Bioresource and Agricultural Engineering Commons^™

Composting Reduces The Risks Of Resistome In Beef Cattle Manure At The Transcriptional Level, Yuepeng Sun, Zachery R. Staley, Bryan Woodbury, Jean-Jack Riethoven, Xu Li

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Transcriptomic evidence is needed to determine whether composting is more effective than conventional stockpiling in mitigating the risk of resistome in livestock manure. The objective of this study is to compare composting and stockpiling for their effectiveness in reducing the risk of antibiotic resistance in beef cattle manure. Samples collected from the center and the surface of full-size manure stockpiling and composting piles were subject to metagenomic and metatranscriptomic analyses. While the distinctions in resistome between stockpiled and composted manure were not evident at the DNA level, the advantages of composting over stockpiling were evident at the transcriptomic level in …

Field Research Report: Results From The Enreec Vri Field For The 2021, 2022, And 2023 Crop Seasons, Derek M. Heeren, Ali T. Mohammed, Eric Wilkening, Christopher M. U. Neale, Alan L. Boldt, Ankit Chandra, Precious Nneka Amori, Ivo Z. Goncalves, Yeyin Shi, Guillermo R. Balboa

Department of Agricultural and Biological Systems Engineering: Presentations and White Papers

Long-term irrigation management research has been conducted from 2014 to 2023 for corn and soybean at the Eastern Nebraska Research, Extension, and Education Center (ENREEC) Variable Rate Irrigation (VRI) Field located in subhumid east-central Nebraska (in the Lower Platte North Natural Resources District). The objective of this report was to present the overall results from the VRI Field for 2021 to 2023. Across the three growing seasons, there were the following irrigation treatments: Best Management Practice (BMP), 50% BMP, 125% BMP, rainfed, Spatial ET Modeling Interface (SETMI), SDD1, SDD2, machine-learning-based Cyber-Physical System (CPS), a student team recommended rate, and industry …

Soil Nitrate Prediction Using Ftir-Atr, Vis-Nir, And Raman Spectroscopy, Sabiha Ferdous

Department of Agricultural and Biological Systems Engineering: Dissertations, Theses, and Student Research

Fourier transform infrared spectroscopy (FTIR) combined with Attenuated total reflectance (ATR), Visible-Near Infrared spectroscopy (Vis-NIR), and Raman spectroscopy (RS) are non-destructive techniques for rapid determination of nitrogen compounds in soil. Leveraging FTIR-ATR and Vis-NIR spectra using partial least squares regression (PLSR) modeling, the study aims to predict soil nitrate content and explored the feasibility of Raman spectroscopy to detect nitrate (NO₃^-), nitrite (NO₂^-), and ammonium (NH₄⁺) in soil. Soil samples were collected from four different fields, dried, sieved (2mm), and then used for collecting spectra (FTIR-ATR and Vis-NIR). Laboratory analysis was …

Techno-Economic Feasibility Of Polyhydroxybutyrate (Phb) Production From Corn Stover, Jey-R Ventura, Ruby Lynn Ventura

The Philippine Agricultural Scientist

This research evaluated the techno-economic feasibility of polyhydroxybutyrate (PHB) production using corn stover as a substrate for the fermentation process. The target PHB plant production was set at 1000 t PHB per yr, with a daily production of about 3 t PHB. The required corn stover biomass was around 12 000 t per yr. The economic analysis of this study suggested that 91.13 M US$ is needed to put up the targeted plant production capacity, with 94% of the total investment to be allotted to the direct fixed capital cost. Annual operating cost was rated at 4.71 M US$ per …

Optimization Of Factors Affecting The Performance Of A Fluidized Bed Dryer, Soner Celen, Sultan Pektas

The Philippine Agricultural Scientist

This study investigated the theoretical, analytical, and experimental effects of parameters such as bed height, air velocity, and air temperature on drying using a fluidized bed dryer. The objective was to examine how these parameters influence the drying process of salt products in a pilot fluidized bed dryer and establish the foundation for the development of a future full-scale machine. Salt products with an initial moisture content of 3% were used in all experimental trials. The pressure drop was determined by calculating the minimum fluidization rate, Archimedes and Reynolds number. The calculated values were compared with the analyses conducted using …

