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| Filter results9 paper(s) found. |
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1. 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 capable... R. Khosla, D.G. Westfall, L. Longchamps |
2. Testing The Author Sequence - FinalizeThis is just a test to verify the bug with the authors sequence. ... L. Longchamps, B. Panneton, D.G. Westfall, R. Khosla |
3. Spatial Variability Of Crop And Soil Properties In A Crop-livestock Integrated SystemThe knowledge of spatial variability soil properties is useful in the rational use of inputs, as in the site specific application of lime and fertilizer. The objective of this work was to map and evaluate the spatial variability of the crop, soil chemical and physical properties. The study was conducted in 2 areas of 6.9 and 11.7 ha of a Typic Haplustox in Sao Carlos, SP, Brazil. The summer crops corn and sorghum were sowed together to the forage crop Brachiaria brizantha in the system of crop-pasture... A.C. Bernardi, C.R. Grego, R.G. Andrade, C.M. Vaz, L.M. Rabello, R.Y. Inamasu |
4. Improving the Precision of Maize Nitrogen Management Using Crop Growth Model in Northeast ChinaThe objective of this project was to evaluate the ability of the CERES-Maize crop growth model to simulate grain yield response to plant density and N rate for two soil types in Northeast China, with the long-term goal of using the model to identify the optimum plant density and N fertilizer rate forspecific site-years. Nitrogen experiments with six N rates, three plant densities and two soil types were conducted from 2015 to 2017 in Lishu county, Jilin Province in Northeast China. The CERES-Maize... X. Wang, Y. Miao, W.D. Batchelor, R. Dong, D.J. Mulla |
5. Improving Active Canopy Sensor-Based In-Season N Recommendation Using Plant Height Information for Rain-Fed Maize in Northeast ChinaThe inefficient utilization of nitrogen (N) fertilizer due to leaching, volatilization and denitrification has resulted in environmental pollution in rain-fed maize production in Northeast China. Active canopy sensor-based in-season N application has been proven effective to meet maize N requirement in space and time. The objective of this research was to evaluate the feasibility of using active canopy sensor for guiding in in-season N fertilizer recommendation for rain-fed maize in Northeast... X. Wang, Y. Miao, T. Xia, R. Dong, G. Mi, D.J. Mulla |
6. Investigating Spatial Relationship of Apparent Electrical Conductivity with Turfgrass and Soil Characteristics in Sand-capped Golf Course FairwaysTurfgrass quality decreases when grown on fine textured soils that are irrigated with poor quality water. As a result, sand-capping (i.e., a sand layer above existing native soil) is now considered during golf course fairway renovation and construction. Mapping spatial variability of soil apparent electrical conductivity (ECa) has recently been suggested to have applications for precision turfgrass management (PTM) in native soil fairways, but sand-capped fairways have received less... C. Straw, B. Wyatt, A.P. Smith, K. Watkins, S. Hong, W. Floyd, D. Williams, C. Garza, T. Jansky |
7. In-season Nitrogen Management of Maize Based on Nitrogen Status and Lodging Risk PredictionDevelopment of effective precision nitrogen (N) management strategies is crucially important for food security and sustainable development. Lodging is one of the major constraints to increasing maize yield that can be induced by strong winds, and is also influenced by management practices, like N rate. When making in-season N application decisions, lodging risk should be considered to avoid yield loss. Little has been reported on in-season N management strategies that also incorporate lodging... R. Dong, Y. Miao, X. Wang |
8. Early Forecasting of Maize Lodging Risk Through Multi-period and Multi-source Data IntegrationLodging is a critical constraint on global maize (Zea mays L.) productivity, primarily through detrimental effects on both grain yield and quality. However, reliable methods to predict maize lodging risk early in the growing season are lacking, which hinders timely implementation of effective agronomic management interventions to increase crop lodging resistance and reduce corresponding yield losses. This work aimed to develop a feasible early season maize lodging risk prediction method... L. Dong, Y. Miao, X. Wang, P. Berry, D. Hatley, K. Kusnierek |
9. A Statistical Approach to Defining Coffee Management Zones: Integrating Apparent Soil Electrical Conductivity, Altimetry and Satelitte Indices for Moisture MonitoringCharacterizing the spatial and temporal behavior of soil and plant attributes represents the elementary step toward adoption precision agriculture. The expanding availability of multi-temporal remote sensing imagery with enhanced spatial resolution has rendered the delineation of management zones (MZ) an increasingly feasible strategy, especially when the intention is to carry out spatially differentiated interventions considering the vegetative vigor throughout the crop cycle or the plant yield.... E.A. Speranza, E.J. Ferreira, L.H. Bassoi, L.M. Rabello, C.M. Vaz, A. Torre-neto |