Proceedings
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| Filter results9 paper(s) found. |
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1. Field Phenotyping Infrastructure in a Future World - Quantifying Information on Plant Structure and Function for Precision Agriculture and Climate ChangePhenotyping in the field is an essential step in the phenotyping chain. Phenotyping begins in the well-defined, controlled conditions in laboratories and greenhouses and extends to heterogeneous, fluctuating environments in the field. Field measurements represent a significant reference point for the relevance of the laboratory and greenhouse approaches and an important source of information on potential mechanisms and constraints for plant performance tested at controlled conditions. In this... O. Muller, M.P. Cendrero mateo, H. Albrecht, F. Pinto, M. Mueller-linow, R. Pieruschka, U. Schurr, U. Rascher, A. Schickling, B. Keller |
2. Detection of Potato Beetle Damage Using Remote Sensing from Small Unmanned Aircraft SystemsRemote sensing with small unmanned aircraft systems (sUAS) has potential applications in agriculture because low flight altitudes allow image acquisition at very high spatial resolution. We set up experiments at the Oregon State University Hermiston Agricultural Research and Extension Center (HAREC) to assess advantages and disadvantages of sUAS for precision farming. In 2014, we conducted an experiment in irrigated potatoes with 4 levels of artificial infestation by Colorado Potato Beetles.... E. Hunt, S.I. Rondon, A.E. Bruce, R.W. Turner, J.J. Brungardt |
3. 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 after... Y. Hirai, Y. Beppu, Y. Mori, K. Tomita, K. Hamagami, K. Mori, S. Uchida, S. Inaba |
4. Utilizing Weather, Soil, and Plant Condition for Predicting Corn Yield and Nitrogen Fertilizer ResponseImproving corn (Zea mays L.) nitrogen (N) fertilizer rate recommendation tools should increase farmer’s profits and help mitigate N pollution. Weather and soil properties have repeatedly been shown to influence crop N need. The objective of this research was to improve publicly-available N recommendation tools by adjusting them with additional soil and weather information. Four N recommendation tools were evaluated across 49 N response trials conducted in eight U.S. states over three growing... N.R. Kitchen, M.A. Yost, C.J. Ransom, G. Bean, J. Camberato, P. Carter, R. Ferguson, F. Fernandez, D. Franzen, C. Laboski, E. Nafziger, J. Sawyer |
5. Spatial and Temporal Factors Impacting Incremental Corn Nitrogen Fertilier Use EfficiencyCurrent tools for making crop N fertilizer recommendations are primarily based on plot and field studies that relate the recommendation to the economic optional N rate (EONR). Some tools rely entirely on localized EONR (e.g., MRTN). In recent years, tools have been developed or adapted to account for within-field variation in crop N need or variable within season factors. Separately, attention continues to elevate for how N fertilizer recommendations might account for environmental... N.R. Kitchen, C.J. Ransom, J.S. Schepters, J.L. Hatfield, R. Massey |
6. Mapping Soil Health and Grain Quality Variations Across a Corn Field in TexasSoil health is a key property of soils influencing grain yield and quality. Within-field mapping of soil health index and grain quality can help farmers and managers to adjust site-specific farm management decisions for economic benefits. A study was conducted to map within-field soil health and grain protein and oil content variations using apparent electrical conductivity (ECa) and terrain attributes as their predictors. Two hundred and two topsoil samples were analyzed to determine soil health... K. Adhikari, D.R. Smith, C. Hajda, P.R. Owens |
7. Estimating Water and Nitrogen Deficiency in Corn Using a Multi-parameter Proximal SensorThe Crop Circle Phenom (CCP) is an innovative integrated proximal sensor that can be potentially used to perform in-season diagnosis of nitrogen and water status. In addition to measuring spectral reflectance in several bands including the red, red edge, and near-infrared wavelengths, the CCP can also measure canopy and air temperatures and provides several parameters that can be associated with chlorophyll content, crop vigor, and water status. These capabilities differentiate the CCP from other... L. Lacerda, Y. Miao, V. Sharma, A. E. flores, A. Kechchour, J. Lu |
8. In-season Diagnosis of Corn Nitrogen and Water Status Using UAV Multispectral and Thermal Remote SensingFor irrigated corn fields, how to optimize nitrogen (N) and irrigation simultaneously is a great challenge. A promising strategy is to use remote sensing to diagnose corn N and water status during the growing season, which can then be used to guide in-season variable rate N application and irrigation management. The objective of this study was to evaluate the effectiveness of UAV multispectral and thermal remote sensing in simultaneous diagnosis of corn N and water status. Two field experiments... Y. Miao, A. Kechchour, V. Sharma, A. Flores, L. Lacerda, K. Mizuta, J. Lu, Y. Huang |
9. On-farm Evaluation of the Potential Benefits of Variable Rate Seeding for Corn in MinnesotaMany farmers in Minnesota are interested in adopting variable rate seeding technology for corn, however, little has been reported about their potential benefits. The objectives of this study were to 1) determine within-field variability of optimal seeding rates, and 2) evaluate the potential benefits of variable rate seeding in commercial corn fields in Minnesota. Four on-farm variable rate seeding trials were conducted in Minnesota in 2022 and 2023, with seeding rates ranging from 31,000 to 41,000... Y. Miao, A. Kechchour, S. Folle, K. Mizuta |