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1. Precision Nitrogen Management and Global Nitrogen Use EfficiencyTraditionally, nitrogen (N) fertilizers have been applied uniformly across entire field while ignoring inherent spatial variation in crop N needs across crop fields. This results in either too little or too much application of N in various parts of the ... M. Gupta, R. Khosla |
2. Categorization of Districts Based on Nonexchangeable Potassium: Generation GIS Maps and Implications in Efficient K Fertility Management in Indian AgricultureRecommendations of K fertilizer are made based on available (exchangeable + water soluble) K status only in India and other despite of substantial contribution of nonexchangeable fraction of soil K to crop K uptake. Present paper examines the information generated in the last 30 years on the status of nonexchangeable K in Indian soils, categorization of Indian soils based on exchangeable and nonexchangeable K fractions and making K recommendations. Data for both K fractions of dif... C. Srinivasa rao, K. Rao, H. Magen, B. Venkateswarlu, A. Subba rao |
3. A Statistical and an Agronomic Approach for Definition of Management Zones in Corn and SoybeanThe use of productivity level management zones (MZ) has demonstrated good potential for the site-specific management of crop inputs in traditional row crops. The objectives of this research were to analyze the process of defining MZs and develop methods to evaluate the quality of MZ maps. Two approaches were used to select the layers to be used in the MZ definition: 1) Statistical Approach (SA_MZ) and 2) Agronomic Approach (AA_MZ). The difference is that in the AA_MZ approach all non stable v... C.L. Bazzi, E.G. Souza, R. Khosla, R.M. Reich |
4. Use of Chemical and Physical Attributes Of the Soil in Management Units DefinitionSeveral equipments and methodologies have been developed to make available precision agriculture, especially the high cost of its implantation and sampling. An interesting ... C.L. Bazzi, E.G. Souza, L.H. Nobrega, M.A. Uribe-opazo, D.M. Rocha |
5. Early Detection of Corn N-Deficiency by Active Fluorescence Sensing in MaizeGlobally, the agricultural nitrogen use efficiency (NUE) is no more than 40 %. This low efficiency comes with an agronomic, economic and environmental cost. By better management of spatial and temporal variability of crop nitrogen need, NUE can be improved. Currently available crop canopy sensors based on reflectance are cap... R. Khosla, D.G. Westfall, L. Longchamps |
6. Stable Isotope N-15 as Precision Technique to Investigate Elemental Sulfur Effects on Fertilizer Nitrogen Use Efficiency of Corn Grown in Calcareous Sandy Soils... A.A. Soaud, .M. Rahman, F.H. Al darwish |
7. The Effect of Scheduling Irrigation on Yield, Concentration and Uptake of Nutrient in Zero Tilled Wheat (Triticum Aestivum L.)Abstract: The rice–wheat rotati... D. Krishna |
8. Precision Fertigation in Wheat for Sustainable Agriculture in Saudi ArabiaWheat is an important cereal crop of Saudi Arabia grown on an area of 250,000 ha with an annual production of 1,260,000 metric tons. The crop is cultivated on sandy soils using sprinkler irrigation under center pivots. The crop is sown in Nove... V.C. Patil, K.A. Al-gaadi |
9. Soil pH maps Derived from On-the-Go pH-Measurements as Basis for Variable Lime Application under German Conditions: Concept Development and Evaluation in Field Trials... A. Borchert, D. Trautz, H. Olfs |
10. Economic Evaluation of a Variable Lime Application Strategy Based on Soil pH Maps Derived from On-The-Go pH-Measurements under German Conditions... A. Borchert, G. Recke, D. Dabbelt, D. Trautz, H. Olfs |
11. Deriving Nitrogen Indicators of Maize Using the Canopy Chlorophyll Content IndexMany spectral indices have been proposed to derive aerial nitrogen (N) status parameters of crops in recent decades. However, most of red light based spectral indices easily loss sensitivity at moderate-high aboveground biomass. The objective of present study is to assess the performance of red edge bas... Y. Miao, F. Li |