Design, Fabrication, And Determination Of The Optimum Working Conditions Of A Peanut (Arachis Hypogaea L.) Pneumatic Bagging System, Selcuk Ugurluay, Ali Somay

The Philippine Agricultural Scientist

The peanut bagging process is not mechanized, it requires a large amount of human labor. In addition, the shovel or canister used in bagging breaks the peanut shell that causes losses. The purpose of this study is to reduce the required workforce by mechanizing the peanut bagging process, and to determine the optimum working criteria (hose diameter and air velocity) of the prototype machine. A peanut pneumatic bagging machine powered by a tractor power takeoff (PTO) was designed and fabricated to convey peanut pods from the ground and fill the product into the bags. To determine the optimum working conditions …

Quantifying Wildfire Drivers And Predictability In Boreal Peatlands Using A Two-Step Error-Correcting Machine Learning Framework In Tefire V1.0, Rongyun Tang, Mingzhou Jin, Daniel M. Ricciuto, Anping Chen, Yulong Zhang

Biological and Agricultural Engineering Faculty Publications and Presentations

Wildfires are becoming an increasing challenge to the sustainability of boreal peatland (BP) ecosystems and can alter the stability of boreal carbon storage. However, predicting the occurrence of rare and extreme BP fires proves to be challenging, and gaining a quantitative understanding of the factors, both natural and anthropogenic, inducing BP fires remains elusive. Here, we quantified the predictability of BP fires and their primary controlling factors from 1997 to 2015 using a two-step correcting machine learning (ML) framework that combines multiple ML classifiers, regression models, and an error-correcting technique. We found that (1) the adopted oversampling algorithm effectively addressed …

A Systematic Review Of Fourth Industrial Revolution Technologies In Smart Irrigation: Constraints, Opportunities, And Future Prospects For Sub-Saharan Africa, Joshua Wanyama, Erion Bwambale, Shafik Kiraga, Abia Katimbo, Prossie Nakawuka, Isa Kabenge, Isaac Oluk

Department of Agricultural and Biological Systems Engineering: Faculty Publications

The adoption of Fourth Industrial Revolution (4IR) technologies has revolutionized agricultural practices worldwide. However, their application in the context of sub-Saharan Africa remains a critical challenge. This study presents a systematic review that investigates the potential of 4IR technologies in smart irrigation. Sub- Saharan Africa faces multiple agricultural challenges, exacerbated by climate change, water scarcity, and inefficient irrigation practices. The need for sustainable, water-efficient, and data-driven irrigation systems is urgent to ensure food security and economic development in the region. This study addresses a crucial knowledge gap by assessing the constraints, opportunities, and prospects of implementing 4IR technologies for smart …

Fair Fault-Tolerant Approach For Access Point Failures In Networked Control System Greenhouses, Mohammed Ali Yaslam Ba Humaish

Theses and Dissertations

Greenhouse Networked Control Systems (NCS) are popular applications in modern agriculture due to their ability to monitor and control various environmental factors that can affect crop growth and quality. However, designing and operating a greenhouse in the context of NCS could be challenging due to the need for highly available and cost-efficient systems. This thesis presents a design methodology for greenhouse NCS that addresses these challenges, offering a framework to optimize crop productivity, minimize costs, and improve system availability and reliability. It contributes several innovations to the field of greenhouse NCS design. For example, it recommends using the 2.4GHz frequency …

Impacts Of Farrowing Pen Design, Season, And Sow Parity On Litter Performance And Piglet Mortality, Verônica Madeira Pacheco, Tami M. Brown-Bandl, Gary A. Rohrer, Rafael Vieira De Sousa, Luciane Silva Martello

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Piglet mortality during lactation is a significant concern in swine production, influenced by complex interactions involving sow, piglet, environmental, and management factors. While crushing by the sow may be the ultimate cause of piglet mortality, there are many factors influencing the outcome, including parity, thermal stress, and animal housing systems. New farrowing systems are continuously being developed; however, it is difficult for producers to make decisions without any scientific basis. This study aimed to assess the impact of different farrowing pen layouts on piglet performance, considering parity and season. A total of 546 sows and 9123 piglets were monitored across …

