<p> Soybean seed cost has dramatically increased in recent decades which has led to producer interest in lowering input cost through reductions in seeding rate. Fifty-eight seeding rate trials of soybean were conducted at field-scale in Indiana from 2010 to 2021 to update recommendations of seeding rates and plant population. The objectives were to determine the agronomic optimal seeding rate (AOSR) and plant population (AOPP) based on planting equipment, tillage practices, and planting date. Economic optimal seeding rate (EOSR) was also determined based on these field scenarios. Harvest AOPP was not influenced by planting equipment (~212,000 plants ha-1) or tillage (~239,000 plants ha-1), but AOSR varied. Soybean seeded with a row-crop planter optimized grain yield with 352,600 seeds ha-1; whereas, the grain drill required 75,200 more seeds ha-1. Soybean seeded into conventional tillage maximized grain yield at 380,400 seeds ha-1; whereas, under no-till conditions 41,400 more seeds ha-1 were required. Timely planting required 417,300 seeds ha-1 to optimize grain yield, which resulted in harvest AOPP of 216,700 plants ha-1. Conversely, late plantings required 102,800 fewer seeds ha-1 but 36,200 more plants ha-1 than timely planting. Depending on seed cost and soybean market price, seeding rates could be reduced 13,700 to 92,800 seeds ha-1 below AOSR to maximize profit.</p> <p>Secondly, digital imagery with high spatial resolution was collected with an unmanned aerial vehicle (UAV) to develop a simple and practical method to segment soybean from non-plant pixels. The best vegetation indices were selected to segment young soybean plants (VC to V6). Two field-scale trials of soybean were planted in 2020 with the agronomic trial design of two varieties x five seeding rates with three replications. The imagery was collected during this period as it coincides with the time for determining whether a soybean stand should be replanted. Five relative vegetative indices based on the red, green, and blue (RGB) imagery were evaluated: excess greenness index (ExG), excess redness index (ExR), green leaf index (GLI), normalized green-red difference index (NGRDI) and visible atmospheric resistance index (VARI). Both GLI and ExG were superior in overall accuracy compared to all other vegetative indices with very small soybean plants (VC to V1 growth stages). VARI and NGRDI had relatively poor overall accuracy at VC and V1, but had similar overall accuracy to GLI as soybean plants grew larger (V2 to V6 growth stages). Across all growth stages and locations, ExR performed the poorest. Moreover, GLI had consistent performance across the range of growth stages, suggesting its suitability for early soybean stand assessment methods.</p> <p>Six field-scale trials were established in 2020 and 2021 in Indiana with two varieties seeded from 123,000 to 618,000 seeds ha-1. Canopy cover was calculated using GLI to create binary segmentation of plant pixels and non-plant pixels. UAV-derived canopy cover measurements were correlated with plant population of soybean from VC to V4 and growing degree days (GDD) after planting. Yield potential (75, 80, 85, 90, 95, 100%) was correlated with canopy cover from VC to V4 and GDD after planting. Canopy cover of 2.1, 5.0, 8.9 and 13.8% by 150, 250, 350, and 450 GDD°C after planting, respectively, would maximize yield. Canopy cover for 75% yield potential was one-fourth as much as the 100% yield potential. Recommended threshold for replant decisions should be based on canopy cover to attain 95% yield potential. Field observations below a canopy cover of 1.8, 4.2, 7.4, and 11.5% canopy cover by 150, 250, 350, and 450 GDD°C after planting respectively, would consider replanting. </p>

<p>The agricultural data landscape is largely dysfunctional because of the industry’s highvariability  in  scale,  scope,  technological  adoption,  and  relationships.   Integrated  data  andmodels of agricultural sub-systems could be used to advance decision-making, but interoperability  challenges  prevent  successful  innovation.   In  this  work,  temporal  and  geospatial indexing  strategies  and  aggregation  were  explored  toward  the  development  of  functional data  structures  for  soils,  weather,  solar,  and  machinery-collected  yield  data  that  enhance data context, scalability, and sharability.</p> <p>The data structures were then employed in the creation of decision support tools including web-based  applications  and  visualizations.   One  such  tool  leveraged  a  geospatial  indexing technique called geohashing to visualize dense yield data and measure the outcomes of on-farm yield trials.  Additionally, the proposed scalable, open-standard data structures were used to drive a soil water balance model that can provide insights into soil moisture conditions critical to farm planning, logistics, and irrigation.  