Proceedings :: International Society of Precision Agriculture

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Menegasso, A.E

Sharma, V

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Authors

Sobjak, R

Bazzi, C.L

Schenatto, K

Oliveira, W.K

Menegasso, A.E

Dhillon, R

Takoo, G

Sharma, V

Nagle, M

Topics

Artificial Intelligence (AI) in Agriculture

Data Analytics for Production Ag

Type

Poster

Oral

Year

2024

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Filter results2 paper(s) found.
1. AgDataBox-IA – Web Application with Artificial Intelligence for Agricultural Data Analysis in Precision Agriculture Agriculture has been continually evolving, incorporating hardware, software, sensors, aerial surveys, soil sampling for chemical, physical, and granulometric analysis (based on sample grids), and microclimatic data, leading to a substantial volume of data. This requires platforms to store, manage, and transform these data into actionable information for decision-making in the field. In this regard, Artificial Intelligence (AI) is the most widely used tool globally to mine and transform vast data... R. Sobjak, C.L. Bazzi, K. Schenatto, W.K. Oliveira, A.E. Menegasso Download paper
2. Machine Learning Approach to Study the Effect of Weather and Proposed Climate Change Scenarios on Variability in the Ohio Corn and Soybean Yield Climate is one of the primary factors that affects agricultural production. Climate change and extreme weather events have raised concerns about its effect on crop yields. Climate change patterns affect the crop yield in many ways including the length of the growing season, planting and harvest time windows, precipitation amount and frequency, and the growing degree days. It is important to analyze the effect of climate change on yield variability for a better understanding of the effect... R. Dhillon, G. Takoo

Filter results2 paper(s) found.

1. AgDataBox-IA – Web Application with Artificial Intelligence for Agricultural Data Analysis in Precision Agriculture

Agriculture has been continually evolving, incorporating hardware, software, sensors, aerial surveys, soil sampling for chemical, physical, and granulometric analysis (based on sample grids), and microclimatic data, leading to a substantial volume of data. This requires platforms to store, manage, and transform these data into actionable information for decision-making in the field. In this regard, Artificial Intelligence (AI) is the most widely used tool globally to mine and transform vast data... R. Sobjak, C.L. Bazzi, K. Schenatto, W.K. Oliveira, A.E. Menegasso

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2. Machine Learning Approach to Study the Effect of Weather and Proposed Climate Change Scenarios on Variability in the Ohio Corn and Soybean Yield

Climate is one of the primary factors that affects agricultural production. Climate change and extreme weather events have raised concerns about its effect on crop yields. Climate change patterns affect the crop yield in many ways including the length of the growing season, planting and harvest time windows, precipitation amount and frequency, and the growing degree days. It is important to analyze the effect of climate change on yield variability for a better understanding of the effect... R. Dhillon, G. Takoo