Enhancing Estimation Of Cover Crop Biomass Using Field-Based High-Throughput Phenotyping And Machine Learning Models, Geng Bai, Katja Koehler-Cole, David Scoby, Vesh R. Thapa, Andrea D. Basche, Yufeng Ge

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Incorporating cover crops into cropping systems offers numerous potential benefits, including the reduction of soil erosion, suppression of weeds, decreased nitrogen requirements for subsequent crops, and increased carbon sequestration. The aboveground biomass (AGB) of cover crops strongly influences their performance in delivering these benefits. Despite the significance of AGB, a comprehensive field-based high-throughput phenotyping study to quantify AGB of multiple cover crops in the U.S. Midwest has not been found. This study presents a two-year field experiment carried out in Eastern Nebraska, USA, to estimate AGB of five different cover crop species [canola (Brassica napus L.), rye (Secale …

An Automated On-The-Go Unloading System Reduces Harvest Operator Stress Relative To Manual Operation, Travis A. Burgers, Kusha Kamarei, Mukund Vora, Matthew Horne

Mechanical Engineering Faculty Publications

On-the-go unloading improves harvest operational efficiency, but it requires skilled labor because it is challenging and stressful to balance numerous concurrent tasks. Harvest automation reduces workload, stress, and fatigue. The objective of this study was to determine if using a commercially available, automated on-the-go unloading system (Raven Cart Automation TM , RCA, Raven Industries) would reduce operator stress com- pared to manual operation. Nine grain cart tractor operators and six combine operators participated in this study. Operators performed their typical harvest operation, except to alternate on-the-go unloading using RCA or operating manually. Skin conductance (elec- trodermal activity) was measured with …

Stage And Discharge Prediction From Documentary Time-Lapse Imagery, Kenneth W. Chapman, Troy E. Gilmore, Mehrube Mehrubeoglu, Christian D. Chapman, Aaron R. Mittelstet, John E. Stranzl Jr.

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Imagery from fixed, ground-based cameras is rich in qualitative and quantitative information that can improve stream discharge monitoring. For instance, time-lapse imagery may be valuable for filling data gaps when sensors fail and/or during lapses in funding for monitoring programs. In this study, we used a large image archive (> 40,000 images from 2012 to 2019) from a fixed, ground-based camera that is part of a documentary watershed imaging project (https://plattebasintimelapse.com/). Scalar image features were extracted from daylight images taken at one-hour intervals. The image features were fused with United States Geological Survey stage and discharge data as …

Student Use Of Anchors And Metacognitive Strategies In Reflection, Anu Singh, Heidi A. Diefes-Dux

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Context: Self-regulation, a skillset involving taking charge of one’s own learning processes, is crucial for workplace success. Learners develop self-regulation skills through reflection where they recognize weaknesses and strengths by employing metacognitive strategies: planning, monitoring, and evaluating. Use of anchors assists learners’ engagement in reflection. Purpose or Goal: The purpose of this work was to gain insight into students’ use of anchors when reflecting on their learning. The two research questions: (1) To what extent do students link their self-evaluation and learning objective (LO) self-ratings to their reflections? and (2) What dimensions and level of metacognitive strategies do students use …

Classification Of Sow Postures Using Convolutional Neural Network And Depth Images, Md Towfiqur Rahman, Tami M. Brown-Brandl, Gary A. Rohrer, Sudhendu R. Sharma, Yeyin Shi

Department of Agricultural and Biological Systems Engineering: Faculty Publications

The United States swine industry reports an average preweaning mortality of approximately 16% where approximately 6% of them are attributed to piglets overlayed by sows. Detecting postural transitions and estimating sows’ time budgets for different postures are valuable information for breeders and engineering design of farrowing facilities to eventually reduce piglet death. Computer vision tools can help monitor changes in animal posture accurately and efficiently. To create a more robust system and eliminate varying lighting issues within a day including daytime/ nighttime differences, there is an advantage to using depth cameras over digital cameras. In this study, a computer vision …

