Proceedings
Topics
| Filter results74 paper(s) found. |
|---|
1. Statistical Variability of Crop Yield, Soil Test N and P Within and Between Producer’s FieldsSoil test N and P significantly affect crop production in the Canadian Prairies, but vary considerably within and between producer's fields. This study describes the variability of crop yield, soil test N and P within and between producer's fields in the context of variable fertilizer rates. Yield, terrain attribute, soil test N and P data were collected for 10 fields in Alberta, Saskatchewan and Manitoba Canada in 2014 and 2015. The influence of ... A. Moulin, M. Khakbazan |
2. Understanding Complex Soil Variability: the Application of Archaeological Knowledge to Precision Agriculture Systems in the UK.As higher resolution datasets have become more available and more accessible within commercial agriculture, there has been an increasing expectation that more data will bring more answers to questions surrounding soil, crop and yield variability. When this does not happen, trust and confidence in data can be lost, affecting the uptake and use of precision agriculture. This research presents a novel approach for understanding complex soil variability at a variety of different scales.... H. Webber |
3. Estimating Environmental Systems Using Iterated Sigma Point Techniques: a Biomass Substrate Hypothetical SystemThis paper addresses the problem of biomass substrate hypothetical system estimation using sigma points kalman filter (SPKF) methods. Various conventional and state-of-theart state estimation methods are compared for the estimation performance, namely the unscented Kalman filter(UKF), the central difference Kalman filter (CDKF), the square-root unscented Kalman filter (SRUKF), the square-root central difference Kalman filter (SRCDKF), the iterated unscented Kalman filter (IUKF), the iterated ... I. Baklouti, M. Mansouri, M. Destain, A. Hamida |
4. Spatial and Temporal Variation of Soil Nitrogen Within Winter Wheat Growth SeasonThis study aims to explore the spatial and temporal variation characteristics of soil ammonium nitrogen and nitrate nitrogen within winter wheat growth season. A nitrogen-rich strip fertilizer experiment with eight different treatments was conducted in 2014. Soil nitrogen samples of 20-30cm depth near wheat root were collected by in-situ Macro Rhizon soil solution collector then soil ammonium nitrogen and nitrate nitrogen content determined by SEAL AutoAnalyzer3 instrument. Classical statisti... X. Song, G. Yang, Y. Ma, R. Wang, C. Yang |
5. Rectification of Management Zones Considering Moda and Median As a Criterion for Reclassification of PixelsManagement zones (MZ) make economically viable the application of precision agriculture techniques by dividing the production areas according to the homogeneity of its productive characteristics. The divisions are conducted through empirical techniques or cluster analysis, and, in some cases, the MZ are difficult to be delimited due to isolated cells or patches within sub-regions. The objective of this study was to apply computational techniques that provide smoothing of MZ, so as to become v... N.M. Betzek, E.G. Souza, C.L. Bazzi, K. Schenatto, A. Gavioli, M.F. Maggi |
6. Positioning Strategy of Maize Hybrids Adjusting Plant Population by Management ZonesChoice of hybrid and accurate amount of plants per area determines grain yield and consequently net incomes. Local field adjustment in plant population is a strategy to manage spatial variability and optimize environmental resources that are not under farmer control (like soil type and water availability). This study aims to evaluate the response of hybrids by levels of plant population across management zones (MZ). Six different hybrids and five rates of plant populations were analyzed start... A.A. Anselmi, J.P. Molin, M.T. Eitelwein, R. Trevisan, A. Colaço |
7. Should One Phosphorus Extraction Method Be Used for VRT Phosphorus Recommendation in the Southern Great Plains?Winter Wheat has been produced throughout the southern Great Plains for over 100 years. In most cases this continuous production of mono-culture lower value wheat crop has led to the neglect of the soils, one such soil property is soil pH. In an area dominated by eroded soils and short term leases, Land-Grant University wheat breeders have created lines of winter wheat which are aluminum tolerant to increase production in low productive soils. Now the fields in this region can hav... D.B. Arnall, S. Phillips, C. Penn, P. Watkins, B. Rutter, J. Warren |
8. Consequences of Spatial Variability in the Field on the Uniformity of Seed Quality in Barley Seed CropsSpatial variation is known to affect cereal growth and yield but consequences for seed quality are less well-known. Intra-field spatial variation occurs in soil and environmental variables and these are expected to affect the crop. The objective of this paper was to identify the spatial variation in barley seed quality and to investigate its association with environmental factors and the spatial scale over which this correlation occurs. Two uniformly-managed, commercial fields of wi... S. Hama rash, A.J. Murdoch |
9. Processing Yield Data from Two or More CombinesErroneous data affect the quality of yield map. Data from combines working close to each other may differ widely if one of the monitors is not properly calibrated and this difference has to be adjusted before generating the map. The objective of this work was to develop a method to correct the yield data when running two or more combines in which at least one has the monitor not properly calibrated. The passes of each combine were initially identified and three methods to correct yield data w... L. Maldaner, J.P. Molin, T.F. Canata |
