Implications highlight the importance of resources, training, and informed decision-making for all farming communities, highlighting the significance of risk-based agricultural materials. Originality/ValueThe research adds value by shedding light on the unequal distribution of biosecurity resources, especially concerning small-scale farming operations. While the study primarily focuses on livestock and animal health, it acknowledges the importance of crop biosecurity, thus contributing to a broader understanding of agricultural protection. The significance of collaboration and information sharing in the global context of biosecurity extends beyond national borders and requires a coordinated effort.

Reproductive Performance of Buffalo (Bubalus bubalis) in Small Scale Farm in Boyolali Regency Central Java

This study aimed to determine the reproductive performance of female buffalo in Boyolali Regency, Central Java, Indonesia. The sampling method used was the purposive sampling method. The number of respondents was 30 buffalo farmers with a total sample were 100 female buffalo. Collecting data using interview, observation, and literature study methods and analyzing descriptively. The data that has been obtained is then calculated into percentages, averages, and standard deviations, then analyzed descriptively. Buffalo farmers are rice farmers who are still productive with a dominant age of less than 65 years. The main feed given was rice straw, and 64% of buffalo received additional field grass when grazing. The farming experience of farmers was quite long, which is more than 15 years, and was classified as a small-scale farm with the number of buffalo less than 5 heads. The management system used by buffalo farmers is mostly (90%) semi-intensive. The values of gestation length, postpartum estrus, and postpartum estrus were 308.0±7.4 days, 102.2±6.2 days, and 406.8±8.9 days, respectively. The age of first calving for buffalo in the study in Boyolali Regency was 3.60 ± 0.3 years. This study concluded that the reproductive performance of buffaloes in smallholder farms in Boyolali Regency, Central Java Province was in good condition.

Full-Season Crop Phenology Monitoring Using Two-Dimensional Normalized Difference Pairs

The monitoring of crop phenology informs decisions in environmental and agricultural management at both global and farm scales. Current methodologies for crop monitoring using remote sensing data track crop growth stages over time based on single, scalar vegetative indices (e.g., NDVI). Crop growth and senescence are indistinguishable when using scalar indices without additional information (e.g., planting date). By using a pair of normalized difference (ND) metrics derived from hyperspectral data—one primarily sensitive to chlorophyll concentration and the other primarily sensitive to water content—it is possible to track crop characteristics based on the spectral changes only. In a two-dimensional plot of the metrics (ND-space), bare soil, full canopy, and senesced vegetation data all plot in separate, distinct locations regardless of the year. The path traced in the ND-space over the growing season repeats from year to year, with variations that can be related to weather patterns. Senescence follows a return path that is distinct from the growth path.

Modifying physical supply and use tables (PSUTs) in the system of environmental-economic accounting (SEEA) for off-farm irrigation water management

A reliable water accounting framework is crucial for understanding the contribution of water resources in meeting agricultural demands and selecting appropriate operating systems for off-farm water systems, including hydraulic conveyance and distribution structures. This ensures fair, adequate, and dependable irrigation water distribution, especially under water scarcity operational scenarios. This study presents a novel and effective method for modifying PSU tables in the SEEA water accounting framework that is specifically designed for small-scale agricultural water management study areas. The proposed approach entails a comprehensive analysis of the surface water distribution within the water holders using a hydraulic simulation model and a spatial analysis of the groundwater extraction for meeting on-farm water demands. This approach was implemented on Iran's Central Plateau and revealed notable variations in water rights and distribution effectiveness among stakeholders so that, surface water contributed 27–40% less than the legal water rights, leading to aquifer overexploitation. The evaluation indicated that changing crop patterns and upgrading to pressurized irrigation systems led to 4–7.5% overexploitation of groundwater and 3.5–6% water conservation on farm scales. Besides, the spatial assessment verified a considerable overlap of 59% between the farms with modern irrigation systems and those with cultivated area expansion, resulting in sustained overexploitation pressure on the aquifer. The present study has two significant practical implications. Firstly, it specifies the contribution of surface- and groundwater resources in fulfilling the water demands of individual water-holders. Secondly, it provides reliable information to decision-makers about the incentives for modernization, rehabilitation, and renovation projects in an irrigation district.

