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Negrini, R.P
Nugent, P
Vanino, S
Vail, B
Viator, R.P
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Authors
Nino, P
Vanino, S
Lupia, F
Altobelli, F
Vuolo, F
Namdarian, I
De Michele, C
Price, R.R
Johnson, R.M
Viator, R.P
Nugent, P
Neupane, J
Negrini, R.P
Miao, Y
Mizuta, K
Stueve, K
Kaiser, D
Coulter, J.A
Vail, B
Oster, Z
Weinhold, B
Vail, B
Mizuta, K
Miao, Y
Lu, J
Negrini, R.P
Pereira de Souza, F
Negrini, R.P
tao, H
Topics
Remote Sensing Applications in Precision Agriculture
Geospatial Data
Artificial Intelligence (AI) in Agriculture
Site-Specific Nutrient, Lime and Seed Management
Big Data, Data Mining and Deep Learning
On Farm Experimentation with Site-Specific Technologies
Type
Poster
Oral
Year
2012
2018
2024
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Authors

Filter results8 paper(s) found.

1. Applications for Precision Agriculture: the Italian Experience of SIRIUS Project

    This paper reports the results of the project SIRIUS (Sustainable Irrigation water management and River-basin... P. Nino, S. Vanino, F. Lupia, F. Altobelli, F. Vuolo, I. Namdarian, C. De michele

2. Development of an Overhead Optical Yield Monitor for a Sugarcane Harvester in Louisiana

A yield monitor is a device used to measure harvested crop weight per unit area for a specific location within a field.  The device documents yield variability in harvested fields and ultimately can be used to create a geographical-referenced yield map. Yield maps can be used to identify low yielding areas where poor soil fertility, disease, or pests may adversely affect yield.  Management practices can then be adjusted to correct these issues, resulting in an increase in yields and... R.R. Price, R.M. Johnson, R.P. Viator

3. Using Machine Vision to Build Field Maps of Forage Quality and the Need for Agriculture-specific Machine Vision Networks

Machine vision systems have truly come of age over the past decade. These networks are relatively simple to implement with systems such as YOLOv5 or the more recent YOLOv8. They are also relatively easy and computationally cheap to retrain to a custom data set, allowing for customization of these networks to new object detection and classification tasks. With this ease, it is no surprise that we are seeing an explosion of these networks and their application through all aspects of agriculture.... P. Nugent, J. Neupane

4. Within-field Spatial Variability in Optimal Sulfur Rates for Corn in Minnesota: Implications for Precision Sulfur Management

The ongoing decline in sulfur (S) atmospheric depositions and high yield crop production have resulted in S deficiency and the need for S fertilizer applications in corn cropping systems. Many farmers are applying S fertilizers uniformly across their fields. Little has been reported on the within-field spatial variability in optimal S rates and the potential benefits of variable rate S applications. The objectives of this study were to 1) assess within-field variability of optimal S rates (OSR),... R.P. Negrini, Y. Miao, K. Mizuta, K. Stueve, D. Kaiser, J.A. Coulter

5. Generative Modeling Method Comparison for Class Imbalance Correction

An image dataset, for use in object detection of hay bales, with over 6000 images of both good and bad hay bales was collected.  Unfortunately, the dataset developed a class imbalance, with more good bale images than bad bales.  This dataset class imbalance caused the bad bale class to over train and the good bale class to under train, severely impacting precision, and recall.  To correct this imbalance and provide a comparison of differing generative modeling methods; three different... B. Vail, Z. Oster, B. Weinhold

6. Machine Vision in Hay Bale Production

The goal of this project is to develop a system capable of real-time detection, pass/fail classification, and location tracking of large square hay bales under field conditions.  First, a review of past and current methods of object detection was carried out.  This led to the selection of the YOLO family of detectors for this project.  The image dataset was collected through help from our sponsor, collection of images from the K-STATE research farm, and images collected from the... B. Vail

7. Evaluating Different Strategies to Analyze On-farm Precision Nitrogen Trial Data

On-farm trials are being conducted by more and more researchers and farmers. On-farm trials are very different to traditional small plot experiments due to the existence of significant within-field variability in soil-landscape conditions. Traditional statistical techniques like analysis of variance (ANOVA) are commonly adopted for on-farm trial analysis to evaluate overall performance of different treatments, assuming uniform environmental and management factors within a field. As a result, the... K. Mizuta, Y. Miao, J. Lu, R.P. Negrini

8. Optimizing Chloride (Cl) Application for Enhanced Agricultural Yield

The optimization of chloride (Cl-) application rates is crucial for enhancing crop yields and reducing environmental impact in agricultural systems. This study investigates the relationship between chloride application rates and wheat yields, focusing on Club wheat cultivation in a 19.76-hectare field in Washington State. The target yield was set at 3765 kilograms per hectare, with seeding conducted at 67.24 kilograms per hectare using conservation tillage practices. Potassium chloride... F. Pereira de souza, R.P. Negrini, H. Tao