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1. Nitrogen Loss In Corn Production Varies As A Function Of Topsoil DepthUnderstanding availability and loss potential of nitrogen for varying topsoil depths of poorly-drained claypan soil landscapes could help producers make improve decisions when managing crops for feed grain or bio-fuels. While it has been well documented that topsoil depth on these soils plays an important role in storing water for crop growth, it is not well known how this same soil... E. Allphin, N.R. Kitchen, K.A. Suddeth, A. Thompson |
2. Spatial And Vertical Distribution Of Soil P, K, And Mg Content In A Vineyard Of The Do Ca Rioja Using Grid And Target Sampling MethodsKnowledge of spatial variability of soil nutrient contents is very important to design a fertilization strategy based on the needs of the vine. Matching fertilization and nutritional plant needs is very important due to the influence of nutritional status of vineyards on productive and qualitative factors. The aim of this work was to study the spatial and vertical variability of P, K and Mg in a vineyard soil by two methods: (i) the grid sampling at three depth ranges (0-30,... O. Unamunzaga, A. Castell, G. Besga, R. Perez-parmo, A. Aizpurua |
3. Performance Of The Veris Nir Spectrophotometer For Mapping Soil C In The Palouse Soils Of Eastern WashingtonRecent advances in sensing technology have made measuring and mapping the dynamics of important soil properties that regulate carbon and nutrient budgets possible. The Veris Technologies (Salinas, KS) Near Infrared (NIR) Spectrometer is one of the first sensors available for collecting geo-referenced NIR soil spectra on-the-go. Field studies were conducted to evaluate the performance of the Veris NIR in wheat grown under both conventional and no-till management in the Palouse region of eastern... F. Pierce, E.M. Perry, S.L. Young, H.P. Collins, P.G. Carter |
4. Landscape Influences on Soil Nitrogen Supply and Water Holding Capacity for Irrigated Corn... T. Shaver, M. Schmer, S. Irmak, S. Van donk, B. Wienhold, V. Jin, A. Bereuter, D. Francis, D. Rudnick, N. Ward, L. Hendrickson, R. Ferguson, V.I. Adamchuk |
5. Water And Nitrogen Use Efficiency Of Corn And Switchgrass On Claypan Soil LandscapesClaypan soils cover a significant portion of Missouri and Illinois crop land, approximately 4 million ha. Claypan soils, characterized with a pronounced argilic horizon at or below the soil surface, can restrict nutrient availability and uptake, plant water storage, and water infiltration. These soil characteristics affect plant growth, with increasing depth of the topsoil above the claypan horizon having a strong positive correlation to grain crop production. In the case of low... A. Thompson, D.L. Boardman, N. Kitchen, E. Allphin |
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. Refractive Index Based Brix Measurement System for Sugar and Allied IndustriesAn attempt has been made to design optimization of Refractormetric based method for the measurement of Brix. Optimization of various constructional parameters including selection and location of source, prism and detector, position of source, angular position and height of source from prism plane, divergent angle of source, refractive index of prism, size of prism, the location of detector to pick up the optimum reflected light, refractive index of sample, critical angle, choice of suitable... M.L. Dongare, B.T. Jadhav, A.D. Shaligram |
8. Soil Spatial Variability Assessment and Precision Nutrient Management in Maize (Zea Mays L.)Investigations on soil spatial variability and precision nutrient management based targeted yield approach in maize was carried out at Agricultural research station (ARS), Mudhol (Karnataka), India under irrigated condition during 2013-14, 2014-15 and 2015-16. ARS, Mudhol is located in northern dry zone of Karnataka at 160 20! N latitude, 750 15! E longitude and at an altitude of 577.6 meter above mean sea level. To assess the spatial variability, the study area was divided into 20 x20 m size... M.P. Potdar, G.B. Balol, S.A. Satyareddi, B.T. Nadagouda , C.P. Chandrashekar |
9. Using Profitability Map to Make Precision Farming Decisions: A Case Study in MississippiRecent development in precision agriculture technologies have generated massive amount of geospatial data of farming, such as yield mapping, seeding rates, input applications, and so on. However, producers are still struggling to convert those precision data into farm management decisions to improve productivity and profitability of farming. Indeed, deriving accurate decisions at each site of the field requires complex and comprehensive modeling of crop yield responses to various... X. Li, K. Coble |
10. Field Phenotyping and an Example of Proximal Sensing of PhotosynthesisField phenotyping conceptually can be divided in five pillars 1) traits of interest 2) sensors to measure these traits 3) positioning systems to allow high throughput measurements by the sensors 4) experimental sites and 5) environmental monitoring. In this paper we will focus on photosynthesis as trait of interest, measured by remote active fluorescence. The sensor presented is the Light Induced Fluorescence Transient (LIFT) instrument. The LIFT instrument is integrated in three positioning systems.... O. Muller, B. Keller, L. Zimmermanm, C. Jedmowski, V. Pingle, K. Acebron, N. Zendonadi, A. Steier, R. Pieruschka, U. Schurr, U. Rascher, T. Kraska |
11. Comparison of Different Aspatial and Spatial Indicators to Assess Performance of Spatialized Crop Models at Different Within-field ScalesMost current crop models are point-based models, i.e. they simulate agronomic variables on a spatial footprint on which they were initially designed (e.g. plant, field, region scale). To assess their performances, many indicators based on the comparison of estimated vs observed data, can be used such as root mean square error (RMSE) or Willmott index of agreement (D-index) among others. However, shifting model use from a strategic objective to tactical in-season management is becoming a significant... D. Pasquel, S. Roux, B. Tisseyre, J.A. Taylor |
12. 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 qualitative... J. Aliloo, E. Abbasi, E. Karamidehkordi , E. Ghanbari parmehr, M. Canavari, G.-. Vitali |
13. AI Tools in Agri DSS Pipeline - the Case of Irrigated SugarbeetA general pipeline that can be associated to a DSS includes several steps. Data Collectionn includes Acquisition, extraction, and aggregation of data from previously identified and selected sources. Data Cleaning and preparation make data available for exploratory analysis that make them usable. Data Analysis is then applied to extract meaningful information e.g. by statistical and/or simulation models. Data are successively synthesized and visualized to make them clear to the decision-maker to... G.-. Vitali, C. Ferraz |
14. Optimizing Vineyard Crop Protection: an In-depth Study of Spraying Drone Operational ParametersIn modern agriculture, the precise and efficient application of agrochemicals is essential to ensure crop health and increase productivity while minimizing adverse environmental impacts. While traditional spraying methods have long been the cornerstone of crop protection, the introduction of unmanned aerial vehicles (UAVs), commonly known as drones), has led to a revolutionary era in agriculture. UAVs offer novel opportunities to improve agricultural practices by providing precision, efficiency,... V. Psiroukis, S. Fountas, H. Uyar, A. Balafoutis, A. Kasimati |