10. The New Digital Soil Map of Sweden -Derived for Free Use in Precision AgricultureThe Digital Soil Map of Sweden (DSMS) was finalized in 2015. The present paper describes the mapping strategy, the estimated uncertainty of the primary map layers and its potential use in precision agriculture. The DSMS is a geodatabase with information on the topsoil of the arable land in Sweden. The spatial resolution is 50 m × 50 m and it covers > 90% of the arable land of the country (~2.5 million ha). Non-agriculture land and areas with organic soil are excluded. Access to a num... K. Piikki, M. Söderström |
11. Shifting Fertiliser Response Zones in a Four Year, Whole-paddock Cereal Cropping Experiment.Precision agriculture in cropping areas of dryland Australia has focused on managing within production zones. These are ideally stable, possibly soil- and topography-based areas within fields. There are many different ideas on how to delimit and implement zones, and a four year whole-field experiment, with low, medium and high treatment philosophies applied per 9m seeder/harvester width across the entire field, was established to explore how zones might best be established and used. The treat... B. Jones, T. Mcbeath, N. Wilhelm |
12. Spatial Variability of Soil Nutrients and Site Specific Nutrient Management in MaizeA field study was conducted during kharif 2014 and rabi 2014-15 at Southern Transition Zone of Karnataka under the jurisdiction of University of Agricultural Sciences, GKVK, Bangalore, India to know the spatial variability for available nutrient content in cultivator’s field and effect of site specific nutrient management in maize. The farmer’s fields have been delineated with each grid size of 50 m x 50 m using geospatial technology. Soil samples from 0-15 cm we... S. T, M. Giriyappa, D. Hanumanthappa, N. Dr., S. K, S. Yogananda, A. Kiran |
13. Sources of Information to Delineate Management Zones for CottonCotton in Brazil is an input-intensive crop. Due to its cultivation in large fields, the spatial variability takes an important role in the management actions. Yield maps are a prime information to guide site-specific practices including delineation of management zones (MZ), but its adoption still faces big challenges. Other information such as historical satellite imagery or soil electrical conductivity might help delineating MZ as well as predicting crop performance. The objective of this w... R.G. Trevisan, M.T. Eitelwein, A.F. Colaço, J.P. Molin |
14. Measurement of In-field Variability for Active Seeding Depth Applications in Southeastern USProper seeding depth control is essential to optimize row-crop planter performance, and adjustment of planter settings to within field spatial variability is required to maximize crop yield potential. The objectives of this study were to characterize planting depth response to varying soil conditions within fields, and to discuss implementation of active seeding depth technologies in Southeastern US. This study was conducted in 2014 and 2015 in central Alabama for non-irrigated maize (Zea may... A.M. Poncet, J.P. Fulton, T.P. Mcdonald, T. Knappenberger, R.W. Bridges, J. Shaw, K. Balkcom |
15. Response of Soybean Cultivars According to Management Zones in Southern BrazilThe positioning of soybean cultivars on fields according your environmental response is new strategy to obtain high soybean yields. The aim of this study was to investigate the agronomic response of six soybean cultivars according management zones in Southern Brazil. The study was conducted in 2013/2014 and in two fields located in Boa Vista das Missões, Rio Grande do Sul, Brazil. The experimental design was a randomized complete block in a factorial arrangement (3x6), with three manag... T.J. Amado, A.L. Santi, G.M. Corassa, M.B. Bisognin, R. Gaviraghi, J.L. Pires |
16. High-resolution Mapping with On-the-go Soil Sensor and Its Relation with Corn Yield and Soil Acidity in a Dystrophic Red OxisolSpatial representations of soil attributes with low resolution can lead to gross errors of recommendation and compromise the efficiency of soil corrections and consequently the grain yield. However, obtaining the spatial variability of soil attributes with high resolution by soil sampling is not recommended because of its large time spent and high cost of laboratory analysis what makes difficult their large-scale application. This way, the on-the-go soil sensing has been used in precision agr... G.M. Corassa, T.J. Amado, R.A. Schwalbert, G.B. reimche, D. Dalla nora, T. . horbe, F.M. tabaldi |
17. Spatial Variability and Correlations Between Soil Attributes and Productivity of Green Corn CropIn Brazil, the progressive development in the cultivation of the corn for consumption in the green stadium stands by the relevant socio-economic role that this related to multiple applications, the attractive market price and continuous demand for the product in nature. Therefore, this study was to analyze the correlations and spatial variability of the productivity of the culture of the green corn in winter, in alluvial soil of the type Cambisols eutrophic in the amount areas and Hydromorphi... W.J. Souza, S.H. Benez, P.H. Nakazawa, A.J. Santana neto, L.C. Citon, V.S. Akune |
18. Claypan Depth Effect on Soil Phosphorus and Potassium DynamicsUnderstanding the effects of fertilizer addition and crop removal on long-term change in spatially-variable soil test P (STP) and soil test K (STK) is crucial for maximizing the use of grower inputs on claypan soils. Using apparent electrical conductivity (ECa) to estimate topsoil depth (or depth to claypan, DTC) within fields could help capture the variability and guide site-specific applications of P and K. The objective of this study was to determine if DTC derived from ECa... L. Conway, M. Yost, N. Kitchen, K. Sudduth, B. Myers |
