Improved Land Management Practices Research Articles

Accurate Quantification of 0–30 cm Soil Organic Carbon in Croplands over the Continental United States Using Machine Learning

Increases in organic carbon within agricultural soils are widely recognized as a “negative emission” that removes CO2 from the atmosphere. Accurate quantification of soil organic carbon (SOC) to a certain depth in the spatial domain is critical for the effective implementation of improved land management practices in croplands. Currently, there is a lack of understanding regarding what depth strategy should be used to estimate SOC at 0–30 cm when sample datasets come from multiple depths. Furthermore, few studies have examined depth strategies for mapping SOC at the agricultural management level (i.e., field level), opting instead for point-based analysis. Here, three types of approaches with different depth strategies were evaluated for their ability to quantify 0–30 cm SOC content based on soil samples from 0–5 (surface), 5–30 (subsurface), and 0–30 cm (full column). These approaches involved the generalized additive model and machine learning techniques, i.e., artificial neural networks, random forest, and XGBoost. The soil samples used for the model evaluation and selection consisted of the newly collected samples in 2020–2022 and the Rapid Carbon Assessment (RaCA) legacy samples collected in 2010–2011. Environmental covariates corresponding to these SOC measurements were used in model training, including long-term physical climate, short-term weather, topographic and edaphic, and remotely sensed variables. Among the models evaluated in this study, the XGB regression model with a full column depth assignment strategy yielded the best prediction performance for 0–30 cm SOC content, with an r2 (squared Pearson correlation coefficient) of 0.48, an RMSE (root mean square error) of 0.29%, an ME (mean error) of 0.06%, an MAE of 0.25%, and an MEC (modeling efficiency coefficient) of 0.36 at the pixel level and an r2 of 0.64, an RMSE of 0.32%, an ME of −0.20%, an MAE of 0.28%, and an MEC of 0.48 at the field level. This study highlights that machine learning models with a full column depth strategy should be used to quantify 0–30 cm SOC content in agricultural soils over the continental United States (CONUS).

Willingness to Pay for Watershed Services by Downstream Water Users in Babati District, Tanzania

Payment for Ecosystem Services promotes watershed management through Payment for Watershed Services. It encourages improved land management practices in upstream areas to enhance the quantity and quality of water downstream. The Nou Forest Reserve in Babati district covers Lake Manyara's headwaters. Its rivers are the primary water source for the area's inhabitants. However, there have been reports of declining water quality and quantity, presenting an opportunity to introduce payment for watershed services for Nou Forest Reserve conservation and management. The present study was conducted to assess the level of awareness among downstream water users about the importance of watersheds in providing sustainable water supply. Using the Contingent Valuation Method, the study estimated the communities’ willingness to pay for improved watershed services, analysed factors influencing capacity to pay, and examined possible operational modes for implementing payment mechanisms. A total of 155 domestic water users and 50 non-domestic water users were interviewed. It was found that 71% of domestic water users and 82% of non-domestic water users were willing to pay for improved watershed services, with a mean willingness to pay estimated at TAS 1261 per user/year for domestic water users and TAS 112322 per user/year for non-domestic water users. Factors such as gender, occupation, education, and farm size significantly (P<0.05) influenced water users' willingness to pay. Income was a significant factor in the willingness to pay for non-domestic water users, but it was not significant for domestic water users. The current study suggests that downstream water users in Babati district, who act as watershed service buyers, could collect a water user fee based on estimated amounts. This approach would help address declining water quality and quantity through improved watershed management and thus enhance watershed conservation and management.