12. Precision Nutrient Management in Cotton- A Case Study from IndiaCotton is being one of the important commercial crops in India, farmers have adopted cultivating hybrid cotton to achieve higher yield. In this context, cotton is becoming input intensive crop... U. Shanwad, V. H, R. N.l., P.S. Kanannnavar, S. Swamy, M.B. Patil |
13. Site-Specific Evaluations of Nitrification Inhibitor with Fall Applications of Liquid Swine Manure... P.M. Kyveryga, T.M. Blackmer |
14. Digital Aerial Imagery Guides a Statewide Nutrient Management Benchmarking Survey... P.M. Kyveryga, T.M. Blackmer |
15. Performance Evaluation of STICS Crop Model to Simulate Corn Growth Attributes in Response to N Rate and Climate VariationsImproving nitrogen use efficiency in crop plants contributes to increase the sustainability of agriculture. Crop models could be used as a tool to test the impact of climatic conditions on crop growth under several N management practices and to refine N application recommendation and strategy. STICS, a crop growth simulator developed by INRA (France), has the capability to assimilate leaf area index (LAI) from remote sensing to re-initialize input parameters, such as seeding date and see... E. Pattey, G. Jego, N. Tremblay, C. Drury, B. Ma, J. Sansoulet, N. Beaudoin |
16. Determination of Optimal Number of Management Zones... A. Melnitchouck |
17. Effect of Urea Application through Drip Irrigation on Yield, Water and Nitrogen Use Efficiency of Summer Bitter GourdBitter gourd (Momordica charantia L.) is one of the important vegetable crops grown during summer months in high lands of Lower Gangetic Plains. Crop is very much responsive to water and nutrient but water is limiting in dry summer months. Farmers generally adopt furrow irrigation and hand watering with pitcher for growing this crop. Drip irrigation ... S. Goswami, S. Saha |
18. Field Moist Processing for Soil Analysis: Precision Measurement is Required for Precision ManagementIt has been well established over the last 50 years that many of the typical processes used by conventional soil analysis (such as drying and grinding the soil during preparation) can affect measured soil nutrient values. However, these processes have become conventional practice due to a lack of commercially viable methods of processing soil in its native field moist state. Solum, Inc (Mountain View, CA) has developed a process that allows routine, high throughput mea... M. Preiner |
19. Interest Of 3D Modeling For Lai Retrieval From Canopy Transmittance Measurements: The Cases Of Wheat And VineyardRemote sensing techniques are now widely used in agriculture, for cultivar screening as well as for decision making tools. Empirical methods relate directly the remote sensing measured values to crop characteristics. These methods are limited by the important amount of ground data necessary for their calibration. Their validity domain is generally not very well defined as well as the associated uncertainties. Conversely, radiative transfer models allow simulating a wide range of conditions, a... B. De solan, R. Lopez lozano, K. Ma, F. Baret, B. Tisseyre |
20. Comparative Performance Of Different Remote Sensing (RS) And Geographic Information System (GIS) Techniques Of Wheat Area And Production EstimatesThe major wheat producing countries in the world are India, China, USA, France, Russia, Canada and Australia. Global demand for wheat is growing @ 1% per year. Crop growth and productivity are determined by a large number of factors such as genetic potential of crop cultivar, soil, weather and management variables, which vary significantly across time and space. Early prediction of crop yield is important for planning and taking various policy decisions. Many countries use th... V.C. Patil, K.A. Al-gaadi |