The model integrates SSURGO soil data,weather data from the Applied Climate Information System, and solar data from the National Solar Radiation Database in order to compute a soil water balance, returning values including runoff, evaporation, and soil moisture in an automated, continuous, and incremental manner.</p> <p>The approach leveraged the Open Ag Data Alliance framework to demonstrate how the data structures can be delivered through sharable Representational State Transfer Application Programming Interfaces and to run the model in a service-oriented manner such that it can be operated continuously and incrementally, which is essential for driving real-time decision support tools.  The implementations rely heavily on the Javascript Object Notation data schemas leveraged by Javascript/Typescript front-end web applications and back-end services delivered through Docker containers.  The approach embraces modular coding concepts and several levels of open source utility packages were published for interacting with data sources and supporting the service-based operations.</p> <p>By making use of the strategies laid out by this framework, industry and research canenhance data-based decision making through models and tools.  Developers and researchers will  be  better  equipped  to  take  on  the  data  wrangling  tasks  involved  in  retrieving  and parsing unfamiliar datasets, moving them throughout information technology systems, and understanding those datasets down to a semantic level.</p>

For the majority of rural people, agricultural activities continue to be one of their main livelihood strategies. Production of food crops is not dependent on any formally acquired knowledge of farming but is solely based on indigenous agricultural knowledge passed from generation to generation through experience and careful observations. Resource-poor farmers, especially in rural areas, follow traditional farming methods to produce their food crops and these are specifically tailored to suit their environments. Embo is located in rural KwaZulu-Natal and falls under Mkhambathini municipality. The area is characterised by small-holder farmers who are mainly Ezemvelo Farmers Organisation (EFO) members. The purpose of this study was to review the farming practices followed by farmers in respect of food crop production and secondly to understand what influences the continual practice of such farming practices among rural farming communities of Embo in KwaZulu-Natal especially the EFO farmers. The study looked at what farmers see as traditional agriculture. A combination of qualitative and quantitative methods was used for the study. Data collection methods included participatory observations, semi structured face-to-face interviews and focus group discussions. The study found that farmers are happy to follow traditional farming methods to produce their food crops. Traditional farming tools such as the hoe and animal traction are the main implements used to prepare land. Household members are the main source of farm labour with men mainly responsible for ploughing activities while the bulk of planting, weeding and harvesting activities is the responsibility of women. Cropping patterns include intercropping and crop rotation with common crops being amadumbe, beans, maize and sweet potatoes. The majority of these crops are produced for both subsistence and commercial reasons. Amadumbe is an important commercial crop produced organically. Crop protection against pests is done through traditional methods where farmers mix some concoctions made from locally available resource in order to minimise losses. Kraal manure is the main soil fertility strategy followed by farmers. Landrace seeds are the main seed type used by the farmers. Local seed sources include own production and asking from other farmers. Crops with good qualities are selected in fields and maintained as seeds, which are then stored separate from those for home consumption. Harvesting is mainly done manually and for important crops such as tubers with short shelf lives, harvested through piecemeal methods. Farmers are able to generate some income from their efforts and this contributes to local economies and household food security. Farmers value their farming methods and see their farming as efficient despite challenges. There is a need to consider developing labour support groups in order to ease the burden of labour especially by women. In view of the importance of traditional farming in the lives of rural people, it is important that agricultural scientists and extension officers take into consideration the knowledge farmers already have so as to develop technologies suitable for farmers’ environments. / Thesis (M.Soc.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2008.