Assessment of land use management and its effect on soil quality and carbon stock in Ebonyi State, Southeast Nigeria

Evaluating soil quality (SQ) resulting from land management use impact is important for soil carbon (C) monitoring, land sustainability and suitability. However, the data in less developed regions of Africa like Nigeria is scarce, limiting our understanding at global scale. The study evaluated land management use on soil quality in Ebonyi State, Nigeria, a representative region of Africa. Soil samples were collected in 2021 and resampled in 2022 from regions including five land use managements (FS = forest soil; GLS = grass land soil; ACS = alley cropping Soil; SDS = sewage dump-soils; CCS = continuously cultivated soil). Soil physical and chemical properties were analyzed and discussed. The results shows that soil physical properties (bulk density, hydraulic conductivity, aggregate stability) were significantly (P < 0.05) influenced by land use management. Moderate to high bulk density, very low hydraulic conductivity (HC), and low aggregate stability were observed across land management, suggesting potential inhibition to root penetration, poor aeration, and water infiltration. Improved land management practices such as planting of cover crops either for re-grassing or addition of crop residues could be adopted as conservative options for increasing soil quality and encourage additional soil C. Soil pH decreased with the increase in soil depth in all land uses for both years. A higher soil pH of 6.78 (slightly acidic) was seen in SDS and lower mean 6.0 (moderately acidic) was obtained in CCS at 0–20 cm in 2021. The average mean nitrogen content was rated “very high” (0.81 g kg−1 and 0.69 g kg−1) in 2021 and 2022 respectively, suggesting nitrogen might not be a limiting factor for plant growth in the region. During the 2021 and 2022 study periods, the overall average mean C stock were 12.71 g kg−1 and 15.87 g kg−1 respectively suggesting 3.1 g kg−1 C stock increment in 2022. Soil inorganic C also increased by 9.86 g cm−2 in 2022. The study provided crucial information about how land management use affected soil physico-chemical properties including C stock and suggested that C stock could be improved by adopting appropriate land management use practices. The results fill a data gap in under-studied regions, but also facilitate potential land management practices.

Geospatial Land Classification Via Advanced Image Processing using CNN

High resolution analysis of remote sensing images is pivotal for various classification including land use determination, environmental detection, environmental planning and geospatial object recognition. This paper introduces a robust method for categorizing satellite images into distinct groups, facilitating accurate classification for global geographical areas. It includes image compression, image preprocessing, image segmentation and feature extraction. This innovative approach enables precise identification and understanding of different areas, contributing to optimize resource allocation and improved land management practices in agriculture. CNN is the classifier that is employed in this experiment. The outcome demonstrates that our suggested strategy offers excellent accuracy, outperforming many recently published publications.

Economic efficiency of using internal land management on the basis of agroindustrial enterprises

The relevance of this study lies in the specific context of the country, where the state plays a crucial role in the development and management of the agricultural sector. With the increasing development of agroindustrial complexes and the need for efficient use of agricultural land, the state has a primary responsibility to ensure optimal utilization of these resources. The purpose of the study is to investigate and compare models of intrafarm land use on the basis of agroindustrial complexes both in the territory of the Republic of Kazakhstan and in the United States as well as in countries of Asia and the European Union. In the furtherance of this goal, the following methods were used: literature review, SWOT analysis, data analysis, case studies and comparative analysis to examine the land use management (LUM) system in Kazakhstan. Specifically, to identify indicators of the economic efficiency of intrafarm land management, the criterion of national economic efficiency was used by comparing costs and benefits in the adoption of various decisions. The study analysed the operation of the land management mechanism in Kazakhstan and proposed innovative solutions on the basis of successful examples from other countries. The manuscript's contribution to the academic dialogue on sustainable land use can provide valuable information and insights for policymakers and scholars interested in improving land management practices.

Contrasting Effects of Grazing in Shaping the Seasonal Trajectory of Foliar Fungal Endophyte Communities on Two Semiarid Grassland Species.

