UAV

Coupling of machine learning methods to improve estimation of ground coverage from unmanned aerial vehicle (UAV) imagery for high-throughput phenotyping of crops

Ground coverage (GC) allows monitoring of crop growth and development and is normally estimated as the ratio of vegetation to the total pixels from nadir images captured by visible-spectrum (RGB) cameras. The accuracy of estimated GC can be …

Integrating Crop Growth Models with Remote Sensing for Predicting Biomass Yield of Sorghum

Plant phenotypes are often descriptive, rather than predictive of crop performance. As a result, extensive testing is required in plant breeding programs to develop varieties aimed at performance in the target environments. Crop models can improve …

ModelingGlobal Wheat Head Detection (GWHD) Dataset: A Large and Diverse Dataset of High-Resolution RGB-Labelled Images to Develop and Benchmark Wheat Head Detection Methods

The detection of wheat heads in plant images is an important task for estimating pertinent wheat traits including head population density and head characteristics such as health, size, maturity stage, and the presence of awns. Several studies have …

Extraction of phenotypic traits using unmanned aerial vehicle for field experiments in the agronomy and crop breeding

With advances in camera and robotic technologies, unmanned aerial vehicles (UAV) provide the means to capture images at sufficiently large scale to extract crop phenotypic traits. The current challenges are to efficiently manage the meta information …

Estimation of plot variability using unmanned aerial vehicle (UAV) for the wheat breeding trials

Gaps in breeders’ plots (spatial variability) are caused by multiple biotic and abiotic stresses (i.e. poor seed gemination, frost, heat, drought, and/or disease). The gaps are either ignored or visually scored by human inspection. However, this …

A Weakly Supervised Deep Learning Framework for Sorghum Head Detection and Counting

The yield of cereal crops such as sorghum (Sorghum bicolor L. Moench) depends on the distribution of crop-heads in varying branching arrangements. Therefore, counting the head number per unit area is critical for plant breeders to correlate with the …

Pixel size of aerial imagery constrains the applications of unmanned aerial vehicle in crop breeding

Image analysis using proximal sensors can help accelerate the selection process in plant breeding and improve the breeding efficiency. However, the accuracies of extracted phenotypic traits, especially those that require image classification, are …

Accuracy assessment of plant height using an unmanned aerial vehicle for quantitative genomic analysis in bread wheat

Background: Plant height is an important selection target since it is associated with yield potential, stability and particularly with lodging resistance in various environments. Rapid and cost-effective estimation of plant height from airborne …

Characterization of peach tree crown by using high-resolution images from an unmanned aerial vehicle

In orchards, measuring crown characteristics is essential for monitoring the dynamics of tree growth and optimizing farm management. However, it lacks a rapid and reliable method of extracting the features of trees with an irregular crown shape such …

Estimation of plant height using a high throughput phenotyping platform based on unmanned aerial vehicle and self-calibration: Example for sorghum breeding

Plant height is an essential trait to evaluate in grain sorghum, being positively associated with potential grain yield. Standard manual measures of plant height for large breeding trials are labour-intensive and time-consuming. Due to potential …

McGET: A rapid image-based method to determine the morphological characteristics of gravels on the Gobi desert surface

The relationship between morphological characteristics (e.g. gravel size, coverage, angularity and orientation) and local geomorphic features (e.g. slope gradient and aspect) of desert has been used to explore the evolution process of Gobi desert. …

Phenotyping with light interception

Quantification and evaluation of the phenotyping parameters and light interception function of the crop canopy based on rotor unmanned aerial vehicle (UAV) platform

PhenoCopter: An cloud based platform to manage, process and visualize images captured by unmanned aerial vehicle for high throughput phenotyping

As the advances of technologies, unmanned aerial vehicles (UAV) are more convenient to capture images in large scale to extract crop phenotypes. However, the key challenge is how to efficiently manage all meta information, process huge amount of …

The big impacts of image resolution on the estimation of ground coverage for wheat in UAV survey

Ground coverage (GC) is a simple and important trait to monitor crop growth and development, which can be easily captured by visual camera attached on the ground and aerial based platform. However, the accuracy of GC is determined by pixel size …

Estimation of canopy height using an unmanned aerial vehicle in the field during wheat growth season

Canopy height is a simple trait to represent status of plant growth and development and potentially biomass production, as well as having an influence on lodging susceptibility. Measurement is labour-intensive and time consuming, especially in the …

Dynamic monitoring of NDVI in wheat agronomy and breeding trials using an unmanned aerial vehicle

While new technologies can capture high-resolution normalized difference vegetation index (NDVI), a surrogate for biomass and leaf greenness, it is a challenge to efficiently apply this technology in a large breeding program. Here we validate a …

EasyPCC: Benchmark Datasets and Tools for High-Throughput Measurement of the Plant Canopy Coverage Ratio under Field Conditions

Understanding interactions of genotype, environment, and management under field conditions is vital for selecting new cultivars and farming systems. Image analysis is considered a robust technique in high-throughput phenotyping with non-destructive …

Comparison of ground cover estimates from experiment plots in cotton, sorghum and sugarcane based on images and ortho-mosaics captured by UAV

Ground cover is an important physiological trait affecting crop radiation capture, water-use efficiency and grain yield. It is challenging to efficiently measure ground cover with reasonable precision for large numbers of plots, especially in tall …

Pheno-Copter: a low-altitude, autonomous remote-sensing robotic helicopter for high-throughput field-based phenotyping

Plant breeding trials are extensive (100s to 1000s of plots) and are difficult and expensive to monitor by conventional means, especially where measurements are time-sensitive. For example, in a land-based measure of canopy temperature (hand-held …

A field-based high-throughput method for acquiring canopy architecture using unmanned aerial vehicle images

Plant architectural traits are important selection criteria in plant breeding that relate to photosynthetic efficiency and crop productivity. Conventional manual measures of architectural traits for large breeding trials are labour- and …