21. SPOT5 Multispectral Data Potentialities To Monitor Potato Crop Nitrogen Status At Specific Field ScaleThe many challenges facing European agriculture and farm of tomorrow are such that they increasingly require the setting up of Decision Support Systems (DSS) that favour integrated crop management at farm or regional level. A valuable DSS for management of split fertilizer N applications was developed in Belgium for potato crop. It combines total N recommendation based on field predictive balance-sheet method along with Crop Nitrogen Status (CNS) monitoring through hand-held chlorophyll meter... J. Goffart, A. Leonard, D. Buffet, P. Defourny, L. Van den wyngaert |
22. A Comparison Of Spectral Reflectance And Laser-induced Cholorphyll Fluorescence Measurements To Detect Differences In Aerial Dry Weight And Nitrogen Update Of WheatChlorophyll fluorescence and spectral reflectance analysis are both powerful tools to study the spatial and temporal heterogeneity of plants` biomass and nitrogen status. Whereas reflectance techniques have intensively been tested for their use in precision fertilizer application, laser-induced chlorophyll fluorescence has been tested to a lesser degree, and there are hardly any... B. Mistele, U. Schmidhalter |
23. Chlorophyll Fluorescence Approaches To Estimate The Vitality Of PlantsChlorophyll fluorescence is a now well-established technique for the analysis of photosynthesis in plants and algae. Fluorescence transients (Kautsky curves), exhibited by photosynthetic organisms under different conditions provide detail information about the structure, conformation and function of the photosynthetic apparatus, especially of photosystem II. The analysis of the so-called OJIP-curve and of the pulsed-aplitude-modulated fluorometry in conjunction with the satur... R. Valcke, D. Bierman |
24. Evaluation Of The Multiplex® Fluorescence Sensor For The Assessment Of Corn Nitrogen StatusThe Multiplex® is a new hand-held optical fluorescence sensor for non-destructive measurement of about 20 parameters descriptive of plant physiological status. The Multiplex is of potential value for in-season assessment of crop nitrogen status, but no evaluation has been released for that matter as of yet. An experiment was therefore conducted which consisted of four nitrogen fertilization treatments with 0, 20, 5... Y. Zhang, N. Tremblay |
25. Studies on Soil Spatial Variability and Its Impact on Cane Yield Under Precision Nutrient Management SystemIn present investigation an attempt was made to quantify the soil variability of 30 grids of 10 m x 10 m dimension at research farm of Nandi Sahakari Sakkare Karkhane (NSSK), Krishna Nagar, District. Bijapur. Each grid (10 m x 10 m) showed variation with available nitrogen as low as 140 kg ha-1 to as high as 245 kg/ha with a range of 105 kg/ha, phosphorus as low as 53 kg P2O5 ha-1 and as high as 89.3 kg P2O5 ha-1 wit... M. Kumar r, M. Kumar r, D. Nadagouda |
26. Modifying the University of Missouri Corn Canopy Sensor Algorithm Using Soil and Weather InformationCorn production across the U.S. Corn belt can be often limited by the loss of nitrogen (N) due to leaching, volatilization and denitrification. The use of canopy sensors for making in-season N fertilizer applications has been proven effective in matching plant N requirements with periods of rapid N uptake (V7-V11), reducing the amount of N lost to these processes. However, N recommendation algorithms used in conjunction with canopy sensor measurements have not proven accurate in making N reco... G. Bean, N.R. Kitchen, D.W. Franzen, R.J. Miles, C. Ransom, P. Scharf, J. Camberato, P. Carter, R.B. Ferguson, F. Fernandez, C. Laboski, E. Nafziger, J. Sawyer, J. Shanahan |
27. Winter Wheat Genotype Effect on Canopy Reflectance: Implications for Using NDVI for In-season Nitrogen Topdressing RecommendationsActive optical sensors (AOSs) measure crop reflectance at specific wavelengths and calculate vegetation indices (VIs) that are used to prescribe variable N fertilization. Visual observations of winter wheat (Triticum aestivum L.) plant greenness and density suggest that VI values may be genotype specific. Some sensor systems use correction coefficients to eliminate the effect of genotype on VI values. This study was conducted to assess the effects of winter wheat cultivars and growing conditi... O.S. Walsh, S.M. Samborski, M. Stępień, D. Gozdowski, D.W. Lamb, E.S. gacek, T. Drzazga |