Fungal endophytes are harboured in the leaves of every individual plant host and contribute to plant health, leaf senescence, and early decomposition. In grasslands, fungal endophytes and their hosts often coexist with large herbivores. However, the influence of grazing by large herbivores on foliar fungal endophyte communities remains largely unexplored. We conducted a long-term (18 yr) grazing experiment to explore the effects of grazing on the community composition and diversity of the foliar fungal endophytes of two perennial grassland species (i.e., Artemisia capillaris and Stipa bungeana) across one growing season. Grazing significantly increased the mean fungal alpha diversity of A. capillaris in the early season. In contrast, grazing significantly reduced the mean fungal alpha diversity of endophytic fungi of S. bungeana in the late season. Grazing, growing season, and their interactions concurrently structured the community composition of the foliar fungal endophytes of both plant species. However, growing season consistently outperformed grazing and environmental factors in shaping the community composition and diversity of both plant species. Overall, our findings demonstrate that the foliar endophytic fungal community diversity and composition differed in response to grazing between A. capillaris and S. bungeana during one growing season. The focus on this difference will enhance our understanding of grazing's impact on ecological systems and improve land management practices in grazing regions. This variation in the effects of leaf nutrients and plant community characteristics on foliar endophytic fungal community diversity and composition may have a pronounced impact on plant health and plant-fungal interactions.

Land Fragmentation and Socio-Economic Wellbeing

Land fragmentation results in reduced agricultural productivity, lack of efficiency, and diminished viability of the land. This study investigates land fragmentation's causes and socio-economic impacts, aiming to develop a conceptual model. Thematic analysis was employed to undertake a systematic literature review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method. The findings indicated that land fragmentation resulted in disorganization regarding location and space. This study guides land authorities and urban planners in providing fundamental knowledge to improve land management practices.

Framework for rainfall-triggered landslide-prone critical infrastructure zonation

Rainfall-induced landslides cause frequent disruptions to critical infrastructure in mountainous countries. Climate change is altering rainfall patterns and localizing extreme rainfall events, increasing the occurrence of landslides. For planning climate-resilient critical infrastructure in landslide-prone regions, it is urgent to understand the changing landslide susceptibility in relation to changing rainfall extremes and spatially overlay them with critical infrastructure to determine risk zones. As such, areas requiring financial reinforcements can be prioritized. In this paper, we develop a framework linking changing rainfall extremes to landslide susceptibility and intensity of critical infrastructure — exemplified on a national scale using Nepal as a case study. First, we define a set of 21 different unique rainfall indices that describe extreme and localized rainfall. Second, we prepare a new annual (2016–2020) inventory of 107,900 landslides in Nepal mapped on PlanetScope satellite imagery. Next, we prepare a landslide susceptibility map by training a random forest model using the collected extreme rainfall indices and landslide locations in combination with spatial data on topography. Fourth, we construct a gridded critical infrastructure spatial density map that quantifies the intensity of infrastructure (i.e., transportation, energy, telecommunication, waste, water, health, and education) at each grid location using OpenStreetMap. The landslide susceptibility map classified Nepal's topography into low (36 %), medium (33 %), and (32 %) high rainfall-triggered landslide susceptibility zones. The landslide susceptibility map had an average area under the receiver characteristic curve value of 0.94. Finally, we overlay the landslide susceptibility map with the critical infrastructure intensity to identify areas needing financial reinforcement. Our framework reasonably mapped critical infrastructure hotspots in Nepal prone to landslides on a 1 km grid. The hotspots are mainly concentrated along major national highways and in provinces 4, 3, and 1, highlighting the need for improved land management practices. These hotspots need spatial prioritization regarding climate-resilient critical infrastructure financing and slope conservation policies. The research data, output maps, and code are publicly released via an ArcGIS WebApp and GitHub repository. The framework is scalable and can be used for developing infrastructure financing strategies for landslide mountain regions and countries.

Soil science challenges—An interdisciplinary overview of current and future topics

AbstractThis editorial was written by early career scientists in soil science and gives an overview of the articles published in the special issue “Soil Science Challenges—An Interdisciplinary Overview of Current and Future Topics” on the occasion of the 100th anniversary of Journal of Plant Nutrition and Soil Science. A broad range of articles addressing soil carbon dynamics from the microscale to landscape scale, multi‐dimensional modeling, improved land management practices, nutrient cycles, soil hydrology, plastic in soils, and interdisciplinarity of soil science is covered in this issue.