Yield and growth rates of pastures grown in the Bay of Plenty region over 35 years

Bay of Plenty district, and particularly the Rotorua Lakes area, has a diverse terrain and soil types which influence pasture production. Regular measurement of pasture production enables short term decision making on a farm scale and is invaluable for catchment,district and regional long term management strategies. Thomas (Tom) M. Gee, was a retired farmer with more than 18 years of field trial experience with MAF Field Research Division. He collected data from more than 30 farms after he retired. Data from other sites in the district were collected in the early 1970s by MAF technicians stationed in Whakatane and Tauranga and later by AgResearch staff and a farm consultant based in Rotorua. Tom Gee’s mission was to use these measurements to provide farmers with rates of growth (ROG) data to inform them about their farm. The Gee farm (Fairbank) of 200 ha was originally leased from Ngati Whakaue Tribal Lands in 1916 and then purchased before much of it was sold back to the Incorporation in 1970. Tom retired in 1989 but kept meticulously recording pasture growth rates on different farms up to ~ 2007. Some field notes were lost, but datasets with gaps are still useful to assist monthly growth rates calculations. His valuable and extensive (almost 25 years) on farm field records have been retrieved, compiled, assembled, and digitised, to be saved electronically, and entered into the AgYields National Database hosted at Lincoln University. Part of this legacy dataset has been summarised and dry matter yields and growth rates calculated, consistent withprevious methods, to provide a quantified description of mean monthly pasture growth rates across the Bay of Plenty region, in New Zealand.

Effects of Vermicompost on Soil and Plant Health and Promoting Sustainable Agriculture

This review highlights the potential of vermicompost and its derived products as sustainable and eco-friendly solutions for enhancing production and pest management in grain crops. It assesses their impact comprehensively on crops such as maize, wheat, barley, rice, and pearl millet. Vermicompost improves soil quality, increases nutrient availability, boosts crop productivity, and enhances pest and disease tolerance. It acts as an organic fertilizer, enriching the soil with essential nutrients, humic acids, growth-regulating hormones, and enzymes, improving plant nutrition, photosynthesis, and overall crop quality. Furthermore, vermicompost shows promise in mitigating soil degradation and sequestering organic carbon while demonstrating the potential for pest management, including effectiveness against pests like fall armyworm (Spodoptera frugiperda). This review emphasizes the importance of integrated nutrient management and proper application strategies to maximize the benefits of vermicompost in grain crops. Factors such as the form and timing of application, efficacy against specific pests, and economic viability for different farming scales are discussed. Understanding these factors is crucial for successfully implementing and adopting vermicompost-based pest management strategies in grain crops. This review also explores the potential of vermicomposting as an eco-friendly and cost-effective solution to remediate organic contaminants, emerging contaminants, personal-care and pharmaceutical products, and microplastics. The review further identifies knowledge gaps and highlights the need for future studies to effectively utilize vermicompost and its derived products in cereal production for sustainable agriculture, contributing to global food security.

Molecular epidemiology and current management of Infectious Spleen and Kidney Necrosis Virus (ISKNV) infection in Ghanaian cultured tilapia

Infectious Spleen and Kidney Necrosis Virus (ISKNV) is globally gaining more attention, due to its highly significant economic impact on the aquaculture industry. In late 2018, unusually high levels of mortality (60–90%) was reported in some intensive tilapia cage culture systems on the Eastern bank of Lake Volta in Ghana. This resulted in the fold-up of several small and medium scale farms. Preliminary investigations confirmed the involvement of ISKNV, a viral pathogen noted for fatal systemic infections in many fish species. As a follow-up on the outbreak situation, and post-mass vaccination of affected fish farms, the need to investigate further the molecular epidemiology and phylogeography of the virus across Lake Volta became paramount. A multiplexed PCR assay to detect the virus and MinION™ nanopore sequencing of the Major Capsid Protein (MCP) were performed to investigate the presence and genotype of ISKNV in tilapia collected from 30 randomly selected farms at various geographical locations. ISKNV was found to be widely distributed across the lake and detected in 80% of farms with a reported average daily mortality of 40%. Fry and juvenile fish were the most affected, and approximately 50% of fish that tested positive were asymptomatic. These apparently healthy fish are likely contributors of virus transmission across farms. Phylogenetic analysis of the MCP revealed that all 35 isolates from 14 different farms distributed across the lake clustered with ISKNV clade I with 100% homology to isolates from the 2019 outbreak strain. Vaccination and heat-shock treatment; the two main specific interventions currently employed to control the viral pathogen have not achieved much success, and ISKNV remains a threat to the growth of the aquaculture industry in Ghana. The outcome of this study can be useful in improving fish health management and biosecurity policies in the aquaculture industry.

A new multispectral index for canopy nitrogen concentration applicable across growth stages in ryegrass and barley

