OOIR: Observatory of International Research

Papers

(The H4-Index of Plant Methods is 31. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-05-01 to 2024-05-01.)

Article	Citations
Plant diseases and pests detection based on deep learning: a review	367
Early recognition of tomato gray leaf spot disease based on MobileNetv2-YOLOv3 model	125
Semi-supervised few-shot learning approach for plant diseases recognition	75
Analysis and comprehensive comparison of PacBio and nanopore-based RNA sequencing of the Arabidopsis transcriptome	70
A survey of few-shot learning in smart agriculture: developments, applications, and challenges	70
Leaf area index estimation model for UAV image hyperspectral data based on wavelength variable selection and machine learning methods	70
High-throughput three-dimensional visualization of root system architecture of rice using X-ray computed tomography	68
Development of support vector machine-based model and comparative analysis with artificial neural network for modeling the plant tissue culture procedures: effect of plant growth regulators on somatic	59
A hybrid model based on general regression neural network and fruit fly optimization algorithm for forecasting and optimizing paclitaxel biosynthesis in Corylus avellana cell culture	53
Wheat ear counting using K-means clustering segmentation and convolutional neural network	46
High throughput analysis of leaf chlorophyll content in sorghum using RGB, hyperspectral, and fluorescence imaging and sensor fusion	45
Remote estimation of leaf area index (LAI) with unmanned aerial vehicle (UAV) imaging for different rice cultivars throughout the entire growing season	45
Yield prediction by machine learning from UAS-based multi-sensor data fusion in soybean	44
Accurate machine learning-based germination detection, prediction and quality assessment of three grain crops	44
Machine learning for high-throughput field phenotyping and image processing provides insight into the association of above and below-ground traits in cassava (Manihot esculenta Crantz)	42
Few-shot cotton leaf spots disease classification based on metric learning	41
Screening natural product extracts for potential enzyme inhibitors: protocols, and the standardisation of the usage of blanks in α-amylase, α-glucosidase and lipase assays	39
Computer vision-based wood identification and its expansion and contribution potentials in wood science: A review	39
Early real-time detection algorithm of tomato diseases and pests in the natural environment	38
Isolation of antimicrobial peptides from different plant sources: Does a general extraction method exist?	38
Phenotypic techniques and applications in fruit trees: a review	38
Quantitative visualization of photosynthetic pigments in tea leaves based on Raman spectroscopy and calibration model transfer	37
Determination of phosphorus compounds in plant tissues: from colourimetry to advanced instrumental analytical chemistry	37
Evaluation of novel precision viticulture tool for canopy biomass estimation and missing plant detection based on 2.5D and 3D approaches using RGB images acquired by UAV platform	36
Deep learning-based detection of seedling development	36

DeepFlower: a deep learning-based approach to characterize flowering patterns of cotton plants in the field	36
Heritable gene editing using FT mobile guide RNAs and DNA viruses	35
Maize tassels detection: a benchmark of the state of the art	34
Estimation of plant height and yield based on UAV imagery in faba bean (Vicia faba L.)	34
Non-destructive estimation of field maize biomass using terrestrial lidar: an evaluation from plot level to individual leaf level	33
Method for accurate multi-growth-stage estimation of fractional vegetation cover using unmanned aerial vehicle remote sensing	33
SILEX: a fast and inexpensive high-quality DNA extraction method suitable for multiple sequencing platforms and recalcitrant plant species	31
Optimization of protoplast regeneration in the model plant Arabidopsis thaliana	31
An improved strategy to analyse strigolactones in complex sample matrices using UHPLC–MS/MS	31
CRISPR-Cas9 enrichment and long read sequencing for fine mapping in plants	31