28. On-Farm Evaluation of an Active Optical Sensor Performance for Variable Nitrogen Application in Winter WheatWinter wheat (Triticum aestivum L.) represents almost 50% of total cereal production in the European Union, accounting for approximately 25% of total mineral nitrogen (N) fertilizer applied to all crops. Currently, several active optical sensor (AOS) based systems for optimizing variable N fertilization are commercially available for a variety of crops, including wheat. To ensure successful adoption of these systems, definitive measurable benefits must be demonstrated. Nitrogen management str... O.S. Walsh, S.M. Samborski, D. Gozdowski, M. Stępień, E. Leszczyńska |
29. UAV-based Crop Scouting for Precision Nutrient ManagementPrecision agriculture – is one of the most substantial markets for the Unmanned Aerial Vehicles (UAVs). Mounted on the UAVs, sensors and cameras enable rapid screening of large numbers of experimental plots to identify crop growth habits that contribute to final yield and quality in a variety of environments. Wheat is one of the Idaho’s most important cereal crops grown in 42 of 44 Idaho counties. We are working on establishing a UAV-based methodology for in-season prediction of w... O.S. Walsh, K. Belmont, J. Mcclintick-chess, J. Marshall, C. Jackson, C. Thompson, K. Swoboda |
30. Accuracy of Differential Rate Application Technology for Aerial Spreading of Granular Fertiliser Within New ZealandAerial topdressing of granular fertilizer is common practice on New Zealand hill country farms because of the challenging topography. Ravensdown Limited is a New Zealand fertilizer manufacturer, supplier and applicator, who are funding research and development of differential rate application from aircraft. The motivation for utilising this technology is to improve the accuracy of fertilizer application and fulfil the variable nutrient requirements of hill country farms. The capability ... I.J. Yule, S.E. Chok, M.C. Grafton, M. White |
31. Delineation of Site-specific Management Zones Using Spatial Principal Components and Cluster AnalysisThe delineation of site-specific management zones (MZs) can enable economic use of precision agriculture for more producers. In this process, many variables, including chemical and physical (besides yield data) variables, can be used. After selecting variables, a cluster algorithm like fuzzy c-means is usually applied to define the classes. Selection of variables comprise a difficult issue in cluster analysis because these will often influence cluster determination. The goal of this study was... A. Gavioli, E.G. Souza, C.L. Bazzi, N.M. Betzek, K. Schenatto, H. Beneduzzi |
32. Using the Adapt-N Model to Inform Policies Promoting the Sustainability of US Maize ProductionMaize (Zea mays L.) production accounts for the largest share of crop land area in the U.S. It is the largest consumer of nitrogen (N) fertilizers but has low N Recovery Efficiency (NRE, the proportion of applied N taken up by the crop). This has resulted in well-documented environmental problems and social costs associated with high reactive N losses associated with maize production. There is a potential to reduce these costs through precision management, i.e., better application timing, use... S. Sela, H. Van-es, E. Mclellan, J. Melkonian, R. Marjerison , K. Constas |
33. Spatial Variability of Soil Nutrients and Precision Nutrient Management for Targeted Yield Levels of Groundnut (Arachis Hypogaea L.)A field study was conducted during rabi / summer 2014-15 to know the spatial variability and precision nutrient management practices on targeted yield levels of groundnut. The experimental field has been delineated into 36 grids of 9 m x 9 m using geospatial technology. Soil samples from 0-15 cm were collected and analysed. Spatial variability exists for available nitrogen, phosphorous and potassium and they varied from 99 to 197 kg N, 12.1 to 64.0 kg P2O5 and 1... H. D.c, S. Dr., N. Dr., M. Giriyappa, S. T |
