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1. Precision Sensors For Improved Nitrogen Recommendations In WheatCrop sensor-based systems with developed algorithms for making mid-season fertilizer nitrogen (N) recommendations are commercially available to producers in some parts of the world. Although there is growing interest in these technologies by grain producers in Montana, use is limited by the lack of local research under Montana’s semiarid conditions. A field study was carried out at two locations in 2011, three locations in 2012, and two locations in 2013 in North West Mont... O.S. Walsh, A. Pandey, R. Christiaens |
2. Evaluating Different Nitrogen Management Strategies For The Intensive Wheat-Maize System In North China PlainThe sustainable agricultural development involves both environmental challenges and production goals to meet growing food demand. However, excessive nitrogen (N) applications are threatening the sustainability of intensive agriculture in the North China Plain (NCP). Improved N management should result in greater N use efficiency (NUE) and producer profit while reducing the risk of environmental contamination. Therefore, developing and disseminating feasible N management strategi... Q. Cao, Y. Miao, G. Feng, F. Li, B. Liu, X. Gao, Y. Liu |
3. Nitrogen Fertilisation Recommendations : Could They Be Improved Using Stochastically Generated Climates In Conjunction With Crop Models ?In the context of precision nitrogen (N) management, to ensure that the yield potential could be reached each year, farmers have too often applied quantities of fertilizers much larger than what was strictly required. However, since 2002, the Belgian Government transposed the European Nitrate Directive 91/676/EEC in the Belgian law, with the aim to maintain the productivity and the revenue of Belgian's farmers while reducing the environmental impact of excessive N management... B. Basso, J. Destain, B. Bodson, M. Destain, B. Dumont |
4. Precision Nutrient Management In Cotton At Different Yield Targets In Northern Transitional Zone Of KarnatakaNutrient management in cotton is complex due to the simultaneous production of vegetative and reproductive structures during the active growth phase. Lot of spatial variation in soil available nutrients is observed under similar management situation. In view of this an experiment ... C.C. Pgowda |
5. Variable-Rate Application Of Nitrogen And Potassium Fertilizers In Louisiana Sugarcane Production Systems.If sugar and cane yields are to be optimized and profitability improved, it is critical that a sugarcane crop receive the proper levels of plant nutrients. Under-fertilization can result in reduced cane yields, while over-fertilization can reduce sugar recovery. In addition, improper fertilization may increase crop susceptibility to environmental stresses and disease and insect pests. Nitrogen (N) continues to be one of the most important and co... B.J. Viator, R.M. Johnson |
6. Estimation Of Nitrogen And Chlorophyll Content In Wheat Crop Using Hand Held SensorsA Field experiment was conducted to estimate crop nitrogen (N) status and chlorophyll content in wheat crop by using chlorophyll content meter(Apogee’s CCM-200) and N-Tester® (Make YARA International). The experiment was conducted by sowing university recommended wheat variety viz. PBW 550 with 5 nitrogen levels i.e. 0, 30, 60, 90, 120 & 150 kg N/ha. It was found that at tillering stage when nitrogen rates were increased from 0 to 150 kg ha-1 , the... M.S. Makkar, A. Kaul, R. Kumar, A. Sharma, B.S. Sekhon, C.S. Pannu |
7. Multilayer And Multiyear Data Analysis In Precision Yield PlanningThis work covers two separate field experiments. In the first one, the results of 1-ha grid soil analysis for soil organic matter (OM), pH, cation exchange capacity (CEC), nitrate N, P, K, S, Ca, Mg and soluble salts were compared with the results of yield mapping, biomass index from optical on-the-go sensors, as well as multispectral imagery analysis for the last 30 years. As a result, it was found that none of the analyzed soil characteristics was predominant for determining yiel... A. Melnitchouck |
8. Response Of Rhodes Grass (Chloris Gayana Kunth) To Variable Rate Application Of Irrigation Water And Fertilizer NitrogenRhodes grass is cultivated extensively in Saudi Arabia under center pivot sprinkler irrigation system. The research work was carried out to optimize irrigation water and fertilizer nitrogen levels for the crop. The objectives of the study were: 1. To delineate the field in to management zones, 2. To study the effects of variable rate application (VRA) of irrigation water and fertilizer nitrogen on the yield of Rhodes grass. A field experiment was carried out fro... V. Patil, R. Madugundu, E. Tola, S. Marey, D.J. Mulla, S.K. Upadhyaya, K.A. Al-gaadi |