Although conventional or scientific farming practices have been encouraged and promoted by state and other agencies, rural and resource poorfarmers have increasingly resorted to indigenous farming practices. This study was undertaken to test the hypothesis that indigenous farming practices are not only environmentalfriendly, but are more profitable than conventional practices. A conceptual framework for testing the hypothesis was formulated based on a comparison of Margins above Specified Cost of indigenous and conventional farming practices. The data required were identified and a methodology for data collection and analysis was designed. The research methodology included a literature review, a GIS based sample scheme designedfor data collection and statistical analysis. As a major feature of this component of the mini-dissertation, the literature review reveals that indigenous farming practices have positive impact on the environment by improving soil through mulching, composting and use of non-toxic control ofpests and diseases. On the other hand the review reveals that conventional practices can impact negatively on the environment. / Thesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2005.

The grazing management project in the Okhombe ward of the Amazizi Tribal Authority formed part of the National Department of Agriculture's LandCare program to address communal natural resource management issues. Okhombe land is communal whereby every member of the community is the legal owner of the rangeland with individual ownership of stock with the chieftaincy playing a major role in land allocation. In order to avoid critics of the past and address the top-down approach of the past interventions, a participatory approach was conducted in the planning and implementation of the grazing system. The service providers held a series of visioning workshops with the community in an effort to better understand community resource use patterns, needs, constraints and opportunities as part of the participatory approach. Issues identified by the community were the need for fencing grazing camps, animal health improvement, subdivision of rangeland and crop fields and the development of a rotational grazing system. The main aims of this study were to develop a participatory grazing plan with the community, develop and support institutional structures governing range management, and build capacity of the community in range management. The effect of the current grazing system on species composition was determined. In addition to these, the project investigated the potential different fodder trees has on alleviating feed and nutritional deficit, particularly during the dry winter months of the Upper Thukela. Among the main achievements of this study was the development and strengthening of local institutional structures and effective liaison by all structures with the Inkosi and the tribal council. The community developed a rotational grazing plan, marked the camp boundaries, produced digital maps and successfully built fence boundaries (approximately 20 kms of fencing) to divide their land. The fence boundaries separated the crop fields and rangeland, closed ward boundaries in the upland to prevent access by cattle from neighbouring wards, and divided the land into three camps. Six crush pens were constructed in each subward of the Okhombe ward. A communal herders fund opened and fence construction improved crop yields due to a decrease in crop damage by cattle. Okhombe ward, located in the Highland Sourveld region of KwaZulu-Natal, experiences feed and nutrition deficits to ruminants during winter. The prevailing species composition in Okhombe was investigated as part of the grazing plan. The veld condition of the sites ranged from poor (40.7%) in the bottomland to an averaged of 47.0% in upland sites. The most distinctive feature of the rangeland in this area was the loss of highly palatable Decreaser grass species (P <0.05), such as Themeda triandra in the bottom slopes « 1300 m) when compared to the upland (> 1800 m). The proportional abundance of Decreaser species accounted for an averaged of 1.02% of the bottomland and an averaged of 11.5% of the upland compared to the values of 49% in the benchmark (grassland in optimal condition). The composition of the less palatable Increaser Il species was very high at all elevations (1200 m -80.7%, 1400 m - 75.8% and 1700 m - 55.7%) when compared to the low benchmark composition of 19%. The dominant grasses of the bottom slopes were Increaser Il species, such as Eragrostis curvula, Eragrostis plana and Sporobolus africanus and unpalatable Increaser III species such as Aristida junciformis. A significant difference (P < 0.05) in the composition of Decreaser, Increaser I and Increaser Il species was found between the bottom and slopes compared to the upland region. However, the grass cover formed by these tufted species was generally high, making it more resistant to physical degradation. The bottom slope ranged from reasonable to excellent cover (16.9%), the middle slope ranged from reasonable (15.9%) to a good cover of 18.1%, averaging 16.7% and a range of 16.1% to 17.9% for the upland plateau. In the agroforestry trial the potential of different fodder species for supplementing fodder was examined. Leucaena leucocephala had the potential of being a suitable fodder tree species for use in alley cropping (P < 0.05) compared to Morus alba and Acacia karroo. Results from the partially intercropped treatments showed that L. leucocephala yield (665 kg ha-I) varied significantly (P < 0.05) from the A. karroo (378 kg ha-I) and M alba yield (345 kg ha-I). Treatments that were fully intercropped varied, but no significant difference (P > 0.05) were