34. Precision Nutrient Management System Based on Ion and Crop Growth SensingAutomated sensing and variable-rate supply of nutrients in hydroponic solutions according to the status of crop growth would allow more efficient nutrient management for crop growth in closed systems. The Structure from Motion (SfM) method has risen as a new image sensing method to obtain 3D images of plants that can be used to estimate their growth, such as leaf cover area (LCA), plant height, and fresh weight. In this sense, sensor fusion technology combining ion-selective electrodes (ISEs)... W. Cho, D. Kim, C. Kang, H. Kim, J. Son, S. Chung, J. Jiang, H. Yun |
35. Precision Nutrient Management Through Drip Irrigation in Aerobic RiceA field experiment was conducted during kharif 2015 to asses the spatial variability and precision nutrient management through drip irrigation in aerobic rice at ZARS, GKVK, Bangalore. The experimental field has been delineated into 48 grids of 4.5 m x 4.5 m using geospatial technology. Soil samples from 0-15 cm depth were collected and analysed. There was spatial variability for available nitrogen (154 to 277 kg ha-1), phosphorous (45 to 152 kg ha-1) and potass... N. Dr., S. T, M. Giriyappa, H. D.c, B. Patil, D. Prabhudeva, G. Kombali, S. Noorasma, M. Thimmegowda |
36. Integrated Approach to Site-specific Soil Fertility ManagementIn precision agriculture the lack of affordable methods for mapping relevant soil attributes is a fundamental problem. It restricts the development and application of advanced models and algorithms for decision making. The project “I4S - Integrated System for Site-Specific Soil Fertility Management” combines new sensing technologies with dynamic soil-crop models and decision support systems. Using sensors with different measurement principles improves the estimation of soil f... R. Gebbers, V. Dworak, B. Mahns, C. Weltzien, D. Büchele, I. Gornushkin, M. Mailwald, M. Ostermann, M. Rühlmann, T. Schmid, M. Maiwald, B. Sumpf, J. Rühlmann, M. Bourouah, H. Scheithauer, K. Heil, T. Heggemann, M. Leenen, S. Pätzold, G. Welp, T. Chudy, A. Mizgirev, P. Wagner, T. Beitz, M. Kumke, D. Riebe, C. Kersebaum, E. Wallor |
37. Use of Crop Canopy Reflectance Sensor in Management of Nitrogen Fertilization in Sugarcane in BrazilGiven the difficulty to determine N status in soil testing and lack of crop parameters to recommend N for sugarcane in Brazil raise the necessity of identify new methods to find crop requirement to improve the N use efficiency. Crop canopy sensor, such as those used to measure indirectly chlorophyll content as N status indicator, can be used to monitor crop nutritional demand. The objective of this experiment was to assess the nutritional status of the sugarcane fertilized with different nitr... S.G. Castro, G.M. Sanches, G.M. Cardoso, A.E. Silva, H.C. Franco, P.S. Magalhães |
38. Adjustment of Corn Population and Nitrogen Fertilization Based on Management ZonesThe main objective of this study was to adjust the corn population and nitrogen fertilization according to management zones, based on past grain yield maps (seven of soybean and three of corn) and soil electrical conductivity. The study was carried out in Não-Me-Toque, Rio Grande do Sul, Brazil, and it was conducted in a factorial strip blocks with 3 repetitions in each management zone, being the treatments: corn populations (56000, 64000, 72000, 80000 and 88000 plants ha-1)... R. Schwalbert, T.J. Carneiro amado, T. Horbe, G.M. Corassa, F.H. Gebert |
39. Towards Precision MicrobiologyIn the recent years, the use of organic matter (OM) and microorganisms is increasing beyond organic agriculture, into conventional horticultural systems, in order to achieve high yields and quality through a more sustainable soil management. Thus, Integrated Nutrient Management (INM), that includes the use of diagnostic tools, high quality OM, microbial inoculants, highly-efficient fertilizer, and site-specific management in gaining space in intensive production systems. Precision m... V. Gutiérrez, R. Ortega |