Accurately monitoring Canopy Nitrogen Concentration (CNC) is a prerequisite for precision nitrogen (N) fertiliser management at the farm scale with carbon and N budgeting across the landscape and ecosystems. While many spectral indices have been proposed for CNC monitoring, their applicability and accuracy are often adversely affected by confounding factors such as aboveground biomass (AGB), crop type, growth stages, and environmental conditions, limiting their broader application and adoption; with AGB being one of the most dominant signals and confounding factors at canopy scale. The confounding effect can become more challenging as AGB is also physiologically linked with CNC across the growth stages. Additionally, the interplay between index form, selection of optimal wavebands and their bandwidths remains poorly understood for CNC index design. This study proposes robust and cost-effective 2- and 4-waveband multispectral (MS) CNC indices applicable across a wide range of crop conditions. We collected 449 canopy reflectance spectra (400–980 nm) together with corresponding CNC and AGB measurements across four growth stages of ryegrass (winter and summer), and five growth stages of barley (winter-spring) in Victoria, Australia, in 2018 and 2019. All possible waveband (400–980 nm) combinations revealed that the best combination varied between seasons and crop types. However, the visible spectrum, particularly the blue region, presented high and consistent performance. Bandwidths of 10–40 nm outperformed either very narrow (2 nm) or very broad bandwidths (80 nm). The newly developed 2-waveband index (416 and 442 nm with 10-nm bandwidth; R2 = 0.75 and NRMSE = 0.2) and 4-waveband index (512, 440, 414 and 588 nm with 40-nm bandwidth; R2 = 0.81 and NRMSE = 0.17) exhibited the best performance, while validation with an independent dataset (from a different growing period to those used in the model development) obtained NRMSE values of 0.25 and 0.24, respectively. The 4-waveband index provides enhanced performance and permits use of broader bandwidths than its 2-waveband counterpart.

Poverty Status and Scale Economies of Maize-based Farmers in Southwest, Nigeria

The study examines the relationship between poverty status and scale economies of maize-based farmers in Southwest, Nigeria. Primary data were sourced with the aid of a well-designed questionnaire and oral interview. A multistage sampling technique was used to randomly select 240 maize-based farmers in the area. The main data analysis used were Foster-Greer-Thorbecke (FGT) and the probit regression model. The FGT results showed that poverty incidence was prevalent among small-scale farmers across the cropping patterns. It further highlighted the potential of medium and large-scale farming operations in reducing poverty due to their capacity for higher income generation. Moreover, years of farming experience, access to credit, and larger farm sizes emerge as crucial factors in alleviating poverty among farmers using probit regression analysis. However, we noted the impact of certain variables, such as marital status and land acquisition, which can vary regionally and contextually. Therefore, by recognizing the role of farm scale and the various socio-economic factors at play, stakeholders can develop more effective strategies to improve the livelihoods of maize-based crop farmers and promote sustainable agricultural development.

University MOOC should be added with farmer interested sections and provide individualized service to adapt to farmer training.

Vegetables represent an important agricultural industry in China. New farmers and new technologies for vegetable production have emerged in recent years, which makes farmer training very necessary. On the other hand, massive open online courses (MOOCs) are currently widely used in universities. The purpose of this study is to investigate the importance of different sections of a university MOOC focused on olericulture to farmers with different demographic characteristics and provide a basis to improve university MOOCs for farmer training. The survey results suggest that the age, education level, gender, farmer scale, facility type and profit of farmer learners are important factors determining evaluations of the importance of different MOOC sections, indicating that services customized to different farmer populations are necessary. Among different sections of MOOC "Olericulture", farmers with younger age, higher education, larger farm, more advanced facility and more profit were more interesting in sections include cultural, social and theoretical knowledge, and less interesting in practical skill sections. Based on the survey, eight new sections including one marketing subsection (new agricultural supplies and market news), one social subsection (laws and regulations), two practical subsections (practice videos, photos and videos from other farms), and three comprehensive subsections (discussion of practical issues, mechanization, and smart olericulture) were added to the original MOOC, and the results indicate that this improvement is efficient in enhancing the importance evaluations and profits of all farmer learners, especially among those with high education levels.

Analysis of cassava farming efficiency as a supporter of post-COVID-19 rural economic changes in wonogiri regency

Cassava farming, as an important commodity in agriculture in Wonogiri Regency, is necessary for structural changes in the rural economy of Wonogiri Regency in postCOVID-19 conditions. This study aims to determine the level of efficiency and analyse the elasticity of cassava farming. The Data Envelopment Analysis is used in analysing the efficiency of cassava farming, while multiple linear regression analysis is used in analysing production elasticity. The results of Data Envelopment Analysis with an inputoriented model in the study show that farmers have a level of technical efficiency of 64.6%, allocative efficiency of 47.1%, and economic efficiency of 30%. Farmers who are not efficient can increase their efficiency value by using cassava farming inputs. The elasticity of the production of seedlings, manure, SP36 fertilizer, Phonska fertilizer, urea fertilizer, pesticides, and labour is positive. The scale of business results show that farming is in a condition of increasing returns to scale. The addition of production factors has a positive effect on cassava production. However, if production factors are not considered, it will result in additional inputs, decreasing yields. Optimal use of inputs can increase the production scale of cassava farming and increase efficiency. This study can be helpful for the farmers to increase the efficiency level through the efficient use of inputs. They can be helpful for the government in the formulation of rural development plans with farming development and implementing policies to increase the efficiency