Increasing uptake of improved land management practice to benefit environment and landholders: insights through a transaction cost lens

Transaction costs, related to either investigating improved land management practices (ILMP), engaging in adoption support programs for these practices and/or implementing changes on-ground, create barriers to ILMP adoption. Perceived and actual transaction costs have long been hypothesised as a potential barrier to grazier adoption of ILMPs in catchments to the Great Barrier Reef. Applying a framework derived from transaction cost theory, we assess this hypothesis. Through semi-structured interviews of a sample of participants in two ILMP programs, we find that ILMP adoption support program characteristics have a large influence on perceived and actual transaction costs of landholders seeking to engage in ILMP programs or adopt ILMPs. The importance of establishing and nurturing relationships between landholders and extension officers was also highlighted as critical to reducing landholder transaction costs. The degree to which relationships reduce transaction costs demonstrates the importance of fostering landholder leadership in ILMP program design as well as targeted extension in supporting adoption.

Decoupling between circulation pattern and dust path since the last glacial in the Songnen Plain, NE China: Insights from quantitative provenance reconstruction of the Harbin dust sediments

• Potential sources of the Harbin loess during the last glacial and modern dust were quantitatively tracked. • The sandy lands of NE China figure importantly in acting as a dust transfer station. • Decoupling between circulation patterns and dust export since the last glacial in the Songnen Plain were revealed. • The SW-direction sandy land of the Songnen Plain should be treated as a priority for environmental management. Knowledge of the provenance of dust deposits in the easternmost margin of the Eurasian loess belt is essential for understanding the connection between circulation patterns and dust source-to-sink route in the Songnen Plain, NE China. Here, a total of 131 samples, from the loess-paleosol sequence since the last glacial (20) and the modern dust-storm sediments (7) in Harbin area together with potential dust source areas (104), were collected for elemental geochemical analysis to quantify the source apportionment and compare the performance of the Frequentist and Bayesian models. Fourteen geochemical properties (V, Zn, Ga, Sr, Mo, Ba, Pb, Y/Ta, MREE N /MREE N *, Th/Sc, Th/U, La/Sc, Zr/Hf and Co/Th) were selected as the optimum composite fingerprint after a range test, non-parametric Kruskal-Wallis H-test and stepwise discriminant function analysis. Based on both the models, the source contributions to the loess sequence and dust-storm deposits were in the following order: southwestern Songnen Sandy Land (57–95%, 49–97%), Horqin Sandy Land and Onqin Daga Sandy Land (2–43%, 0–31%), northwestern Songnen Sandy Land (0–21%, 0–20%) and Hulun Buir Sandy Land (0%, 0–8%). Following the goodness-of-fit and virtual mixtures, combined with root mean square error and mean absolute error, we argue that the Frequentist model is slightly more accurate than the Bayesian model in quantifying dust sources. The sandy lands figure importantly in acting as a dust transfer station. The comparison between the loess sequence and modern dust-storm source reconstructions reveals a decoupling between circulation pattern (northwesterly wind domination in the glacial) and dust path (dominantly southwestern direction), and small areas, high vegetation coverage and topographical barrier are considered to be the main reasons for the significantly limited dust emission in the NW-direction source area. Finally, the study highlights that improving land management practices in the SW-direction but not NW-direction sandy land may help ameliorate the effects of the Harbin dust pollution.

European Ground Squirrels at the Edge: Current Distribution Status and Anticipated Impact of Climate on Europe’s Southernmost Population

The European ground squirrel (Spermophilus citellus) is an endangered semifossorial small mammal of grassland/agricultural ecosystems. In the last few decades, the species’ population has declined throughout its range in Europe. The Greek populations represent the southernmost limit of the species’ range and are notably small, scattered, and located mainly in human-modified areas. The goal of the present research is to understand the environmental and anthropogenic variables associated with its distribution in the Mediterranean habitats, assess possible drivers of observed local extinctions, and propose conservation and land-use management actions in light of near-future climate change scenarios. We used presence records since 2000 across all known populations (107 colonies) and maximum entropy conditional probability models (MaxEnt) to calculate both the habitat suitability (bioclimatic variables) and habitat availability (anthropogenic/land-use variables) within the European ground squirrel’s historical range in northern Greece. We report a projected 39% to 94.3% decrease in habitat suitability by 2040–2060 due to climate change. Based on our findings, we provide guidance by proposing nascent conservation actions to protect the few existing colonies in Greece via improved land management practices and identify in situ climate refugia that could be prioritized as sites for future reintroductions.

