[HTML][HTML] Advanced high-throughput plant phenotyping techniques for genome-wide association studies: A review

Q Xiao, X Bai, C Zhang, Y He - Journal of advanced research, 2022 - Elsevier
Background Linking phenotypes and genotypes to identify genetic architectures that
regulate important traits is crucial for plant breeding and the development of plant genomics …

Advanced technology in agriculture industry by implementing image annotation technique and deep learning approach: A review

N Mamat, MF Othman, R Abdoulghafor, SB Belhaouari… - Agriculture, 2022 - mdpi.com
The implementation of intelligent technology in agriculture is seriously investigated as a way
to increase agriculture production while reducing the amount of human labor. In agriculture …

Direct and accurate feature extraction from 3D point clouds of plants using RANSAC

M Ghahremani, K Williams, F Corke… - … and Electronics in …, 2021 - Elsevier
While point clouds hold promise for measuring the geometrical features of 3D objects, their
application to plants remains problematic. Plants are three dimensional (3D) organisms …

Deep segmentation of point clouds of wheat

M Ghahremani, K Williams, FMK Corke… - Frontiers in Plant …, 2021 - frontiersin.org
The 3D analysis of plants has become increasingly effective in modeling the relative
structure of organs and other traits of interest. In this paper, we introduce a novel pattern …

Machine and deep learning: Artificial intelligence application in biotic and abiotic stress management in plants

C Gou, S Zafar, N Fatima, Z Hasnain, N Aslam… - Frontiers in Bioscience …, 2024 - osti.gov
Biotic and abiotic stresses significantly affect plant fitness, resulting in a serious loss in food
production. Biotic and abiotic stresses predominantly affect metabolite biosynthesis, gene …

DeepLearnMOR: a deep-learning framework for fluorescence image-based classification of organelle morphology

J Li, J Peng, X Jiang, AC Rea, J Peng, J Hu - Plant physiology, 2021 - academic.oup.com
The proper biogenesis, morphogenesis, and dynamics of subcellular organelles are
essential to their metabolic functions. Conventional techniques for identifying, classifying …

High‐throughput measurement of plant fitness traits with an object detection method using Faster R‐CNN

P Wang, F Meng, P Donaldson, S Horan… - New …, 2022 - Wiley Online Library
Revealing the contributions of genes to plant phenotype is frequently challenging because
loss‐of‐function effects may be subtle or masked by varying degrees of genetic redundancy …

Systematic literature review: application of deep learning processing technique for fig fruit detection and counting

ASF Kamaruzaman, AIC Ani, MAHM Farid… - Bulletin of Electrical …, 2023 - beei.org
Deep learning has shown much promise in target identification in recent years, and it's
becoming more popular in agriculture, where fig fruit detection and counting have become …

ACORBA: Automated workflow to measure Arabidopsis thaliana root tip angle dynamics

NBC Serre, M Fendrych - Quantitative Plant Biology, 2022 - cambridge.org
The ability of plants to sense and orient their root growth towards gravity is studied in many
laboratories. It is known that manual analysis of image data is subjected to human bias …

[HTML][HTML] Automated flower counting from partial detections: Multiple hypothesis tracking with a connected-flower plant model

W Houtman, A Siagkris-Lekkos, DJM Bos… - … and Electronics in …, 2021 - Elsevier
This paper presents an automated flower counting method based on Multiple Hypothesis
Tracking (MHT) with a connected-flower plant model which is based on detections of …