40. Content Analysis of the Challenges of Using Drones in Paddy Fields in the Haraz Plain Watershed, IranDrone technology has gained popularity in recent years as a sustainable solution to changing agricultural conditions. Using drones in agriculture provides many advantages in farm management. However, the use of drones in paddy fields in Iran is a new phenomenon facing numerous challenges. This study aims to explore the challenges for using drones in paddy fields and provide practical guidelines to solve the challenges facing the their application. This research was conducted with a qualitativ... J. Aliloo, E. Abbasi, E. Karamidehkordi , E. Ghanbari parmehr, M. Canavari, G.-. Vitali |
41. Treetop Tech: Uplifting German Foresters' Drone Perspectives Through the Technology Acceptance ModelForests play a key role in nature as they purify water, stabilize soil, cycle nutrients, store carbon and also provide habitats for wildlife. Economically, forest product industries provide jobs and economic wealth. Sustainable forest management and planning requires foresters’ understanding of the forests dynamics for which the collection of field data is necessary, which can be time consuming and expensive. Unmanned aerial vehicles or drones can improve the efficiency of tradition acq... M. Michels, H. Wever, O. Mußhoff |
42. Farming for a Greener Future: the Behavioural Drive Behind German Farmers’ Alternative Fuel Machinery Purchase IntentionsClimate change due to greenhouse gas emissions, e.g. anthropogenic carbon dioxide (CO2), in the atmosphere will lead to damages caused by global warming, increases in heavy rainfall, flooding as well as permafrost melt. One of the main issues for reducing greenhouse gas emissions is the dependence on oil for fueling transportation and other sectors. Accordingly, policy makers aim to reduce dependency on fossil fuels with the accelerated roll-out of renewable energy. Among others, t... M. Michels, V. Bonke, H. Wever, O. Mußhoff |
43. Finnish Future Farm Speeding Up the Uptake of Precision AgricultureThe Finnish Future Farm (FFF) is an innovative concept that seamlessly integrates a physical Smart Farm with a Digital Twin, complemented by educational programs and business development opportunities. This holistic approach aims to propel the evolution of Smart Agriculture in Finland. At its core, FFF is a platform for co-creation with a strong emphasis on User-Centered Design. It employs a Multi-Actor Approach, bringing together companies, experts, researchers, and end users to co... H.E. Haapala |
44. Global Adoption of Precision Agriculture: an Update on Trends and Emerging TechnologiesThe adoption of precision agriculture (PA) has been mixed. Some technologies (e.g., Global Navigation Satellite System (GNSS) guidance) have been adopted rapidly worldwide wherever there is mechanized agriculture. Adoption of some of the original PA technologies introduced in the 1990s has been modest almost everywhere (e.g., variable rate fertilizer). New and more advanced technologies based on robotics, uncrewed aerial vehicles (UAVs), machine vision, co-robotic automation, and artificial i... J. Mcfadden, B. Erickson, J. Lowenberg-deboer, G. Milics |
45. R2B2 Project: Design and Construction of a Low-cost and Efficient Autonomous UGV For Row Crop MonitoringDriving the adoption of agricultural technological advancements like Unmanned Ground Vehicles (UGVs) by small-scale farmers (SSFs) is a major concern for researchers and agricultural organizations. They aim for the adoption of precision farming (PF) by SSFs to increase crop yield to meet the increasing demand for food due to population growth. In the United States, the cost of purchasing and maintaining rugged UGVs capable of precision agricultural operations stands as a barrier to the a... J.O. Kemeshi, S. Gummi, Y. Chang |
46. Barriers and Adoption of Precision Ag Tehcnologies for Nitrogen Management NebraskaA statewide survey of Nebraska farmers shows that they determine the N rate based on soil lab recommendations (82%), intuition, traditional rate, and own experience (67%). The adoption of dynamic site-specific models (23%), and sensor-based algorithms (11%) remains low. The survey identified the main barriers to the adoption of these N management technologies. ... G. Balboa, L. Puntel, L. Thompson, P. Paccioretti |
