Proceedings :: International Society of Precision Agriculture

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Mahmood, S

Payton, M.E

Miniotti, E.F

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Authors

Moss, J.Q

Bell, G.E

Solie, J.B

Stone, M.L

Martin, D.L

Payton, M.E

Cordero, E

Sacco, D

Moretti, B

Miniotti, E.F

Tenni, D

Beltarre, G

Romani, M

Grignani, C

Karampoiki, M

Todman, L

Mahmood, S

Murdoch, A

Paraforos, D

Hammond, J

Ranieri, E

Topics

Precision Horticulture

In-Season Nitrogen Management

Big Data, Data Mining and Deep Learning

Type

Poster

Oral

Year

2010

2018

2022

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Filter results3 paper(s) found.
1. Development Of A Precision Sensing Sprayer For The Application Of Nitrogen Fertilizer To Turfgrass Normalized difference vegetation index (NDVI) may be very useful for turfgrass managers to measure turf quality and obtain an indirect measurement of turf N status. The objective of this research was to develop a Nitrogen Fertilization Optimization Algorithm (NFOA) for use in a turfgrass variable rate N applicator on bermudagrass [Cynodon dactylon (L.) Pers] fairways and creeping bentgrass (Agrostis stolonifera L.) greens in Oklahoma. Plots (0.9 X 1.5 m)... J.Q. Moss, G.E. Bell, J.B. Solie, M.L. Stone, D.L. Martin, M.E. Payton Download paper
2. Deriving Fertiliser VRA Calibration Based on Ground Sensing Data from Specific Field Experiments Nitrogen (N) fertilisation affects both rice yield and quality. In order to improve grain yield while limiting N losses, providing N fertilisers during the critical growth stages is essential. NDRE is considered a reliable crop N status indicator, suitable to drive topdressing N fertilisation in rice. A multi-year experiment on different rice varieties (Gladio, Centauro, and Carnaroli) was conducted between 2011 and 2017 in Castello d’Agogna (PV), northwest Italy, with the aim of i) establishing... E. Cordero, D. Sacco, B. Moretti, E.F. Miniotti, D. Tenni, G. Beltarre, M. Romani, C. Grignani Download paper
3. A Bayesian Network Approach to Wheat Yield Prediction Using Topographic, Soil and Historical Data Bayesian Network (BN) is the most popular approach for modeling in the agricultural domain. Many successful applications have been reported for crop yield prediction, weed infestation, and crop diseases. BN uses probabilistic relationships between variables of interest and in combination with statistical techniques the data modeling has many advantages. The main advantages are that the relationships between variables can be learned using the model as well as the potential to deal with missing... M. Karampoiki, L. Todman, S. Mahmood, A. Murdoch, D. Paraforos, J. Hammond, E. Ranieri Download paper

Filter results3 paper(s) found.

1. Development Of A Precision Sensing Sprayer For The Application Of Nitrogen Fertilizer To Turfgrass

Normalized difference vegetation index (NDVI) may be very useful for turfgrass managers to measure turf quality and obtain an indirect measurement of turf N status. The objective of this research was to develop a Nitrogen Fertilization Optimization Algorithm (NFOA) for use in a turfgrass variable rate N applicator on bermudagrass [Cynodon dactylon (L.) Pers] fairways and creeping bentgrass (Agrostis stolonifera L.) greens in Oklahoma. Plots (0.9 X 1.5 m)... J.Q. Moss, G.E. Bell, J.B. Solie, M.L. Stone, D.L. Martin, M.E. Payton

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2. Deriving Fertiliser VRA Calibration Based on Ground Sensing Data from Specific Field Experiments

Nitrogen (N) fertilisation affects both rice yield and quality. In order to improve grain yield while limiting N losses, providing N fertilisers during the critical growth stages is essential. NDRE is considered a reliable crop N status indicator, suitable to drive topdressing N fertilisation in rice. A multi-year experiment on different rice varieties (Gladio, Centauro, and Carnaroli) was conducted between 2011 and 2017 in Castello d’Agogna (PV), northwest Italy, with the aim of i) establishing... E. Cordero, D. Sacco, B. Moretti, E.F. Miniotti, D. Tenni, G. Beltarre, M. Romani, C. Grignani

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3. A Bayesian Network Approach to Wheat Yield Prediction Using Topographic, Soil and Historical Data

Bayesian Network (BN) is the most popular approach for modeling in the agricultural domain. Many successful applications have been reported for crop yield prediction, weed infestation, and crop diseases. BN uses probabilistic relationships between variables of interest and in combination with statistical techniques the data modeling has many advantages. The main advantages are that the relationships between variables can be learned using the model as well as the potential to deal with missing... M. Karampoiki, L. Todman, S. Mahmood, A. Murdoch, D. Paraforos, J. Hammond, E. Ranieri

Download paper