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Cutulle, M
Colaço, A.F
CARCEDO, A
Sapkota, T.B
Shovic, J
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Authors
Sapkota, T.B
Trevisan, R.G
Eitelwein, M.T
Colaço, A.F
Molin, J.P
Eitelwein, M.T
Trevisan, R.G
Colaço, A.F
Vargas, M.R
Molin, J.P
Maja, J.J
Abenina, M
Cutulle, M
Melgar, J
Liu, H
Wells, G
Shovic, J
Everett, M
Hunt, L
Everett, M
Shovic, J
Nocera Santiago, G.N
Cisdeli Magalhães, P
Ciampitti, I
Marziotte, L
CARCEDO, A
Gomez, F
CARCEDO, A
Diatta, A
Nagarajan, L
Prasad, V
Stewart, Z
Zingore, S
Ciampitti, I
Djighaly, P
CARCEDO, A
Ciampitti, I
Lucero, M.F
Zajdband, A
Hernandez, C
Ciampitti, I
CARCEDO, A
Cano, P.B
CARCEDO, A
Gomez, F
Hernandez, C
Gimenez, V
Ciampitti, I
Topics
Precision Nutrient Management
Spatial Variability in Crop, Soil and Natural Resources
Proximal Sensing in Precision Agriculture
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Wireless Sensor Networks and Farm Connectivity
Artificial Intelligence (AI) in Agriculture
Big Data, Data Mining and Deep Learning
Small Holders and Precision Agriculture
Geospatial Data
Country Representative Report
Type
Poster
Oral
Year
2010
2016
2022
2024
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Authors

Filter results11 paper(s) found.

1. Soil Quality Improvement Through Proper Combination Of Tillage, Nitrogen Fertilization And Cover Cropping Systems

No-tillage, N fertilization and cover cropping affect physical, chemical and biological qualities of soil. We investigated the effect of 15-yr of tillage systems, N fertilization and cover crops on soil organic matter, aggregation, bulk density and on microbial community in the sandy loam soil of central Italy. The soil in no-tillage (NT) system had 50% more organic matter and 3 folds higher aggregate stability than the soil in conventional tillage (CT) system. The NT system significantly increased... T.B. Sapkota

2. Sources of Information to Delineate Management Zones for Cotton

Cotton in Brazil is an input-intensive crop. Due to its cultivation in large fields, the spatial variability takes an important role in the management actions. Yield maps are a prime information to guide site-specific practices including delineation of management zones (MZ), but its adoption still faces big challenges. Other information such as historical satellite imagery or soil electrical conductivity might help delineating MZ as well as predicting crop performance. The objective of this work... R.G. Trevisan, M.T. Eitelwein, A.F. Colaço, J.P. Molin

3. On-the-go Measurements of pH in Tropical Soil

The objective of this study was to assess the performance of a mobile sensor platform with ion-selective antimony electrodes (ISE) to determine pH on-the-go in a Brazilian tropical soil. The field experiments were carried out in a Cambisol in Piracicaba-SP, Brazil. To create pH variability, increasing doses (0, 1, 3, 5, 7 and 9 Mg ha-1) of lime were added on the experimental plots (25 x 10 m) one year before the data acquisitions. To estimate soil pH levels we used a Mobile Sensor Platform... M.T. Eitelwein, R.G. Trevisan, A.F. Colaço, M.R. Vargas, J.P. Molin

4. Snap-shot Hyperspectral Camera for Potassium Prediction of Peach Trees Using Multivariate Analysis

Hyperspectral imaging (HSI) is an emerging technology being utilized in agriculture. This system could be used to monitor the overall health of plants or pest disease detection. As sensing technology advances, measuring nutrient levels and disease detection also progresses. This study aimed to predict the levels of potassium (K) content in peach leaves with the new snapshot hyperspectral camera. The study was conducted at the Clemson University Musser Fruit Research Farm (Seneca, SC, USA, 34.61... J.J. Maja, M. Abenina, M. Cutulle, J. Melgar, H. Liu