Machine Learning-Based Disease Classification In Tomato (Solanum Lycopersicum) Plants = Klasifikasi Penyakit Berbasis Pembelajaran Mesin Pada Tanaman Tomat (Solanum Lycopersicum), Md Towfiqur Rahman, Sudipto Dhar Dipto, Israt Jahan June, Abdul Momin, Muhammad Rashed Al Mamun

Department of Agricultural and Biological Systems Engineering: Faculty Publications

English abstract

In Bangladesh, tomato cultivation faces significant challenges due to its susceptibility to various microorganisms, parasites, and bacterial infections. Typically, the early symptoms of these diseases first appear in roots and leaves, complicating timely detection. This study addresses the challenge of timely and accurate detection of diseases in tomato plants, crucial for effective plant protection management. Conventional manual inspection methods are time-consuming and subjective, resulting in delays in implementing necessary protection measures. Therefore, an image processing technique and machine learning algorithms were used for rapid and robust detection of diseases in tomato plant leaves, aiming to streamline the detection …

Effects Of Crate Size On Mortality And Postural Behavior In Post-Farrowing Sows, Md Towfiqur Rahman, Tami M. Brown-Brandl, Gary A. Rohrer, Sudhendu R. Sharma, Yeyin Shi

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Preweaning mortality (PWM) is a economic and animal well-being issue for swine producers in the US. On average, producers face about a 16% pre-weaning mortality. A significant portion of this, around 6%, is because sows accidentally overlay their piglets in farrowing crates. The posture behavior of sow plays a vital role in overlaying piglets and this behavior has a significant effect on farrowing crate dimensions. This study aims to explore the interplay between farrowing crate size, mortality rates, and postural behavior in post-farrowing sows. This study employed three farrowing stalls: Traditional (T), Expanded creep area (C), and Expanded sow area …

Inaugural Future Of Bse Days: Workshop Report, Mark Stone

Department of Agricultural and Biological Systems Engineering: Presentations and White Papers

The inaugural Future of BSE Days (FBD) event, held on May 2-3, 2024, brought together the Biological Systems Engineering (BSE) community to discuss and shape the future of work and learning within the field. The event was designed to foster collaboration between faculty, students, industry leaders, and alumni, with the goal of reimagining the department’s educational approach, enhancing industry partnerships, and preparing students for the challenges of tomorrow. Over the course of two days, participants engaged in insightful discussions, workshops, and presentations that highlighted both the strengths of the department and opportunities for growth.

The workshop resulted in several key …

Classification Of Sow Postures Using Convolutional Neural Network And Depth Images, Md Towfiqur Rahman, Tami M. Brown-Brandl, Gary A. Rohrer, Sudhendu R. Sharma, Yeyin Shi

Department of Agricultural and Biological Systems Engineering: Faculty Publications

The United States swine industry reports an average preweaning mortality of approximately 16% where approximately 6% of them are attributed to piglets overlayed by sows. Detecting postural transitions and estimating sows’ time budgets for different postures are valuable information for breeders and engineering design of farrowing facilities to eventually reduce piglet death. Computer vision tools can help monitor changes in animal posture accurately and efficiently. To create a more robust system and eliminate varying lighting issues within a day including daytime/ nighttime differences, there is an advantage to using depth cameras over digital cameras. In this study, a computer vision …

Development And Evaluation Of A Retrofittable Variable Rate Applicator Controller, Ahmed Abdalla

Electronic Theses and Dissertations

The need to optimize resource utilization while increasing crop productivity is paramount. This research proposes a Low-cost Retrofittable Variable Rate Applicator Controller (VRAC) that aims to leverage the adoption of Variable Rate Technologies. The controller operates via the Raspberry Pi platform, a Global Positioning System (GPS), a stepper motor drive, and an anti-slip wheel encoder. The VRAC allows precise, on-the-fly control of variable-rate application of farming inputs. It utilizes GPS with 10 cm accuracy to pinpoint geographic coordinates in real-time. A wheel encoder measures traveling speed with a slip-resistant wheel design for precise RPM readings. The Raspberry processes the data, …