Baltasar Garcia
@baltasargarcia.bsky.social
Post-doctoral researcher at Unesp- Brazil. Aquaculture genetics/genomics and breeding.
A very cool study developed in the Center of Aquaculture of UNESP (Caunesp) and The Brazilian Agricultural Research Corporation (Embrapa) in collaboration with U-Wisconsin
#Aquaculture #Genetics #DeepLearning
#Aquaculture #Genetics #DeepLearning
December 3, 2024 at 1:26 PM
A very cool study developed in the Center of Aquaculture of UNESP (Caunesp) and The Brazilian Agricultural Research Corporation (Embrapa) in collaboration with U-Wisconsin
#Aquaculture #Genetics #DeepLearning
#Aquaculture #Genetics #DeepLearning
🧬 Estimated heritability for color traits are moderate and low correlated to growth traits suggesting selection for countershading can improve stress resilience without impacting growth!
This study opens doors for breeding stress-resilient, visually appealing tambaqui! 🐟💡🧶
This study opens doors for breeding stress-resilient, visually appealing tambaqui! 🐟💡🧶
December 3, 2024 at 1:26 PM
🧬 Estimated heritability for color traits are moderate and low correlated to growth traits suggesting selection for countershading can improve stress resilience without impacting growth!
This study opens doors for breeding stress-resilient, visually appealing tambaqui! 🐟💡🧶
This study opens doors for breeding stress-resilient, visually appealing tambaqui! 🐟💡🧶
Highlights:
🔬 Development of a computer vision system using DeepLab V3 for automated detection of countershading intensity.
📸 Trained with 3,780 images, achieving 88.2% accuracy in large-scale phenotyping🧶
🔬 Development of a computer vision system using DeepLab V3 for automated detection of countershading intensity.
📸 Trained with 3,780 images, achieving 88.2% accuracy in large-scale phenotyping🧶
December 3, 2024 at 1:26 PM
Highlights:
🔬 Development of a computer vision system using DeepLab V3 for automated detection of countershading intensity.
📸 Trained with 3,780 images, achieving 88.2% accuracy in large-scale phenotyping🧶
🔬 Development of a computer vision system using DeepLab V3 for automated detection of countershading intensity.
📸 Trained with 3,780 images, achieving 88.2% accuracy in large-scale phenotyping🧶