9. Optical Sensors To Predict Nitrogen Demand By SugarcaneThe low effectiveness of nitrogen (N) from fertilizer is a substantial concern in worldwide which has been threatening the sustainability of sugarcane production. The increment of nitrogen use efficiency (NUE) by sugarcane genotypes associated to the best practices of fertilizer management and nutritional diagnosis methods have higher potential to reduce environment impacts of nitrogen fertilization. Due to the difficult to determine N status in soil test as well as there is not... O.T. Kolln, G.M. Sanches, J. Rossi neto, S.G. Castro, E. Mariano, R. Otto, R. Inamasu, P.S. Magalhães, O.A. Braunbeck, H.C. Franco |
10. Effect Of Land Use Over Spatial Variability Of Nitrogen Mineralization And Some Of Chemical Soil Properties In Mirabad Area Of IranAbstract Any changes in ecosystem conditions and land management impact on ecology of soil inorganic nitrogen. Understanding of the biology soil is increasingly important for sustainable ecosystem. The aim of this study was to investigate the spatial variability and zoning of nitrogen mineralization, organic carbon and calcium carbonate influenced by the user of apple orchards, crop production and pasture, and compare the two interpola... E. Nabizadeh, S. Kaboodi |
11. Research On Measurement Device For NO3- Ion Concentration Of Nutrient SolutionThe management of water and ion concentration in nutrient solution is crucial in precision agriculture. Poor management may leads to the increasing of energy consumption and cost as well as low efficiency. The measurement of ion concentration in nutrient solution is prerequisite for optimal control and management of nutrient solution. Real-time detection of NO3-, as an important component of nitrogenous fertilizer, is always a big problem over the world. Th... X. Zhang, Y. Li, K. Xu, X. Sun |
12. Site Specific Drip FertigationTwo test plots, one from high fertility zone and one from low fertility zone were identified and delineated with the help of GPS for raising the test crop. Soil samples were collected from the experimental sites one month before planting. The samples were analyzed for available N, P and K. Site specific nutrient recommendations were made using the Decision Support System for Integrated Fertilizer Recommendation (DSSIFER) software (Murugappan et al. 2004) for optimum yie... A.H. V.m. |
13. Precision Nutrient Management For Enhancing The Yield Of Groundnut In Peninsular IndiaGroundnut is an important oil seed crop grown in an area of around 8 lakh hectares in Karnataka state of India under rainfed conditions. In these situations farmers applied inadequate fertilizer without knowing the initial nutrient status of the soil which resulted in low nutrient use efficiency that intern lead to low productivity of groundnut in these areas. Soil fertility deterioration due to... M. Giriyappa, T. Sheshadri, D. Hanumanthappa, M. Shankar, S.B. Salimath, T. Rudramuni, N. Raju, N. Devakumar, G. Mallikaarjuna, M.T. Malagi, S. Jangandi |
14. The Most Sensitive Growth Stage To Quantify Nitrogen Stress In Sugarcane Using Active Crop Canopy SensorThe use of sensors that allow the application of nitrogen fertilizer at variable rate has been widely used by researchers in many agricultural crops, but without success in sugarcane, probably due to the difficulty of diagnosing the nutritional status of the crop for nitrogen (N). Active crop canopy sensors are based on the principle that the spectral reflectance curve of the leaves are modified by N level. Researchers in USA indicated that in-season N stress in corn can be dete... S.G. Castro, O.T. Kolln, H.S. Nakao, H.C. Franco, O. Braunbeck, P.S. Graziano magalhães, G.M. Sanches |
15. Nutrient Expert Software For Nutrient Management In Cereal CropsMany countries in Asia have started replacing blanket fertilizer recommendations for vast areas of rice, maize, or wheat with more site-specific guidelines adapted to local needs. This process has been accompanied with a shift from traditional on-station research to on-farm development and evaluation of novel practices. A key challenge faced by the local extension agencies remains the complex nature of factors influencing nutrient requirements. To aid in this process, the ... M. Pampolino, K. Majumdar, S. Phillips |
16. Precision Nutrient Management Through Use Of LCC And Nutrient Expert In Hybrid Maize Under Laterite Soil Of IndiaNutrient management has played a crucial role in achieving self sufficiency in food grain production. Energy crisis resulted in high price index of chemical fertilizers. Coupled with their limited production, fertilizer cost, soil health, sustainability and pollution have gave rise to interest in precision nutrient management tools. Field experiment was conducted to study the effect of variety and nutrient management on the growth and productivity of maize under lateritic belt of West Be... M. Banerjee, S. Dutta, G. Bhuiya, G. Malik, D. Maiti |
