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Sozzi, M

Lati, R

Amouzouvi, K.M

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Authors

Herrmann, I

Sadeh, R

Avneri, A

Tubul, Y

Lati, R

Abbo, S

Bonfil, D.J

Peleg, Z

Amouzouvi, K.M

Ozou, K.E

Kolani, L

Amouzouvi, K.A

Sogbedji, J.M

Kayad, A

Sozzi, M

Pirotti, F

Marinello, F

Sartori, L

Gatto, S

Topics

Proximal and Remote Sensing

Precision Agriculture for Field and Plantation Crops

Satellite Imagery

Type

Oral

Year

2020

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Filter results3 paper(s) found.
1. Spectral assessment of chickpea morpho-physiological traits from space, air and ground Chickpea (Cicer arietinum) is an important grain legume in semi-arid regions and water-stress is a major constraint to its productivity. Area under chickpea cultivation is growing but climate change toward greater aridity results in higher precipitation instability and risks yields. The ability to assess water potential can support irrigation decisions. Thus, improved ability to spatially assess plants water status can promote more efficient irrigation. The current... I. Herrmann, R. Sadeh, A. Avneri, Y. Tubul, R. Lati, S. Abbo, D.J. Bonfil, Z. Peleg
2. Performance agronomique et économique de différentes stratégies de gestion de la fertilité du sol sous culture de soja (Glycine max L. Merril) dans la zone littorale du Togo. Ce travail a pour objectif de valoriser les émondes de deux légumineuses arbustives et quelques fertilisants organiques pour améliorer la production du soja. Afin de parvenir à cet objectif, les paramètres comme la masse de mille graines, les rendements en gousses, en graines, en fanes du soja et autres ont été déterminés. L’étude a eu lieu à la Station d’Expérimentation Agronomique de Lomé (SEAL)... K.M. Amouzouvi, K.E. Ozou, L. Kolani, K.A. Amouzouvi, J.M. Sogbedji
3. Monitoring Corn (Zea mays) Yield using Sentinel-2 and Machine Learning for Precision Agriculture Applications Currently, there is a growing demand to apply precision agriculture (PA) management practices at agricultural fields expecting more efficient and more profitable management. One of PA principal components for site-specific management is crop yield monitoring which varies temporally between seasons and spatially within-field. In this study, we investigated the possibility of monitoring within-field variability of corn grain yield in a 22ha field located in Ferarra, North Italy. Archived yield data... A. Kayad, M. Sozzi, F. Pirotti, F. Marinello, L. Sartori, S. Gatto Download paper

Filter results3 paper(s) found.

1. Spectral assessment of chickpea morpho-physiological traits from space, air and ground

Chickpea (Cicer arietinum) is an important grain legume in semi-arid regions and water-stress is a major constraint to its productivity. Area under chickpea cultivation is growing but climate change toward greater aridity results in higher precipitation instability and risks yields. The ability to assess water potential can support irrigation decisions. Thus, improved ability to spatially assess plants water status can promote more efficient irrigation. The current... I. Herrmann, R. Sadeh, A. Avneri, Y. Tubul, R. Lati, S. Abbo, D.J. Bonfil, Z. Peleg

2. Performance agronomique et économique de différentes stratégies de gestion de la fertilité du sol sous culture de soja (Glycine max L. Merril) dans la zone littorale du Togo.

Ce travail a pour objectif de valoriser les émondes de deux légumineuses arbustives et quelques fertilisants organiques pour améliorer la production du soja. Afin de parvenir à cet objectif, les paramètres comme la masse de mille graines, les rendements en gousses, en graines, en fanes du soja et autres ont été déterminés. L’étude a eu lieu à la Station d’Expérimentation Agronomique de Lomé (SEAL)... K.M. Amouzouvi, K.E. Ozou, L. Kolani, K.A. Amouzouvi, J.M. Sogbedji

3. Monitoring Corn (Zea mays) Yield using Sentinel-2 and Machine Learning for Precision Agriculture Applications

Currently, there is a growing demand to apply precision agriculture (PA) management practices at agricultural fields expecting more efficient and more profitable management. One of PA principal components for site-specific management is crop yield monitoring which varies temporally between seasons and spatially within-field. In this study, we investigated the possibility of monitoring within-field variability of corn grain yield in a 22ha field located in Ferarra, North Italy. Archived yield data... A. Kayad, M. Sozzi, F. Pirotti, F. Marinello, L. Sartori, S. Gatto

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