19. In-field Variability of Terrain and Soils in Southeast Kansas: Challenges for Effective ConservationA particular challenge for crop production in southeast Kansas is the shallow topsoil, underlain with a dense, unproductive clay layer. Concerns for topsoil loss have shifted production systems to reduced tillage or conservation management practices. However, historical erosion events and continued nutrient and sediment loss still limit the productive capacity of fields. To improve crop production and further adoption of conservation practices, identification of vulnerable areas of fields was... G.F. Sassenrath, T. Mueller, V.J. Alarcon, S.E. Kulesza, D. Shoup |
20. Field Potential Soil Variability Index to Identify Precision Agriculture OpportunityPrecision agriculture (PA) technologies used for identifying and managing within-field variability are not widely used despite decades of advancement. Technological innovations in agronomic tools, such as canopy reflectance or electrical conductivity sensors, have created opportunities to achieve a greater understanding of within-field variability. However, many are hesitant to adopt PA because uncertainty exists about field-specific performance or the potential return on investment. These co... C.W. Bobryk, M. Yost, N. Kitchen |
21. Assessing the Variability of Red Stripe Disease in Louisiana Sugarcane Using Precision Agriculture MethodsSymptoms of red stripe disease caused by Acidovorax avenae subsp. avenae in Louisiana between 1985 and 2010 were limited to the leaf stripe form which caused no apparent yield loss. During 2010, the more severe top rot form was observed, and a study was initiated to investigate the distribution of red stripe in the field and determine its effects on cane and sugar yields. Two fields of cultivar HoCP 00-950, one plant-cane (PC) crop and one first-ratoon (FR) crop, affected by top rot wer... R.M. Johnson, M.P. Grisham |
22. Evaluation of the Effects of Telone Ii on Nitrogen Management and Yield in Louisiana Delta CottonResearch indicates that cotton yield on light soils within the alluvial flood plain of the Lower Mississippi delta may be increased by using chemical fumigation applications of Telone II and/or seed treatments to control infestations of plant parasitic nematodes. There is a documented interaction with fumigation and nitrogen and therefore a need to further understand the performance of site- specific treatment strategies for nitrogen (N) and fumigation treatments. In a small plot test conduct... E. Burris, D. Burns, K.S. Mccarter, C. Overstreet, M. Wolcott |
23. Terrain Modeling to Improve Soil Survey in North DakotaUsers of site-specific technologies would prefer to use digitized soil survey boundaries to help in delineating management zones for nutrient application. However, the present scale of soil type does not allow meaningful zone delineation. A project was conducted to use terrain modeling and other site- specific tools to delineate smaller-scale soil type boundaries that would be more useful for directing within-field nutrient management. Topography, soil EC, yield mapping and satellite imagery ... D.W. Franzen, J.L. Boettinger |
24. Regional Usefulness of Nitrogen Management Zone Delineation ToolsIn the Northern Plains of Montana, North Dakota and Minnesota, a number of site-specific tools have been used to delineate nitrogen management zones. A three-year study was conducted using yield mapping, elevation measurements, satellite imagery, aerial Ektochrome® photography, and soil EC to delineate nitrogen management zones and compare these zones to residual fall soil nitrate. At most of the sites, variable-rate N was applied and compared with uniform N application. The site-specific... D. Franzen, F. Casey, J. Staricka, D. Long, J. Lamb, A. Sims, M. Halvorson, V. Hofman |
25. Summary of Forty Years of Grid Sampling ResearchBetween the years of 1961 and 2001, two 12.5-ha fields in Illinois were sampled for soil pH, and available P and K in a 24.3-m grid. One field was sampled beginning in 1961 while the other field was sampled from 1982. At each sampling, the samples were obtained in the same grid. This resulted in the ability not only to compare grid sample density to delineate fertility patterns within the fields, but also to determine the rate of soil test change with P and K applications, the change in ferti... D.W. Franzen |
26. Development of Real-time Color Analysis for the On- Line Automated Weeding OperationsWeeds compete with the crop for water, light, nutrients and space, and therefore reduce crop yields and also affect the efficient use of machinery. Chemical sprayer is the most popular method to eradicate weeds but has cause hazardous to the environment, crops and workers. A smart sprayer is required to control the usage of chemical weedicides at the optimal level. Thus an on-line automated sprayer is introduced to the Malaysian farmers to locate in the real time environment the existence and... W. Wan ismail, K. Abdul rahman |
27. Precision Placement of Corn Gluten Meal for Weed Control in Organic Vegetable ProductionOrganic vegetable producers rank weeds as one of their most troublesome, time consuming, and costly production problems. As a result of the limited number of organically approved weed control herbicides, the precision placement of these materials increases their potential usefulness in organic production systems. As a non-selective preemergence or preplant-incorporated herbicide, corn gluten meal (CGM) inhibits root development; decreases shoot length, and reduces plant survival. The developm... C.L. Webber iii, M.J. Taylor, J.W. Shrefler |
28. Seasonal Patterns of Vegetative Indices Over Cropping SystemsRemote sensing of reflectance in the visible and near-infrared portions of the spectrum has been used for agronomic applications for a number of years. The combination of different wavelengths into vegetative indices have proven useful for a variety of applications that range from biomass, leaf area, leaf chlorophyll, yield, crop residue, and crop damage. To help refine our understanding of vegetative indices studies were conducted on corn (Zea mays L.), soybean (Glycine max (L.) Merr.), whea... J.L. Hatfield, J.H. Prueger |