17. Comparison Of The Variable Potassium Fertilization On The Light And Heavy SoilsIntroduction. Determination of the spatial variability of the nutrient levels in soil facilitated adaptation of the fertilizer doses to the soluble forms availability. Nowadays, an increasing use of this method of the fertilizer application is observed, with this being associated with both economical and environmental advantages, as well as, with growing assortment of the purpose-built agricultural instrumentation. An accurate determination of the spatial distri... P. Grocholski, P. Stepien, G. Kulczycki, A. Michalski |
18. Beyond The 4-Rs Of Nutrient Management In Conjunction With A Major Reduction In TillageAgribusiness and government agencies have embraced the 4-R concept (right form, rate, time, and place) to improve nutrient management and environmental quality. No-ti... J.S. Schepers, B. Mclure, G. Swanson |
19. Automated In-field Ornamental Nursery Plant Counting and Quality Assessment with End-to-end Deep Learning for Inventory ManagementEfficient inventory management and rigorous quality evaluation play crucial roles for monitoring sales, yield, space utilization, production schedules, and quality enhancements in the ornamental nursery sector. The current method for conducting inventory and quality assessments is through manual plant counting, even when dealing with thousands of plants. The prevailing approach is inefficient, time consuming, labor intensive, potential inaccuracies, and high expenses. Given the continuous dec... H.H. Syed, T. Rehman |
20. AI-based Pollinator Using CoreXY RobotThe declining populations of natural pollinators pose a significant ecological challenge, often attributed to the adverse effects of pesticides and intensive farming practices. To address the critical issue of pollination in the face of diminishing natural pollinators, we are pioneering an AI-based pollinator that utilizes a CoreXY pollination system. This solution aims to augment pollination efforts in agriculture, increasing yields and crop quality while mitigating the adverse impacts of pe... H. Kulhandjian, M. Kulhandjian, D. Rocha, B. Bennett |
21. AI-based Fruit Harvesting Using a Robotic ArmFruit harvesting stands as a pivotal and delicate process within the agricultural industry, demanding precision and efficiency to ensure both crop quality and overall productivity. Historically reliant on manual labor, this labor-intensive endeavor has taken a significant leap forward with the advent of autonomous jointed robots and Artificial Intelligence (AI). Our project aims to usher in a new era in fruit harvesting, leveraging advanced technology to perform this essential task autonomous... H. Kulhandjian, N. Amely, M. Kulhandjian |
22. Creating a Comprehensive Software Framework for Sensor-driven Precision AgricultureRobots and GPS-guided tractors are the backbone of smart farming and precision agriculture. Many companies and vendors contribute to the market, each offering their own customized solutions for common tasks. These developments are often based on vendor-specific, proprietary components, protocols and software. Many small companies that produce sensors, actuators or software for niche applications could contribute their expertise to the global efforts of creating smart farming solutions, if the... O. Scholz, F. Uhrmann, M. Weule, T. Meyer, A. Gilson, J. Makarov, J. Hansen, T. Henties |
23. Enhancing Precision Agriculture Through Dual Weed Mapping: Delineating Inter and Intra-row Weed Populations for Optimized Crop ProtectionIn the field of precision agriculture, effective management of weed populations is essential for optimizing crop yield and health. This paper presents an innovative approach to weed management by employing dual weed mapping techniques that differentiate between inter-row and intra-row weed populations. Utilizing advanced imaging and data analysis of CropEye images collected by the Robotti robot from AgroIntelli (AgroIntelli A/S, Aarhus, Denmark), we have developed methods to generate distinct... R.N. Jørgensen, S. Skovsen, O. Green, C.G. Sørensen |
24. Voronoi-based Ant Colony Optimization Approach: Autonomous Robotic Swarm Navigation for Crop Disease DetectionThe early detection of agricultural diseases is essential for sustaining food production and economic viability over the long term. To improve disease detection in agriculture, this paper presents an innovative computational approach that utilizes the Voronoi-based Ant Colony Optimization (V-ACO) algorithm with Swarm Robotics (SR). Inspired by the social behaviors observed in insect colonies such as honeybees and ants, SR offers new opportunities for precision farming. SR utilizes the coordin... S. Gummi, M. Alahe, Y. Chang, C. Pack |