recorded. Morus alba produced the least yield of 345 kg ha-I, A. karroo yielded 378 kg ha-1 and 1. leucocephala recorded the high of 664 kg ha-I. Results from the second season showed similar trend in that 1. leucocephala yielded a significant (P < 0.05) fodder production of 1715 kg ha-I in comparison to M. alba (1101 kg ha-I) and A karroo (1140 kg ha-I). M alba yielded the least dry matter production (P < 0.05) but had high potential (P < 0.05) for addressing lack of firewood in rural areas. Morus alba yielded high fuel wood production from both two seasons. There were no significant differences in fuel wood yield (P > 0.05) from the partially intercropped M alba (507.9 kg ha-I) and 1. leucocephala (455.0 kg ha-I) but the yield from both species varied significantly from the A. karroo yield (103.kg ha-I). With regard to fully intercropped plots, fuel wood yield from all tree species varied significantly, A karroo resulting in low yield (63 kg ha-I), 1. leucocephala recorded 243 kg ha-l and M alba the highest yield of 444 kg ha-I. In the second season, M. alba yielded an averaged fuel wood production of 728 kg ha-l and a low of 439 kg ha-I from 1. leucocephala. Acacia karroo, a slow growing indigenous tree, might be preferred by farmers due to its less branches resulting in minimal light competition with crops. Leucaena leucocephala tend to grow slowly in its initial establishment stage, but once roots become well established, it grows fast and produces high quantity of fodder. The effect all fodder trees had on crop yield was not negative during the trial period and further research on long term effects of alley cropping is recommended. The conclusions drawn here were based on tree growth and their likely impact in alley cropping. Leucaena leucocephala was also recommended as a preferred species for rural ruminants based on the forage quality study. The results showed high content of crude protein (19.27%), low NDF content (50.38%) and very low tannin content (1.19%) from 1. leucocephala compared to A. karroo with a high tannin content of 5.69%. Acacia karroo had a crude protein content of 13.60%, NDF percentages of 44.16 and 34.64% of ADF content. Morus alba also had a recommended chemical composition of 11.71% of CP, 42.86% of NDF, 36.96% of ADF and a low tannin content of 0.65%. L. leucocephala foliage proven is readily degradable under different diet ranging within 24 hrs of intake (P < 0.001) compared to other feeds. L. leucocephala had high dry matter loss degraded from the rumen under Eragrostis hay diet with poor nutrients to high protein concentrates diet. Under the Eragrostis hay diet for instance, L. leucocephala tend to degrade rapidly with values of dry matter loss ranging from 32.2% to 39% at 4 hrs to 16 hrs, when compared to low dry mater loss of 26% at 4 hrs to 31.33% at 16 hrs. Feeds such as M alba tend to degrade slowly within 24 hrs of intake and rapidly degrades after the stated period. The ep content of maize stover was very low ranging from 1.60% in maize stalks to 2.63% in maize leaves. The fibre content in maize stover was very high when compared to lower values in fodder samples. The NDF content ranged from 77.92% in maize leaves to 81.60% in maize stalks. Maize leaves when compared to a combination of maize leaves and maize stalks sole tend to degrade better within 24 hrs of intake. This was due to low (P < 0.05) degradability rate of maize stalks compared to a combination of maize stalks and leave and leaves sole and least NDF content in maize leaves might have attributed to these results. Due to poor chemical compositions of these roughage samples, the study recommended the establishment of fodder banks and agroforestry systems to curb the nutrients deficit during winter. In conclusion therefore, this study highlight that the sustainability of rural systems to manage communal grazing land should be further explored. Most of the challenging issues in communal range management are social in nature rather than technical concepts. These include ways of improving social contributions from cattle to the community while maintaining cultural values of the use of cattle. The interventions in communal range management by service providers should understand the institutional arrangements within a community and an attempt to strengthen such existing structures is recommended. Further interventions by service providers in Okhombe ward should bring in the planning discussions, experts from social sciences, to deal with understanding of community dynamics. Complexities in communal range management involve dealing with non-stock owners within project boundaries. Communities from neighbouring wards should not be ignored and ways of improving communications and updating project details to them should be formulated. Shortage of land and closing of ward boundaries to prevent access to land by neighbouring wards is among community complexities to be explored. Communities in rural lands do share land and in most cases boundaries are known but invisible by an outsider to identify. It is important to strengthen and maintain every success in communal lands as that may form core of the project. Successes on grazing management by locals is far from being the improvement in veld but there are rather various factors to the successes of grazing projects in rural areas. Examples of successes based on Okhombe project are reduction in stock theft, improved in relationship between community and locals institutions, a reduction in stock mortalities during winter and improved animal health. Veld improvement is among successes but there are accomplishments phases to fulfil before focusing on improvement of species composition. / Thesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2005.