29. Plant and N Impacts on Corn (Zea Mays) Growth: Whats Controlling Yield?Studies were conducted in South Dakota to assess mechanisms of intraspecific competition between corn (Zea mays) plants. Treatments were two plant populations (74,500 and 149,000 plants ha-1), three levels of shade (0, 40, and 60%) on the low plant population, two water treatments (natural precipitation and natural + irrigation), and two N rates (0 and 228 kg N ha-1). In-season leaf chlorophyll content was measured. At harvest, grain and stover yields were quantified with grain 13C-d... D.E. Clay, S.A. Clay, G. Reicks, D. Horvath |
30. Principal Component Analysis of Rice Production Environment in the Rice Terrace RegionEnvironmental conditions that affect rice production, such as air temper- ature, relative humidity, solar radiation, effective cation exchangeable capacity (ECEC) of the soil, and total nitrogen in irrigation water, were assessed for 4 paddy fields in Hoshino village, Fukuoka prefecture in Japan. Also, environ- mental factors that affected rice quality (physicochemical properties of rice grains and cooked rice) were identified using data during the beginning of a ripening period (20 days afte... Y. Hirai, Y. Beppu, Y. Mori, K. Tomita, K. Hamagami, K. Mori, S. Uchida, S. Inaba |
31. Mapping Surface Soil Properties Using Terrain and Remotely Sensed Data in Arsanjan Plain, Southern IranSustainable land management and land use planning require reliable information about the spatial distribution of the physical and chemical soil properties affecting both landscape processes and services. Spatial prediction with the presence of spatially dense ancillary variables has attracted research in pedometrics. The main objective of this research is to enhance prediction of soil properties such electrical conductivity (ECe), exchangeable sodium percentage (ESP), available phosphorus (P)... M. Baghernejad, M. Emadi |
32. 3d Object Recognition, Localization and Treatment of Rumex Obtusifolius in Its Natural EnvironmentRumex obtusifolius is one of the most highly competitive and persistent sorts of weed in agriculture. An automatic recognition and plant-treatment system is currently under development as an alternative treatment technique. An infrared-laser triangulation sensor and a high-resolution smart camera are used to generate 3D images of the weeds and their natural environment. In a segmentation process, contiguous surface patches are separated from one other. These 3D surface patc... M. Holpp, T. Anken, D. Seatovic, R. Grueninger, R. Hueppi |
33. Zone Mapping Application for Precision-farming: a Decision Support Tool for Variable Rate ApplicationWe have developed a web-based decision support tool, Zone Mapping Application for Precision Farming (ZoneMAP, http://zonemap.umac.org), which can automatically determine the optimal number of management zones and delineate them using satellite imagery and field survey data provided by users. Application rates, say for fertilizer, can be prescribed for each zone and downloaded in a variety of formats to ensure compatibility with GPS-enabled farming applicators. ZoneMAP is linked to Digital Nor... X. Zhang, C. Helgason, G. Seielstad, L. Shi |
34. Application of Geographic Information Systems in Socioeconomic Analysis: A Case of Integrated Soil Fertility Management in the Savannas of NigeriaPopulation pressure increases, shortened fallow cycles, cropping intensification, inaccessibility and low output prices as well as concerns about agricultural sustainability and self-sufficiency have combined to contribute to increased demand for integrated soil fertility management of the agricultural resource base. Following this situation, organic fertilizer in the form of animal manure becomes one of the principal sources of nutrients for soil fertility maintenance and crop production. He... O. Olayide, A. Alene, A. Ikpi, G. Nziguheba, T. Alabi |
35. Soil Moisture, Organic Matter and Potassium Influences on Eca MeasurementSpatial variability of soil physical and chemical properties is a fundamental element of site-specific soil and crop management. Since its early implementation in agriculture as a method of measuring soil salinity, the acceptance of Apparent Electrical Conductivity (ECa) in agriculture has been popular as a method of determining the spatial variability of soil physical and chemical properties that influence the ECa estimates. It was the objective of this study to examine the spatial-temporal ... R.R. Struthers, C.J. Johannsen, D.K. Morris |
36. Evaluation of Utilization Potential for Methods of Georeference in the Management of Weed Contamination of Potato CulturesCombating crop contamination with harmful invasive species is one of the main themes of agricultural research. For the potato cultures, the weed contamination decreases not only the quality but also the quantity of the harvest. The most invasive contamination for this culture is represented by the Agropyron repens and Sorgum halepense, two invasive and very nocive species characterized by underground stems able to penetrate the potato¢s tubercle and decrease their stora... L. Musetescu, M. Gidea |
37. A Passive-RFID Wireless Sensor Node for Precision AgricultureAccurate soil data is crucial for precision agriculture. While existing optical methods can correlate soil health to the gasses emitted from the field, in-soil electronic sensors enable real-time measurements of soil conditions at the effective root zone of a crop. Unfortunately, modern soil sensor systems are limited in what signals they can measure and are generally too expensive to reasonably distribute the sensors in the density required for spatially accurate feedback. In thi... P.J. Goodrich, C. Baumbauer, A.C. Arias |