25. Partial Fruitlet Cutting Approach for Robotic Apple ThinningEarly season thinning of apple fruitlets is a crucial task in commercial apple farming, traditionally accomplished through chemical sprays or labor-intensive manual operations. These methods, however, are faced with the challenges of diminishing labor availability as well as environmental and/or economic sustainability. This research examines 'partial fruitlet cutting,' a novel nature-assisted strategy, as an alternative method for automated apple thinning in orchards. The study hypot... R. Sapkota, M. Karkee |
26. Real Time Application of Neural Networks and Hardware Accelerated Image Processing Pipeline for Precise Autonomous Agricultural SystemsModern agriculture is increasingly turning to automation and precision technology to optimize crop management. In this context, our research addresses the development of an autonomous pesticide spraying rover equipped with advanced technology for precision agriculture. The primary goal is to use a neural network for real-time aphid detection in Sorghum crops, enabling targeted pesticide application only to infested plants. To accomplish this, we've integrated cutting-edge technologies and... J. Raitz persch, R. Harsha chepally, N.K. Piya |
27. Advancements in Agrivoltaics: Autonomous Robotic Mowing for Enhanced Management in Solar FarmsAgrivoltaics – the co-location of solar energy installations and agriculture beneath or between rows of photovoltaic panels – has gained prominence as a sustainable and efficient approach to land use. The US has over 2.8 GW in Agrivoltaics, integrating crop cultivation with solar energy. However, effective vegetation management is critical for solar panel efficiency. Flat, sunny agricultural land accommodates solar panels and crops efficiently. The challenge lies in managing grass... S. Behera, S. Pitla |
28. Implementation of Autonomous Material Re-filling Using Customized UAV for Autonomous Planting OperationsThis project introduces a groundbreaking use case for customized Unmanned Aerial Vehicles (UAVs) in precision agriculture, focused on achieving holistic autonomy in agricultural operations through multi-robot collaboration. Currently, commercially available drones for agriculture are restrictive in achieving collaborative autonomy with the growing number of unmanned ground robots, limiting their use to narrow and specific tasks. The advanced payload capacities of multi-rotor UAVs,... V. Muvva, H. Mwunguzi, S. Pitla, K. Joseph |
29. Advancements in Agricultural Robots for Specialty Crops: a Comprehensive Review of Innovations, Challenges, and ProspectsThe emergence of robot technology presents a timely opportunity to revolutionize specialty crop production, offering crucial support across various activities such as planting, supporting general traits, and harvesting. These robots play a pivotal role in keeping stakeholders up-to-date of developments in their production fields, while providing them the capability to automate laborious tasks. Then, to elucidate the advancements in this domain, we present the results of a comprehensive review... M. Barbosa, R. Santos, L. Sales, L. Oliveira |
30. Utilizing ArUco Markers to Define Implement BoundariesJohn Deere and Blue River Technology’s autonomous tillage system combines multidisciplinary efforts and cutting-edge technology to achieve Level 5—Unsupervised Autonomy. To create this engineering marvel, countless parameters need defined to ensure safe operation of the system; some of these parameters are static, while other of these parameters are dynamic. One particular set of parameters define the tillage implement’s boundaries for the software stack to utilize, and toda... R. Sleichter |
31. Automated Detection and Length Estimation of Green Asparagus Towards Selective HarvestingGreen asparagus is an important vegetable crop in the United States (U.S.). Harvesting the crop is notoriously labor-intensive, accounting for over 50% of production costs. There is an urgent need to develop harvesting automation technology for the U.S. asparagus industry to remain sustainable and competitive. Despite previous research and developments on mechanical asparagus harvesting, no practically viable products are available because of their low harvest selectivity and significant yiel... J. Xu, Y. Lu |
32. Agrosense: AI-enabled Sensing for Precision Management of Tree CropsMonitoring the tree inventory and canopy density and height frequently is critical for researchers and farm managers. However, it is very expensive and challenging to manually complete these tasks weekly. Therefore, a low-cost and artificial intelligence (AI) enhanced sensing system, Agrosense, was developed for tree inventory, canopy height measurement, and tree canopy density classification in this study. The sensing system mainly consisted of four RGB-D cameras, two Jetson Xavier NX, and o... C. Zhou, Y. Ampatzidis, H. Guan, W. Liu, A. De oliveira costa neto, S. Kunwar, O. Batuman |
33. SurePoint Ag Systems - Sponsor Presentation... B. Downing |