Modeling long-term attainable soil organic carbon sequestration across the highlands of Ethiopia

The objectives of this study across the highlands of Ethiopia were: (i) to characterize the association between soil organic carbon (SOC) stocks and biophysical variables and (ii) to model and map attainable SOC sequestration associated with five improved land management practices. The spatial distribution of the SOC stock was studied using a multiple linear regression model driven by eight biophysical predictors. A widely used SOC model (RothC) was then used to model changes in SOC over the next 20–50 years of improved land management. Simulations were driven by the derived SOC stocks, pH and clay contents that are available in the ISRIC soils database at 250 m resolution and climate data from the “Enhancing National Climate Services Initiative” database. Organic carbon inputs to the model were estimated from the “Improved Crop Varieties Yield Register” of the Ministry of Agriculture and Livestock Resource and the Central Statistics Authority. After 50 years of conservation tillage with 80% of available manure applied to cultivated land, the total SOC stock increased by 169,182,174 t, which is 2.8 times higher than the stock increase with only 50% of available manure applied. Introduction of improved pasture species and measures to control soil erosion was an important source of net carbon sequestration in grasslands. Afforestation and reforestation of degraded landscapes and protection of natural ecosystems further increased soil carbon. This highlights the importance of improved land management practices to SOC sequestration, which in turn could enhance agricultural productivity, food security and sustainable development.

Motivators and barriers to adoption of Improved Land Management Practices. A focus on practice change for water quality improvement in Great Barrier Reef catchments

To protect and improve water quality in the Great Barrier Reef, the Queensland Government's Reef 2050 Water Quality Improvement Plan targets that 90% of sugarcane, horticulture, cropping and grazing lands in priority areas be managed using best management practices for sediment, nutrient and pesticides by 2025. Progress towards this target is insufficient and variable across catchments and industries. The motivation to adopt improvements in management practices is heavily influenced by social, economic, cultural and institutional dimensions. In this paper we synthesise the literature on how these human dimensions influence decision making for land management practice and highlight where future investment could be focussed. We highlight that focussing on —1) investigating systems to support landholder decision making under climate uncertainty (risk); 2) generating a better understanding of the extent and drivers of landholder transaction cost; 3) understanding if there are competing ‘right’ ways to farm; and 4) improving understanding of the social processes, trust and power dynamics within GBR industries and what these means for practice change— could improve practice change uptake in the future.

Projected changes in monthly baseflow across the U.S. Midwest

AbstractBaseflow is an essential water resource because it is the groundwater discharged to streams and represents long‐term storage. Understanding its future changes is a major concern for water supply and ecosystem health. This study examines the impacts of climate and agriculture on monthly baseflow in the U.S. Midwest through the end of the 21st century. We use a statistical approach to evaluate three scenarios. The first scenario is based on downscaled and bias corrected global climate model (GCM) outputs and the representative concentration pathway (RCP) 8.5, and agriculture is held constant (and equal to the mean from 2013 to 2019). In the next two scenarios, climate is held constant (2010–2019) to isolate the impact of agriculture on baseflow. In terms of agricultural changes, we consider scenarios representative of either increases or decreases with respect to the production of corn and soybeans. Changes in the climate system point to increases in baseflow that are likely a result of increased precipitation and antecedent wetness. Seasonally, warmer temperature in the winter and spring (i.e., February to July) is expected to cause increasing trends in baseflow. Changes in land use showed that agriculture would either mitigate the impact of climate change or possibly amplify it. Expanding corn and soybean areas would increase baseflow in the Corn Belt region. On the other hand, converting land back to perennial vegetation would decrease baseflow throughout the entire year. Despite its simplicity, this study can provide basic information to understand where to expect adverse effects on baseflow and thus improve land management practices in those areas.