38. Variability in Yield Response of Maize to N, P and K Fertilization Towards Site-specific Nutrient Recommendations in Two Maize Belts in TogoSavannah and central regions are the major maize production zones in Togo, but with maize grain yields at a threshold of only 1.5 Mg ha-1. We use a participatory approach to assess the importance of the major three macro elements (N, P and K) for maize cropping in the two regions in order to further allow for site-specific and scalable fertilizer recommendations. Thirty farmers’ fields served as pilot sites, allocated within the two regions to account for spatial variability ... J.M. Sogbedji, M. Lare, A.K. Lotsi, K.A. Amouzou, T. Agneroh |
39. Suitability of ML Algorithms to Predict Wild Blueberry Harvesting LossesThe production of wild blueberries (Vaccinium angustifolium.) is contributing 112.2 million dollars to the Canada’s revenue which can be further increased through controlling harvest losses. A precise prediction of blueberry harvesting losses is necessary to mitigate such losses. In this study, the performance of three machine learning (ML) models was evaluated to predict the wild blueberry harvest losses on the ground. The data from four commercial fields in Atlantic Canada we... H. Khan, T. Esau, A. Farooque, F. Abbas |
40. Comparative Analysis of Light-weight Deep Learning Architectures for Soybean Yield Estimation Based on Pod Count from Proximal Sensing Data for Mobile and Embedded Vision ApplicationsCrop yield prediction is an important aspect of farming and food-production. Therefore, estimating yield is important for crop breeders, seed-companies, and farmers to make informed real-time financial decisions. In-field soybean (Glycine max L.(Merr.)) yield estimation can be of great value to plant breeders as they screen thousands of plots to identify better yielding genotypes that ultimately will strengthen national food security. Existing soybean yield estimation too... J.J. Mathew, P.J. Flores, J. Stenger, C. Miranda, Z. Zhang, A.K. Das |
41. Agriculture Machine Guidance Systems: Performance Analysis of Professional GNSS ReceiversGNSS (Global Navigation Satellite Systems) plays nowadays a major role in different civilian activities and is a key technology enabling innovation in different market sectors. For instance, GNSS-enabled solutions are widespread within the Precision Agriculture and, among them, applications in the field of machinery guidance are commonly employed to optimize typical agriculture practices. The scope of this paper is to present the outcomes of the agriculture testing campaign performe... J. Capolicchio, D. Mennuti, I. Milani, M. Fortunato, R. Petix, J. Reyes gonzalez, M. Sunkevic |
42. Enhancing PA Adoption Through Value ConnectionsDespite an increase in breadth of precision agriculture over time, and the attendant elements of digital agriculture that either support PA or integrates the outputs of PA, the pace of adoption of digital agriculture in our farming systems remains slow. In assessing impediments to adoption of digital agriculture, much work to date has focused on the value proposition as considered by individual producers or value chain actors. At this level, adoption remains constrained by perceptions o... D.W. Lamb, M.T. Schaefer |
43. Farmer Charlie - Low Cost Smart Local Data Available to Remote FarmersFarmer Charlie brings connectivity and information to farmers, who receive tailored agronomic data to improve their agricultural practice. Farmer Charlie is based on on-site sensors through which soil data can be detected, gathered, and processed by a dedicated server. Broadband communication allows farmers to receive real-time, localised information on tablet or mobile phone. Farmer Charlie is a low-cost solution, it can be adapted to various crops and to detect soil humidity, pH, temperatur... B. Bonnardel |
44. Smart Food Oases: Development of a Distributed Point-to-point Urban Food Ecosystem in Food Desert AreasUrban agriculture has been getting much attention in the past decade as a solution to overcome food insecurity and accessibility of food for urban residents and to have better green environments in cities. Urban agriculture is expected to provide better nutrients to residents, reduce transportation and environmental costs, and help urban dwellers access food efficiently. The present study is to build a collaborative ecosystem among urban growers/producers and create bridges from these farmers... J. Lee, S. Song, S. Oh, K. Krishnaswamy, C. Sun, Y. Adu-gyamfi |
45. The ISO Strategic Advisory Group for Smart Farming: a Multi-pronged Opportunity for Greater Global InteroperabilityAgriculture is becoming increasingly complex and producers must secure their profitability, sustainability, and freedom to operate under a progressively more challenging set of constraints such as climate change, regulatory pressure, changes in consumer preferences, increasing cost of inputs, and commodity price volatility. We have not, however, yet reached the level of data interoperability required for a truly "smart" farming that can tackle the aforementioned probl... R. Ferreyra, J. Lehmann |
46. Realising the Potential of Agricultural Robotics and AI: The Ethical ChallengesRecent advances in AI and robotics may dramatically transform agriculture by greatly expanding the number of contexts in which the techniques of precision agriculture may be applied. Inevitably, this next agricultural revolution will generate profound ethical issues: opportunities as well as risks. Clever applications of AI and robotics may allow agriculture to be more sustainable by facilitating more precise applications of water, fertilisers, and herbicides. Robots may take some of the drud... R. Sparrow |
47. Evaluation of a Single Transect Method for Collecting Grape Samples Based on Sentinel-2 Imagery for the Characterization of Overall Vineyard PerformanceCommercial vineyards are streamed into different wine programs based on analysis of grape or juice samples collected from the field, but spatial and temporal variability can lead to sub-optimal tiering of grapes. This is a particularly difficult problem to overcome in the typically large vineyards of California’s Central Valley. Due to economic and laboratory constraints on sample collection, processing, and analysis, a single sample is often expected to represent the overall fruit qual... B. Sams, M. Aboutalebi, L. Sanchez, N. Dokoozlian, R. Bramley |
