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Moreno, L.A

Khan, F.S

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Authors

Khan, F.S

Zaman, Q.U

Schumann, A.W

Madani, A

Percival, D.C

Farooque, A.A

Saleem, S.R

Khan, F.S

Rossi, C

Almeida, S.L

Sysskind, M.N

Moreno, L.A

Felipe dos Santos, A

Lacerda, L

Vellidis, G

Pilcon, C

Orlando Costa Barboza, T

Topics

Spatial Variability in Crop, Soil and Natural Resources

Artificial Intelligence (AI) in Agriculture

Type

Poster

Oral

Year

2012

2024

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Filter results2 paper(s) found.
1. Relationship of Soil Properties to Apparent Ground Conductivity in Wild Blueberry Fields One of the fundamental deficiencies in high value crops is the lack of detailed, up-to-date and pertinent geo-referenced soil information for site-specific crop management to improve productivity. This experiment was designed to estimate and map soil properties rapidly and reliably using an electromagnetic induction (EMI) method. Two wild blueberry... F.S. Khan, Q.U. Zaman, A.W. Schumann, A. Madani, D.C. Percival, A.A. Farooque, S.R. Saleem, F.S. Khan Download paper
2. Combining Remote Sensing and Machine Learning to Estimate Peanut Photosynthetic Parameters The environmental conditions in which plants are situated lead to changes in their photosynthetic rate. This alteration can be visualized by pigments (Chlorophyll and Carotenoids), causing changes in plant reflectance. The goal of this study was to evaluate the performance of different Machine Learning (ML) algorithms in estimating fluorescence and foliar pigments in irrigated and rainfed peanut production fields. The experiment was conducted in the southeast of Georgia in the United States in... C. Rossi, S.L. Almeida, M.N. Sysskind, L.A. Moreno, A. Felipe dos santos, L. Lacerda, G. Vellidis, C. Pilcon, T. Orlando costa barboza Download paper

Filter results2 paper(s) found.

1. Relationship of Soil Properties to Apparent Ground Conductivity in Wild Blueberry Fields

One of the fundamental deficiencies in high value crops is the lack of detailed, up-to-date and pertinent geo-referenced soil information for site-specific crop management to improve productivity. This experiment was designed to estimate and map soil properties rapidly and reliably using an electromagnetic induction (EMI) method. Two wild blueberry... F.S. Khan, Q.U. Zaman, A.W. Schumann, A. Madani, D.C. Percival, A.A. Farooque, S.R. Saleem, F.S. Khan

Download paper

2. Combining Remote Sensing and Machine Learning to Estimate Peanut Photosynthetic Parameters

The environmental conditions in which plants are situated lead to changes in their photosynthetic rate. This alteration can be visualized by pigments (Chlorophyll and Carotenoids), causing changes in plant reflectance. The goal of this study was to evaluate the performance of different Machine Learning (ML) algorithms in estimating fluorescence and foliar pigments in irrigated and rainfed peanut production fields. The experiment was conducted in the southeast of Georgia in the United States in... C. Rossi, S.L. Almeida, M.N. Sysskind, L.A. Moreno, A. Felipe dos santos, L. Lacerda, G. Vellidis, C. Pilcon, T. Orlando costa barboza

Download paper