5. Data Gator: a Provisionless Network Solution for Collecting Data from Wired and Wireless Sensors

Advances in wireless sensor technology and data collection in precision agriculture enable farmers and researchers to understand operational and environmental dynamics. These advances allow the tracking of water usage, temperature variation, soil pH, humidity, sunlight penetration, and other factors which are crucial for trend prediction and analysis. Capitalizing on this advancement, however, requires data collection infrastructure using large and varied sensor networks. Adoption and implementation... G. Wells, J. Shovic, M. Everett

6. Recovery Mechanism for Real-time Precision Agriculture Sensor Networks: a Case Study

Variable rate technologies are lagging behind other precision agriculture technologies in terms of farmer adoption, and sensor networks have been identified as a necessary step to implement these improvements. However, sensor networks face many issues in terms of cost, flexibility, and reliability. In rugged outdoor environments, it cannot be assumed that a sensor network will maintain constant connectivity to a monitoring interface, even if data is still being collected onsite. This paper presents... L. Hunt, M. Everett, J. Shovic

7. Algorithm to Estimate Sorghum Grain Number from Panicles Using Images Collected with a Smartphone at Field-scale

An estimation of on-farm yield before harvest is important to assist farmers on deciding additional input use, time to harvest, and options for end uses of the harvestable product. However, obtaining a rapid assessment of on-farm yield can be challenging, even more for sorghum (Sorghum bicolor L.) crop due to the complexity for accounting for the grain number at field-scale. One alternative to reduce labor is to develop a rapid assessment method employing computer vision and artificial intelligence... G.N. Nocera santiago, P. Cisdeli magalhães, I. Ciampitti, L. Marziotte

8. An Open Database of Crop Yield Response to Fertilizer Application for Senegal

Food security is one of the major global challenges today.  Africa is one of the continents with the largest gaps in terms of challenges for food security. In Senegal, about 60% of the population resides in rural areas and the cropping systems are characterized as a low productivity system, low input and in reduced areas, smallholder subsistence systems. Increasing crop productivity would have a positive impact on food security in this country. One of the main factors limiting crop productivity... F. Gomez, A. Carcedo, A. Diatta, L. Nagarajan, V. Prasad, Z. Stewart, S. Zingore, I. Ciampitti, P. Djighaly

9. Exploring Crop Suitability in Senegal Across Global Warming Scenarios: an In-silico Approach

Food production systems in Africa are fragile and vulnerable to climate change. In this context, rising temperatures are the primary cause of the anticipated negative climate change impacts on crop yields. Future yield reductions poses a challenging setting for smallholders to attain self-sufficiency, but new opportunities for managing the risk via implementationof decisions towards mitigate these negative effects from an economic, nutritional, and productive standpoint. Therefore, the objectives... A. Carcedo, I. Ciampitti

10. Using Remote Sensing to Quantify Biomass in Alfalfa

Satellite images are a useful decision support tool to optimize management practices at on-farm scale. Based on this, the development of predictive tools to estimate pasture biomass can be a promising framework to determine the best cutting time, maximizing biomass without compromising yield parameters. Therefore, the main objective of this study was to develop a regression model that allows estimating a value of biomass to give as a recommendation to farmers. To collaborate in their decision... M.F. Lucero, A. Zajdband, C. Hernandez, I. Ciampitti, A. Carcedo

11. Trends in Agricultural Technology Advancements: Insights from US Patent Analysis

Meeting the demand for food, fiber, and fuel production while addressing environmental concerns and enhancing societal benefits underscores the need to transition to conservation approaches and sustainable intensification pathways in current agricultural cropping systems. Technological advances in agriculture offer promising opportunities to facilitate this transition. Following this rationale, this study aims to analyze prevailing trends in agricultural technology advancements. Active patents... P.B. Cano, A. Carcedo, F. Gomez, C. Hernandez, V. Gimenez, I. Ciampitti