48. Using Informative Bayesian Priors and On-farm Experimentation to Predict Optimal Site-specific Nitrogen RatesMost U.S. Corn Belt states now recommend the Maximum Return to Nitrogen (MRTN) method for determining optimal nitrogen rates, which is based on 15 years of on-farm yield response to nitrogen trials. The MRTN method recommends a uniform rate for a region of a state. This study combines Illinois MRTN data, Bayesian methods, and on-farm experimentation from the Data Intensive Farm Management (DIFM) project to provide site-specific nitrogen recommendations. On-farm trials are now being used to pr... W. Brorsen, D. Poursina, C. Patterson, T. Mieno, B. Edge, E.D. Nafziger |
49. Site-specific Evaluation of Sensor-based Winter Wheat Nitrogen Tools Via On-farm ResearchCrop producers face the challenge of optimizing high yields and nitrogen use efficiency (NUE) in their agricultural practices. Enhancing NUE has been demonstrated by adopting digital agricultural technologies for site-specific nitrogen (N) management, such as remote-sensing based N recommendations for winter wheat. However, winter wheat fields are often uniformly fertilized, disregarding the inherent variability within the fields. Thus, an on-farm evaluation of sensor-based N tools is needed ... J. Cesario pinto, L. Thompson, N. Mueller, T. Mieno, L. Puntel, P. Paccioretti, G. Balboa |
50. The Impact of Row Unit Position on Planter Toolbar on Corn Crop Development: an Experimental StudyPrecision planting techniques are essential to grow corn successfully. Monitoring planter speed, row-unit bounce, and gauge-wheel load ensures high-quality seeding. Vertical vibration during planting can impede seed metering and delivery, causing planting variability. Row unit vibration increases with planting speed and can lead to spatial variability in planting. Therefore, the goals of this study were to 1) understand the influence of row unit location on its vertical vibration; and 2) comp... J. Peiretti, A. Sharda, S. Badua |
51. Precision Tools for Monitoring Experimental Irrigation Treatments in California VineyardsPrecision farming techniques, such as zonal management and variable rate nutrient delivery, have been used to manage spatial variability in many crops. Wine grapes, and most permanent crops, have been slower than row crops or agronomic crops to take advantage of these techniques, though there are barriers to implementing these methods when compared to agronomic crops. The objective of this project is to show how a suite of monitoring and management tools can be used to evaluate the performanc... B. Sams, P. Previtali, J. Mezger, M. Aboutalebi, L. Sanchez, N. Dokoozlian |
52. Enhancing On-farm Rice Yields, Water Productivity, and Profitability Through Alternate Wetting and Drying Technology in Dry Zones of West AfricaIrrigated rice farming is crucial for meeting the growing rice demand and ensuring global food security. Yet, its substantial water demand poses a significant challenge in light of increasing water scarcity. Alternate wetting and drying irrigation (AWD), one of the most widely advocated water-saving technologies, was recently introduced as a prospective solution in the semi-arid zones of West Africa. However, it remains debatable whether AWD can achieve the multiple goals of saving water whil... Y.J. Johnson, M. Becker, E.R. Dossou-yovo, K. Saito |
53. UAV Multispectral Data As a Suitable Tool for Predicting Sweetness, Size, and Yield of Vidalia OnionsVidalia onions is a specialty crop cultivated solely within the southeastern region of Georgia. The key distinguishing characteristic of Vidalia onions is its high sugar content, making them highly prized and widely consumed. Ten thousand acres are grown with Vidalia Onions each year approximately, and the market value (~$150Mi/year) makes the crop very important for the State of Georgia. Traditionally, the planting, weeding, spraying, harvesting, and post-harvesting operations are usually do... M. Barbosa, L. Oliveira, C. Tyson, A. Shirley, R. Santos, L. Sales, R. Vargas |
54. Citizens Perspectives on Robot-based Crop Farming – a Cluster Analysis Using Unsupervised Machine LearningArtificial intelligence (AI) and its possibilities and threats are prominently discussed by the broader public. Robotic solutions are based on AI and offer the potential to change agricultural production drastically. However, new food technologies have not been perceived solely positively by society in the past. Genetic engineering, for example, has been the subject of repeated controversy. Science communication theory suggests that individual opinion leaders highly influence steering a socia... H. Zeddies, G. Busch |
55. Analysis of Yield Gaps in Sub-Saharan African Cereal Production SystemsFood production in sub-Saharan Africa (SSA) is one of the lowest and keeps declining across farmers’ fields season after season (Assefa et al., 2020; F Affholder, 2013). Yield gaps in cereal cropping systems have been reported by many researchers, attesting to the existence of huge variability in production levels of cereals such as corn, wheat, sorghum, rice and millet. across SSA. It is still unclear whether the yield gaps are similar in size or driven by similar factors across differ... E. Odoom, K.A. Frimpong, S. Phillips |
56. Optimizing Experimental Design for Determining Economic Nitrogen Levels: Insights on the Use of Monte Carlo SimulationsThe determination of economic nitrogen levels is a pivotal element in the quest for sustainable agricultural practices. Designing experiments to accurately identify these levels, especially in contexts constrained by limited plot availability, poses a significant challenge. In response to these challenges, this study endeavors to demonstrate an approach to optimize the experimental design for identifying economic nitrogen levels, even under such constraints. We employed statistical... C. Matavel, A. Meyer-aurich, H. Piepho |
