Bioresource and Agricultural Engineering Commons^™

Principal Variable Selection To Explain Grain Yield Variation In Winter Wheat From Features Extracted From Uav Imagery, Jiating Li, Arun-Narenthiran Veeranampalayam-Sivakumar, Madhav Bhatta, Nicholas D. Garst, Hannah Stoll, P. Stephen Baenziger, Vikas Belamkar, Reka Howard, Yufeng Ge, Jiating Li

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Background: Automated phenotyping technologies are continually advancing the breeding process. However, collecting various secondary traits throughout the growing season and processing massive amounts of data still take great efforts and time. Selecting a minimum number of secondary traits that have the maximum predictive power has the potential to reduce phenotyping efforts. The objective of this study was to select principal features extracted from UAV imagery and critical growth stages that contributed the most in explaining winter wheat grain yield. Five dates of multispectral images and seven dates of RGB images were collected by a UAV system during the spring growing …

Performance Validation Of A Multi-Channel Lidar Sensor: Assessing The Effects Of Target Height And Sensor Velocity On Measurement Error, Surya S. Dasika, Michael P. Sama, L. Felipe Pampolini, Christopher B. Good

Biosystems and Agricultural Engineering Faculty Publications

The objective of this study was to determine the effects of sensor velocity and target height above ground level on height measurement error when using a multi-channel LiDAR sensor. A linear motion system was developed to precisely control the dynamics of the LiDAR sensor in an effort to remove uncertainty in the LiDAR position and velocity while under motion. The linear motion system allowed the LiDAR to translate forward and backward in one direction parallel to the ground. A user control interface was developed to operate the system under different velocity profiles and to log LiDAR data synchronous to the …

Water Effects On Optical Canopy Sensing For Late-Season Site-Specific Nitrogen Management Of Maize, Tsz Him Lo, Daran Rudnick, Brian Krienke, D. M. Heeren, Yufeng Ge, Tim M. Shaver

Department of Agricultural and Biological Systems Engineering: Faculty Publications

The interpretation of optical canopy sensor readings for determining optimal rates of late-season site-specific nitrogen application to corn (Zea mays L.) can be complicated by spatially variable water sufficiency, which can also affect canopy size and/or pigmentation. In 2017 and 2018, corn following corn and corn following soybeans were subjected to irrigation×nitrogen fertilizer treatments in west central Nebraska, USA, to induce variable water sufficiency and variable nitrogen sufficiency. The vegetation index-sensor combinations investigated were the normalized difference vegetation index (NDVI), the normalized difference red edge index (NDRE), and the reflectance ratio of near infrared minus red edge over near …

Microcontroller Based Granular Urea Application Attachment For Rice Transplanter, Md Towfiqur Rahman, Md Monjurul Alam, Md Mosharraf Hossain, Muhammad Rashed Al Mamun

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Transplanting and fertilizer application for rice production in Bangladesh are tedious, time consuming and laborious task, and mostly done manually. Mechanical transplanting of rice becoming popular in the country in recent years and few machines have been developed for granular urea deep placement, however, having some limitations. Placing granular urea precisely along with rice transplanting, an attempt was under taken to design and fabricate an electronic control granular urea applicator to be attach with a 4-row walk behind type rice transplanter. Fabrication of the electronic granular urea applicator was done in the workshop of the Department of Farm Power and …

Variability Of E. Coli In Streambed Sediments And Its Implication For Water Quality, Sadia Salam

Electronic Theses and Dissertations

Fecal indicator bacteria (FIB), including E. coli, are the number one cause of water quality impairments in the United States according to the USEPA. FIB are used as a predictor to identify the possible presence of pathogens in waterbodies. E. coli is a useful indicator of gastrointestinal (GI) related illnesses from contact with fresh water. While surface water is routinely monitored for water quality, streambed sediments are rarely considered as a source of FIB to the overlying water column. This study focuses on understanding the variation of E. coli concentrations in streambed sediments and the potential impact of sediment sources …

Lignocellulosic Biomass Derived Activated Carbon For Energy Storage And Adsorption, Changle Jiang

Graduate Theses, Dissertations, and Problem Reports (ETD)

Lignocellulosic biomass has been converted to hierarchical porous carbon materials which possess macro-, meso- and micro-pores. The natural structure of porous lignocellulosic structure was preserved during activation with further developed porosity by the activation. The activated carbon can be well applied to electrochemical double layer capacitor for transportation storage of ions as well as adsorbent materials for metal ion removal from wastewater.

The first chapter of this dissertation presents an introduction of biomass derived carbon and its applications. In the second chapter, both direct and indirect activation methods using carbon dioxide were adopted in this study. The results show that …

Improving Retrievals Of Crop Vegetation Parameters From Remote Sensing Data, Nathaniel Levitan

Dissertations and Theses

Agricultural systems are difficult to model because crop growth is driven by the strongly nonlinear interaction of Genotype x Environment x Management (G x E x M) factors. Due to the nonlinearity in the interaction of these factors, the amount of data necessary to develop and utilize models to accurately predict the performance of agricultural systems at an operational scale is large. Satellite remote sensing provides the potential to vastly increase the amount of data available for modelling agricultural systems as a result of its high revisit time and spatial coverage. Unfortunately, there have been significant difficulties in deploying remote …