Text in English / In recent years, there have been tremendous advances in information technology, robotics, communication technology, nanotechnology, and artificial intelligence, resulting in the merging of physical, digital, and biological worlds that have come to be known as the "fourth industrial revolution”. In this context, the present study engages such technology in the green economy and to tackle the techno-economic environmental impact assessments challenges associated with floating solar system applications in the agricultural sector of South Africa. In response, this exploratory study aimed to examine the development of a Geographical Information System (GIS)-based support platform for Environmental Impact Assessment (EIA) and due-diligence analyses for future planned agricultural floating solar systems, especially with the goal to address the vast differences between the environmental impacts for land-based and water-based photovoltaic energy systems. A research gap was identified in the planning processes for implementing floating solar systems in South Africa’s agricultural sector. This inspired the development of a novel GIS-based modelling tool to assist with floating solar system type energy infrastructure planning in the renewable energy discourse. In this context, there are significant challenges and future research avenues for technical and environmental performance modelling in the new sustainable energy transformation. The present dissertation and geographical research ventured into the conceptualisation, designing and development of a software GIS-based decision support tool to assist environmental impact practitioners, project owners and landscape architects to perform environmental scoping and environmental due-diligence analysis for planned floating solar systems in the local agricultural sector. In terms of the aims and objectives of the research, this project aims at the design and development of a dedicated GIS toolset to determine the environmental feasibility around the use of floating solar systems in agricultural applications in South Africa. In this context, the research objectives of this study included the use of computational modelling and simulation techniques to theoretically determine the energy yield predictions and computing environmental impacts/offsets for future planned agricultural floating solar systems in South Africa. The toolset succeeded in determining these aspects in applications where floating solar systems would substitute Eskom grid power. The study succeeded in developing a digital GIS-based computer simulation model for floating solar systems capable of (a) predicting the anticipated energy yield, (b) calculating the environmental offsets achieved by substituting coal-fired generation by floating solar panels, (c) determining the environmental impact and land-use preservation benefits of any floating solar system, and (d) relating these metrics to water-energy-land-food (WELF) nexus parameters suitable for user project viability analysis and decision support. The research project has demonstrated how the proposed GIS toolset supports the body of geographical knowledge in the fields of Energy and Environmental Geography. The new toolset, called EIAcloudGIS, was developed to assist in solving challenges around energy and environmental sustainability analysis when planning new floating solar installations on farms in South Africa. Experiments conducted during the research showed how the geographical study in general, and the toolset in particular, succeeded in solving a real-world problem. Through the formulation and development of GIS-based computer simulation models embedded into GIS layers, this new tool practically supports the National Environmental Management Act (NEMA Act No. 107 of 1998), and in particular, associated EIA processes. The tool also simplifies and semi-automates certain aspects of environmental impact analysis processes for newly envisioned and planned floating solar installations in South Africa. / Geography / M.Sc. (Geography)

<p>Field-edge buffers are a promising way to address nonpoint source pollution from agricultural runoff, but concentrated runoff flow often renders standard fixed-width linear buffers ineffective. AgBufferBuilder (ABB) is a tool within ESRI ArcMap Geographic Information Systems software that designs and evaluates targeted, nonlinear buffers based on hydrologic modeling and other field-specific parameters. We tested ABB on n=45 Areas of Interest (AOIs) stratified based on estimated sediment loading across three sub-watersheds within Michigan’s Saginaw Bay watershed to evaluate the effectiveness of ABB relative to existing practices across a wide range of landscape conditions. We modeled tractor movement around ABB buffer designs to assess more realistic versions of the likely final designs. ABB regularly failed to deliver the desired 75% sediment capture rate using default 9 m x 9 m output raster resolution, with Proposed buffers capturing