57. Automated Sow Estrus Detection Using Machine Vision TechnologySuccessful artificial insemination for gilts and sows relies on accurate timing that is determined by estrus check. Estrus checks in current farms are manually conducted by skilled breeding technicians using the back pressure test (BPT) method that is labor-intensive and inefficient due to the large animal-to-staff ratio. This study aimed to develop a robotic imaging system powered by artificial intelligence technology to automatically detect estrus status for gilts and sows in a stall-housin... J. Zhou, Z. Xu, T.J. Safranski, C. Bromfield |
58. Relationship of Activity and Temperature of Dairy Calves As Measured by Indwelling Rumen BolusesCircadian rhythm of body temperature is naturally occurring in animals with a lower temperature at dawn and higher at dusk. In the past, this work was manually completed by a person using rectal temperature with temperature recorded every 2 or 3 hours. Rumen indwelling boluses allow for continuous temperature monitoring without human intervention. Human intervention can increase animal stress which can elevate temperature. Current literature indicates that the animal’s body temperature ... J.M. Hartschuh, J.P. Fulton, S.A. Shearer, B.D. Enger, G.M. Schuenemann |
59. Effective Furrow Closing Systems for Consistent Corn Seed PlacementFarmers face a constant challenge when choosing the appropriate planter setup due to the variability of cropping systems under no-till. Effective performance of the planter's closing wheels can reduce errors from previous components that affect seedbed formation in the furrow. Effective seed-to-soil contact during planting is essential for optimal seed emergence and overall crop stand, with the closing wheels playing a pivotal role in this process. Producers have a range of closing wheels... J. Peiretti, B. Gigena, S. Badua, A. Sharda |
60. Assessment of Soil Spatial Properties and Variability Using a Portable VIS-NIRS Soil Probe for On-farm Precision ExperimentationAssessing the spatial variability of soil properties represents an important issue for on-farm sustainable management owing to high cost of sampling densities. Actual methods of soil properties measurement are based on conventional soil sampling of one sample per ha, followed by laboratory analysis, requiring many soil extraction processes and harmful chemicals. This conventional laboratory analysis does not allow exploring spatial variation of soil properties at desired fine spatial scale. T... A. Cambouris, M. Duchemin, E. Lord, N. Ziadi, B. Javed, J.D. Nze memiaghe, D.A. Ramirez-gonzalez |
61. Operationalization of On-farm Experimentation in African Cereal Smallholder Farming SystemsPast efforts have concentrated on linear or top-down approaches in delivering precision nutrient management (PNM) practices to smallholder farmers. These deliberate attempts at increasing adoption of PNM practices have not yielded the expected outcomes, that is, increased productivity and nutrient use efficiency, at scale. This is because technologies generated by scientists with minimal farmer involvement often are not well tailored to the attendant agro-ecological, socio-economic, and cultu... I. Adolwa, S. Phillips, B.A. Akorede, A.A. Suleiman, T. Murrell, S. Zingore |
62. Cherry Yield Forecast: Harvest Prediction for Individual Sweet Cherry TreesDigitalization continues to transform the agricultural sector as a whole and also affects specific niches like horticulture. Particularly in fruit and wine production, the focus is on the application of sensor systems and data analysis aiming at automated detection of drought stress or pests in vineyards or orchards. As part of the “For5G” project, we are developing an end-to-end methodology for the creation of digital twins of fruit trees, with a strong focu... A. Gilson, L. Meyer, A. Killer, F. Keil, O. Scholz, D. Kittemann, P. Noack, P. Pietrzyk, C. Paglia |
63. Harnessing Farmers’, Researchers’ and Other Stakeholders’ Knowledge and Experiences to Create Shared Value from On-farm Experimentation: Lessons from KenyaAchieving greater sustainability in farm productivity is a major challenge facing smallholder farmers in Kenya. Existing technologies have not solved the challenges around declining productivity because they are one-size-fits-all that doesn’t account for the diverse smallholder contexts. A study was carried out in Kenya by a multi-disciplinary team to assess the value of On-Farm Experimentation (OFE) to tailor technologies to local conditions. The OFE process begun with identification o... J. Muthamia, I. Adolwa, J. Mutegi, S. Zingore, S. Phillips |
64. Spatial Distribution of Dry Matter in Avocado Fruits and Its Relationship with Fruit LoadThe quality and post-harvest life of avocado fruits is strongly conditioned by their oil content, accumulated before harvest. Oil content can be estimated through the dry matter content of the fruit. Thus, to start the harvest, a minimum of 22% dry matter (DM) must be reached, with an optimum between 22 and 28%, while with a DM above 28% the fruit loses its storage condition. The spatial variability of the dry matter of avocado fruits was studied in an 8-hectare field. A 20-poi... H.P. Poblete, R.A. Ortega |
65. Determining Site-Specific Soybean Optimal Seeding Rate Using On-Farm Precision ExperimentationTen on-farm precision experiments were conducted in Nebraska during 2018 – 2022 to address the following: i) determine the Economic Optimal Seeding Rates (EOSR), ii) identify the most important site-specific variables influencing the optimal seeding rates for soybeans. Seeding rates ranged from 200,000 to 440,000 seeds ha-1, and treatments were randomized and replicated in blocks across the entire field. The study was implemented using a variable rate prescription. ... M.M. Dalla betta, L. Puntel, L. Thompson, T. Mieno, J.D. Luck, N. Cafaro la menza, P. Paccioretti |