47. Bio-Effectors As a Promising Tool for Precision Agriculture and Integrated Plant NutritionBio-effectors, such as microorganisms and active natural compounds, are of increasing interest as promising alternatives or substitutes to precarious agrochemicals. European and global markets (valued at 14.6 billion US$ in 2023) for agricultural biologicals (bio-pesticides, bio-fertilizers, and bio-stimulants) are predicted to grow at rates of more than 13.5 % per year. Improved availability and use efficiency of mineral nutrients, tolerance to abiotic stresses, yield and quality traits, as ... M. Weinmann, M. Nkebiwe, N. Weber, K. Bradacova, N. Morad-talab, U. Ludewig, T. Müller, G. Neumann, M. Raupp, K. Bradacova |
48. Who Are the Data Stewards: Moving Data Driven Agriculture ForwardNearly a decade ago agricultural equipment manufacturers, service providers, retailers, land grant universities, and grower organizations came together to begin discussing the growing needs for producers to manage their farm data. This discussion was partly fueled by the industry shifting from moving data via physical media to cloud API connections. Several initiatives including the Agricultural Data Coalition (ADC) were subsequently launched focusing on addressing data privacy and security c... B.E. Craker, D. Bierman |
49. Comparing Global Shutter and Rolling Shutter Cameras for Image Data Collection in Motion on a UGVIn a bid to drive the adoption of precision farming (PF) technology by reducing the cost of developing an Unmanned Ground Vehicle (UGV), during the Reduction-To-Below-Two grand (R2B2) project we compared Arducam’s AR0234, a global shutter camera (GSC) to their IMX462, a rolling shutter camera (RSC). Since the cost of the AR0234 is approximately three times the price of the IMX462, the comparison was done to determine the possibility of using the latter for image data collection in place... J.O. Kemeshi, Y. Chang, P.K. Yadav, M. Alahe |
50. Data-driven Agriculture and Sustainable Farming: Friends or Foes?Sustainability in our food and fiber agriculture systems is inherently knowledge intensive. It is more likely to be achieved by using all the knowledge, technology, and resources available, including data-driven agricultural technology and precision agriculture methods, than by relying entirely on human powers of observation, analysis, and memory following practical experience. Data collected by sensors and digested by artificial intelligence (AI) can help farmers learn about syne... O. Rozenstein, Y. Cohen, V. Alchanatis , K. Behrendt, D.J. Bonfil, G. Eshel, A. Harari, W.E. Harris, I. Klapp, Y. Laor, R. Linker, T. Paz-kagan, S. Peets, M.S. Rutter, Y. Salzer, J. Lowenberg-deboer |
51. Single-strip Spatial Evaluation Approach: a Simplified Method for Enhanced Sustainable Farm ManagementOn-farm experimentation (OFE) plays a pivotal role in evaluating and validating the effectiveness of agricultural practices and products. The results of OFE enable farmers to act and make changes that can enhance the farm’s economic and environmental sustainability. Experimental designs can be a barrier to the adoption of OFE. The conventional approach often involves randomized complete block designs with 3 to 5 replications in the field, which can be space-intensive and disrupt workflo... S. Srinivasagan, Q. Ketterings, M. Marcaida, S. Shajahan, J. Ramos-tanchez, J. Cho, , L. Thompson, J. Guinness, R. Goel |
52. Decision Making Factors of Precision Agricultural Practices in South DakotaA survey among South Dakota Farmers was conducted to document current nutrient management practices. The survey included questions regarding adoption and use of precision ag technologies in addition to information considered to create prescription maps for variable fertilizer and seeding rates. The survey collected demographic information from the producers. The presentation will also highlight how farm size, farm location, farmer/decision maker’s age and/or education level in... P. Kovacs, J. Clark, J. Schad, E. Avemegah |