Assessing the Impact of Land Use and Climate Change on Surface Runoff Response Using Gridded Observations and SWAT+

The Anthropocene period is characterised by a general demographic shift from rural communities to urban centres that transform the predominantly wild global landscape into mostly cultivated land and cities. In addition to climate change, there are increased uncertainties in the water balance and these feedbacks cannot be modelled accurately due to scarce or incomplete in situ data. In African catchments with limited current and historical climate data, precise modelling of potential runoff regimes is difficult, but a growing number of model applications indicate that useful simulations are feasible. In this study, we used the new generation of soil and water assessment tool (SWAT) dubbed SWAT+ to assess the viability of using high resolution gridded data as an alternative to station observations to investigate surface runoff response to continuous land use change and future climate change. Simultaneously, under two representative concentration pathways (RCP4.5 and RCP8.5), six regional climate models (RCMs) from the Coordinated Regional Climate Downscaling Experiment Program (CORDEX) and their ensemble were evaluated for model skill and systematic biases and the best performing model was selected. The gridded data predicted streamflow accurately with a Nash–Sutcliffe efficiency greater than 0.89 in both calibration and validation phases. The analysis results show that further conversion of grasslands and forests to agriculture and urban areas doubled the runoff depth between 1984 and 2016. Climate projections predict a decline in March–May rainfall and an increase in the October–December season. Mean temperatures are expected to rise by about 1.3–1.5 °C under RCP4.5 and about 2.6–3.5 °C under RCP8.5 by 2100. Compared to the 2010–2016 period, simulated surface runoff response to climate change showed a decline under RCP4.5 and an increase under RCP8.5. In contrast, the combine effects of land use change and climate change simulated a steady increase in surface runoff under both scenarios. This suggests that the land use influence on the surface runoff response is more significant than that of climate change. The study results highlight the reliability of gridded data as an alternative to instrumental measurements in limited or missing data cases. More weight should be given to improving land management practices to counter the imminent increase in the surface runoff to avoid an increase in non-point source pollution, erosion, and flooding in the urban watersheds.

A Review Paper on the Role of Terrestrial Carbon Stocks for Climate Change Mitigation Mechanisms

Global warming is among the greatest terrible horrors of the modern times. The global carbon cycle is taking place in three main reservoirs (the oceans, the atmosphere, and terrestrial systems), which store carbon in different forms and varying amounts. The forest ecosystems have large potential to act as a temporary and long-term carbon (C) pool. Global forest vegetation stores 283 Gt of carbon in its biomass, 38 Gt in dead wood and 317 Gt in soils (top 30 cm) and litter. Globally, the litter C pool accounts for an estimated 5% (43 Pg) of all forest ecosystem C stocks. Agroforestry practices can reduce or remove significant amounts of GHGs through increased carbon storage in biomass above-ground and below-ground and in soil organic carbon. Roots are an important part of the C balance, because they transfer large amounts of C into the soil. Grasslands, including rangelands, shrublands, pastureland, and cropland sown with pasture and fodder crops, covered approximately 3.5 billion ha in 2000, representing 26 percent of the world land area and 70 percent of the world agricultural area, and containing about 20 percent of the world’s soil carbon stocks. Soils are the largest carbon reservoirs of the terrestrial carbon cycle 1500–1550 Gt of organic soil carbon and soil inorganic C approximate 750 Gt both to 1 m depth. On a global scale, carbon loss from soils is mainly associated with soil degradation, including accelerated erosion and mineralization, and land use change, and has amounted to 78+/- 12 Gt since 1850. The idea of Reducing Emissions from Deforestation and forest Degradation (REDD) was conceived by United Nations Framework Convention on Climate Change (UNFCCC) as the main carbon emission reduction mechanism by developing countries. The implementation of improved land management practices to build up carbon stocks in terrestrial ecosystems is a proven technology for reducing the concentration of carbon dioxide (CO2) in the atmosphere – offsetting emissions from other sources and drawing down atmospheric CO2. Keywords: Carbon sequestration, Terrestrial carbon, Global warming and Carbon stocks. DOI: 10.7176/JEES/10-8-04 Publication date: August 31 st 2020

