Proceedings :: International Society of Precision Agriculture

Proceedings

Find matching any: Reset

Bao, Y

Bettiol, G.M

Biradar, D.P

» Add more authors

Add filter to result:

Authors

Bettiol, G.M

Inamasu, R.Y

Rabello, L.M

Bernardi, A.C

Campana, M

Oliveira, P.P

Reddy, S

Biradar, D.P

Patil, V.C

Desai, B.L

Nargund, V.B

Patil, P

Desai, V

Tulasigeri, V

Channangi, S.M

John, W

Freire de Oliveira, M.F

Ortiz, B.V

Souza, J.B

Bao, Y

Hanyabui, E

Topics

Precision Dairy and Livestock Management

Applications of Unmanned Aerial Systems

Artificial Intelligence (AI) in Agriculture

Type

Poster

Oral

Year

2012

2018

2024

Home » Authors » Results

Authors

Filter results3 paper(s) found.
1. Spatial Variability of Soil Properties in Intensively Managed Tropical Grassland in Brazil For the intensification of tropical grass pastures systems the soil fertility building up by liming and balanced fertilization is necessary. The knowledge of spatial variability soil properties is useful in the rational use of inputs, as in the variable rate application of lime and fertilizers. PA requires methods to indicate the spatial variability of soil and plant parameters. The objective of this work was to map and evaluate the soil properties and maps the site specific liming and fertilizer... G.M. Bettiol, R.Y. Inamasu, L.M. Rabello, A.C. Bernardi, M. Campana, P.P. Oliveira Download paper
2. Prototype Unmanned Aerial Sprayer for Plant Protection in Agricultural and Horticultural Crops Aerial application of pesticides has the potential to reduce the amount of pesticides required as chemicals are applied where needed. A prototype Unmanned Aerial Sprayer with a payload of 20 kg; a spraying rate of 6 liters per minute; a spraying swathe of 3 meters, coverage rate of 2 to 4 meters per second and 10 minutes of flight time was built using state of the art technologies. The project is a joint development by University of Agricultural Sciences, Dharwad, KLE Technological University,... S. Reddy, D.P. Biradar, V.C. Patil, B.L. Desai, V.B. Nargund, P. Patil, V. Desai, V. Tulasigeri, S.M. Channangi, W. John Download paper
3. Towards a Digital Peanut Profile Board: a Deep Learning Approach Artificial intelligence techniques, particularly deep learning, offer promising avenues for revolutionizing object detection and counting algorithms in the context of digital agriculture. The challenges faced by peanut farmers, particularly the precise determination of optimal maturity for digging, have prompted innovative solutions. Traditionally, peanut maturity assessment has relied on the Peanut Maturity Index (PMI), employing a manual classification process with the aid of a peanut profile... M.F. Freire de oliveira, B.V. Ortiz, J.B. Souza, Y. Bao, E. Hanyabui Download paper

Filter results3 paper(s) found.

1. Spatial Variability of Soil Properties in Intensively Managed Tropical Grassland in Brazil

For the intensification of tropical grass pastures systems the soil fertility building up by liming and balanced fertilization is necessary. The knowledge of spatial variability soil properties is useful in the rational use of inputs, as in the variable rate application of lime and fertilizers. PA requires methods to indicate the spatial variability of soil and plant parameters. The objective of this work was to map and evaluate the soil properties and maps the site specific liming and fertilizer... G.M. Bettiol, R.Y. Inamasu, L.M. Rabello, A.C. Bernardi, M. Campana, P.P. Oliveira

Download paper

2. Prototype Unmanned Aerial Sprayer for Plant Protection in Agricultural and Horticultural Crops

Aerial application of pesticides has the potential to reduce the amount of pesticides required as chemicals are applied where needed. A prototype Unmanned Aerial Sprayer with a payload of 20 kg; a spraying rate of 6 liters per minute; a spraying swathe of 3 meters, coverage rate of 2 to 4 meters per second and 10 minutes of flight time was built using state of the art technologies. The project is a joint development by University of Agricultural Sciences, Dharwad, KLE Technological University,... S. Reddy, D.P. Biradar, V.C. Patil, B.L. Desai, V.B. Nargund, P. Patil, V. Desai, V. Tulasigeri, S.M. Channangi, W. John

Download paper

3. Towards a Digital Peanut Profile Board: a Deep Learning Approach

Artificial intelligence techniques, particularly deep learning, offer promising avenues for revolutionizing object detection and counting algorithms in the context of digital agriculture. The challenges faced by peanut farmers, particularly the precise determination of optimal maturity for digging, have prompted innovative solutions. Traditionally, peanut maturity assessment has relied on the Peanut Maturity Index (PMI), employing a manual classification process with the aid of a peanut profile... M.F. Freire de oliveira, B.V. Ortiz, J.B. Souza, Y. Bao, E. Hanyabui

Download paper