from 0% to 68.49% of sediment within a given AOI (mean=37.56%). Differences in sediment capture between Proposed and Existing buffers (measured as Proposed – Existing) ranged from -48% to 66.81% of sediment (mean=24.70%). Proposed buffers were estimated to capture more sediment than Existing buffers in 37 of 45 AOIs, representing potential for real improvements over Existing buffers across the wider landscape. In 13 of 45 AOIs, ABB buffers modified for tractor movement captured more sediment than Existing buffers using less total buffer area. We conducted a collaborative design process with three Saginaw Bay watershed farmers to assess their willingness to implement ABB designs. Feedback indicated farmers may prefer in-field erosion control practices like cover cropping and grassed waterways over field-edge ABB designs. More farmer input is needed to better assess farmer perspectives on ABB buffers and to identify preferred data-based design alternatives. Engineered drainage systems with raised ditch berms and upslope catch basins piped underground directly into ditches were encountered several times during site visits. ABB only models surface flow and does not recognize drain output flow entering waterways. Modified ABB functionality that models buffers around drain inlets would greatly improve its functionality on drained sites. This may be accomplishable through modification of user-entered AOI margins but requires further investigation. Unfortunately, the existing tool is built for outdated software and is not widely accessible to non-expert users. We suggest that an update of this tool with additional functionality and user accessibility would be a useful addition in the toolbox of conservation professionals in agricultural landscapes.</p>

<p dir="ltr">Precision agriculture has been around for many, many years but as technology has rapidly grown with the population, farmers are looking for more ways to improve their operation with the help of these tools. These tools help farmers manage, understand, and decide when, how and what should be done regarding the tough decisions in the field based on their machinery statues. The tools that utilize GPS location and provide farm managers with useful information and feedback on large scales of value in the Harvesting and planting operation. With previous works done focusing on identify state machine activity utilizing GPS location data with the use of loggers and algorithms this study carries on from one field to the next identifying the truth data set for each and the accuracy of the algorithm. The goal is to add a more realistic view to the states identifying turning and transporting throughout the harvesting operation in truth data and from algorithm results. Also diving into truck activity with lower standard GPS tracking to see how accurately they can be predicted to complete the harvesting cycle from vehicle to vehicle. Overall, the combine and grain cart held at 88% accuracy for labeling all state activity during the harvesting operation for multiple fields, while for the model algorithm with the grain trucks having an overall accuracy of 94%.</p>

<p>Current watershed-scale, nonpoint source (NPS) pollution models do not represent the processes and impacts of agricultural best management practices (BMP) on water quality with sufficient detail. To begin addressing this gap, a novel process-based, watershed-scale, water quality model (WEPP-WQ) was developed based on the Water Erosion Prediction Project (WEPP) and the Soil and Water Assessment Tool (SWAT) models. The proposed model was validated at both hillslope and watershed scales for runoff, sediment, and both soluble and particulate forms of nitrogen and phosphorus. WEPP-WQ is now one of only two models which simulates BMP impacts on water quality in ‘high’ detail, and it is the only one not based on USLE sediment predictions. Model validations indicated that particulate nutrient predictions were better than soluble nutrient predictions for both nitrogen and phosphorus. Predictions of uniform conditions outperformed nonuniform conditions, and calibrated model simulations performed better than uncalibrated model simulations. Applications of these kinds of models in real-world, historical simulations are often limited by a lack of field-scale agricultural management inputs. Therefore, a prototype tool was developed to derive management inputs for hydrologic models from remotely sensed imagery at field-scale resolution. At present, only predictions of crop, cover crop, and tillage practice inference are supported and were validated at annual and average annual time intervals based on data availability for the various management endpoints. Extraction model training and validation were substantially limited by relatively small field areas in the observed management dataset. Both of these efforts contribute to computational modeling research and applications pertaining to agricultural systems and their impacts on the environment.</p>