Agricultural productivity in relation to climate and cropland management in West Africa

The climate of West Africa is expected to become more arid due to increased temperature and uncertain rainfall regimes, while its population is expected to grow faster than the rest of the world. As such, increased demand for food will likely coincide with declines in agricultural production in a region where severe undernutrition already occurs. Here, we attempt to discriminate between the impacts of climate and other factors (e.g. land management/degradation) on crop production across West Africa using satellite remote sensing. We identify trends in the land surface phenology and climate of West African croplands between 2000 and 2018. Using the combination of a an attribution framework and residual trend anlaysis, we discriminate between climate and other impacts on crop productivity. The combined effect of rainfall, land surface temperature and solar radiation explains approximately 40% of the variation in cropland productivity over West Africa at the 95% significance level. The largest proportions of croplands with greening trends were observed in Mali, Niger and Burkina Faso, and the largest proportions with browning trends were in Nigeria, The Gambia and Benin. Climate was responsible for 52% of the greening trends and 25% of the browning trends. Within the other driving factors, changes in phenology explained 18% of the greening and 37% of the browning trends across the region, the use of inputs and irrigation explained 30% of the greening trends and land degradation 38% of the browning trends. These findings have implications for adaptation policies as we map out areas in need of improved land management practices and those where it has proven to be successful.

Determinants of Potato Marketed Surplus Among Smallholder Farmers in Sekela District, West Gojjam Zone of Amhara Region, Ethiopia

For Sekela Woreda smallholder potato producers, potato has significant contribution for consumption at home which increase food security and in generating cash income. Therefore, enhancing potato producers’ access to market and linking them to most beneficial outlets is a key issue needed in the study area. This paper was aimed to identify factors affecting marketed surplus potato farmers using survey data collected from randomly selected 130 farmers from six kebeles were randomly and proportionately sampled to collect both secondary and primary sources. Descriptive statistics was used for characterizing farmers and econometrics analysis was used for identifying determinants of marketed surplus. The result of econometric analysis from OLS marketed surplus model revealed that distance to the nearest market, use of improved seed, frequency of extension contact, area of land allocated for potato and yield of potato significantly determined quantity of potato supplied to the market. Based on the finding the government and other stakeholders need to focus on strengthening improved seed access, strengthening rural-urban infrastructure, expanding market access, improving land management practices and yield through strengthening extension service in order to accelerate market chain development. Keywords: Marketed surplus, Potato, Multiple linear regression DOI : 10.7176/FSQM/83-06

Determinants of Potato Marketed Surplus among Smallholder Farmers in Sekela District, West Gojjam Zone of Amhara Region, Ethiopia

For Sekela Woreda smallholder potato producers, potato has significant contribution for consumption at home which increase food security and in generating cash income. Therefore, enhancing potato producers’ access to market and linking them to most beneficial outlets is a key issue needed in the study area. This paper was aimed to identify factors affecting marketed surplus potato farmers using survey data collected from randomly selected 130 farmers from six kebeles were randomly and proportionately sampled to collect both secondary and primary sources. Descriptive statistics was used for characterizing farmers and econometrics analysis was used for identifying determinants of marketed surplus. The result of econometric analysis from OLS marketed surplus model revealed that distance to the nearest market, use of improved seed, frequency of extension contact, area of land allocated for potato and yield of potato significantly determined quantity of potato supplied to the market. Based on the finding the government and other stakeholders need to focus on strengthening improved seed access, strengthening rural-urban infrastructure, expanding market access, improving land management practices and yield through strengthening extension service in order to accelerate market chain development. Keywords: Marketed surplus, Potato, Multiple linear regression DOI : 10.7176/FSQM/83-06