66. Creating Value from On-farm Research: Efields Data Workflow and Management Successes and ChallengesFarm operations today generate a large amount of data that can be difficult to properly manage. This challenge is further compounded when conducting on-farm research. The Ohio State University eFields program partners with farmers to conduct on-farm research and share results in a timely manner. Since 2017, the team has conducted and shared 987 trials across Ohio with the annual number of trials increasing from 45 to 292. This rapid increase has required development of a data workflow that st... J.P. Fulton, D. Wilson, R. Tietje, E. Hawkins |
67. Evaluating Different Strategies to Analyze On-farm Precision Nitrogen Trial DataOn-farm trials are being conducted by more and more researchers and farmers. On-farm trials are very different to traditional small plot experiments due to the existence of significant within-field variability in soil-landscape conditions. Traditional statistical techniques like analysis of variance (ANOVA) are commonly adopted for on-farm trial analysis to evaluate overall performance of different treatments, assuming uniform environmental and management factors within a field. As a result, ... K. Mizuta, Y. Miao, J. Lu, R.P. Negrini |
68. Have Your Steak and Eat It Too: Precision Beef Management to Simultaneously Reduce Ech4 and Increase ProfitAchieving carbon net zero is a clear priority, with beef farmers under significant scrutiny from food system stakeholders. Tools are available to assess greenhouse gas emissions (GHGe), yet adoption is low, and producers are not currently financially incentivised to change management practices. This study used cattle performance data from a commercial beef operation to model the optimal age and weight at slaughter to maximise profit and reduce enteric methane (eCH4) emissions at th... K. Behrendt, J. Capper, L. Ford, E.W. Harris |
69. Influence of Potassium Variability on Soybean YieldDue to its role as a plant essential nutrient, Potassium (K) serves as a fundamental component for plant growth. Soybeans are heavily reliant upon this nutrient for root growth and the production of pods, so much so that after nitrogen, potassium is the second most in-demand nutrient. Much of the overall soybean crop grown in Oklahoma is not managed with the fertility of K directly in mind. However, as the potential and expectation for greater yield increases, so does interest from produ... J. Derrick, S. Akin, R. Sharry, B. Arnall |
70. All for One and One for All: a Simulation Assessment of the Economic Value of Large-scale On-farm Experiment NetworkWhile on-farm experiments offer invaluable insights for precision management decisions, their scope is usually confined to the specific conditions of individual farms and years, which limits the derivation of more broad and reliable decisions. To address this limitation, aggregating data from numerous farms of various crop growth conditions into a comprehensive dataset appears promising. However, the quantifiable value of this experiment network remains elusive, despite the common agreement o... X. Li |
71. Utilizing Image-based Artificial Intelligence for Grading Bovine OocytesFor years, proper oocyte selection has been carried out with the precision of a lab technician’s eyes. The classification of oocytes using image-based artificial intelligence is a new technology that IVF lab technicians, cattle genetics companies, and veterinarians can utilize. Via the aspiration of the follicles on a cow’s ovaries, oocytes are able to be collected. Once oocytes are obtained from the ovaries of a cow, they are sent to an IVF lab to be cleaned and evaluated by a la... G. Koppelman, J.P. Fulton, S. Khanal, T. Berger-wolf |
72. Optimizing Chloride (Cl) Application for Enhanced Agricultural YieldThe optimization of chloride (Cl-) application rates is crucial for enhancing crop yields and reducing environmental impact in agricultural systems. This study investigates the relationship between chloride application rates and wheat yields, focusing on Club wheat cultivation in a 19.76-hectare field in Washington State. The target yield was set at 3765 kilograms per hectare, with seeding conducted at 67.24 kilograms per hectare using conservation tillage practices. Potassium chlo... F. Pereira de souza, R.P. Negrini, H. Tao |
73. On-farm Experimentation Case Study in Brazil: Evaluation of Soybean Seeding Rate Using Resources Available at the FarmIn order to maximize grain yield in soybean (Glycine max [L.] Merr.) it is necessary that the plant population is correctly defined. Production environments differ spatially, and cultivar holders suggest plant populations across macroregions and in broad ranges. Refinements of planting seasons and populations are carried out through tests on many properties, often costly and sometimes unrepresentative of most fields. Tools for managing spatial variability are ways to conduct mor... M. Rodrigues alves franchi, I. Molina cyrineu, F. Kagami taira, L. Hunhoff, L.M. Gimenez |
74. Driving Growth Through Precision Agriculture: the Evolution of the Nebraska On-farm Research NetworkThe Nebraska On-Farm Research Network (NOFRN), allows farmers to answer production, profitability and sustainability questions in their own field. The University of Nebraska (USA) sponsors the NOFRN and provides technical support in the experimental design, execution, data analysis and results dissemination. In recent years, precision agriculture technologies have expanded network capabilities through an increasing number of experiments and provided new avenues for data analyses. The goal ... G. Balboa, B. Tobaldo, T. Lexow, J.D. Luck |