wheat

Global Wheat Head Detection 2021: An Improved Dataset for Benchmarking Wheat Head Detection Methods

The Global Wheat Head Detection (GWHD) dataset was created in 2020 and has assembled 193,634 labelled wheat heads from 4700 RGB images acquired from various acquisition platforms and 7 countries/institutions. With an associated competition hosted in …

Understanding the Effects of Growing Seasons, Genotypes, and Their Interactions on the Anthesis Date of Wheat Sown in North China

Quantitative studies on the effects of growing season, genotype (including photoperiod genes and vernalization genes), and their interaction (GGI) on the anthesis date of winter wheat (Triticum aestivum L.) are helpful to provide a scientific …

Comparison of Modelling Strategies to Estimate Phenotypic Values from an Unmanned Aerial Vehicle with Spectral and Temporal Vegetation Indexes

Aboveground dry weight (AGDW) and leaf area index (LAI) are indicators of crop growth status and grain yield as affected by interactions of genotype, environment, and management. Unmanned aerial vehicle (UAV) based remote sensing provides …

Using a gene-based phenology model to identify optimal flowering periods of spring wheat in irrigated mega-environments

To maximise the grain yield of spring wheat, flowering needs to coincide with the optimal flowering period (OFP) by minimising frost and heat stress on reproductive development. This global study conducted a comprehensive modelling analysis of …

Genotype specific P-spline response surfaces assist interpretation of regional wheat adaptation to climate change

Yield is a function of environmental quality and the sensitivity with which genotypes react to that. Environmental quality is characterized by meteorological data, soil and agronomic management, whereas genotypic sensitivity is embodied by …

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 …

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 …

Machine Learning in Agriculture

Machine learning applied to high-throughput feature extraction from imagery to map spatial variability.

Does precipitation keep pace with temperature in the marginal double-cropping area of northern China?

Northern China is the major grain-production region in the country. To adapt to climate change and ensure food security with a fixed area of arable land, utilizing a multiple cropping frequency each year is regarded as an efficient method of …

INVITA

A technology and analytics platform for improving variety selection.

A reduced‐tillering trait shows small but important yield gains in dryland wheat production

Reducing the number of tillers per plant using a tiller inhibition (tin ) gene has been considered as an important trait for wheat production in dryland environments. We used a spatial analysis approach with a daily time‐step coupled radiation and …

Enabling breeding of spring wheat for optimisation of flowering time for current and future climates by linking genetic maps to simulation model parameters

In Australian wheat production, optimizing wheat phenology is essential to reach yield potential and to avoid within‐season stress at critical periods, especially around flowering. Identifying loci that determine heading date of wheat cultivars and …

Assessment of traits related with water productivity in the Australian wheatbelt using an improved version of the APSIM-Wheat model.

Traits related with water productivity in dryland cropping interact in multiple ways to influence final grain yield. The APSIM-Wheat model has proved useful to address how to best combine traits for region-specific and management-specific adaptation …

Establishing a value proposition for future traits in a climate-changing world.

Increasing climate variability is as great a concern as increasing air temperatures forecast with climate change. The challenge for breeders is in identifying and selecting traits that are genetically correlated with environments into the future …

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 …

Assessment of traits related with water productivity in the Australian wheatbelt using an improved version of the APSIM-Wheat model.

Traits related with water productivity in dryland cropping interact in complex ways to influence final grain yield. Over the last decades, the APSIM-Wheat model has proved useful to address how to best combine traits for region-specific and …

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 …

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 …

Improving process-based crop models to better capture genotype×environment×management interactions

In spite of the increasing expectation for process-based crop modelling to capture genotype (G) by environment (E) by management (M) interactions to support breeding selections, it remains a challenge to use current crop models to accurately predict …

Modelling impact of early vigour on wheat yield in dryland regions

Early vigour, or faster early leaf area development, has been considered an important trait for rainfed wheat in dryland regions such as Australia. However, early vigour is a genetically complex trait, and results from field experiments have been …

Genetic diversity toolkit

A genetic diversity toolkit to maximise harvest index by controlling the duration of developmental phase

National Phenology Initiative

A nationally validated model of wheat and barley flowering time that can be parameterised for new cultivars using molecular markers, genomic data and/or controlled environment phenotypic data.

Estimation of aboveground biomass and leaf area for a wheat trial index using unmanned aerial vehicle

Aboveground biomass (AGB) and leaf area index (LAI) are very important in plant breeding and precision agriculture, as major indicators of crop growth status and grain yield. However, the traditional destructive sampling method is impractical and …

PhenoCopter: An cloud based solution for image processing captured by unmanned aerial vehicle in 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 …

Projected impact of future climate on water-stress patterns across the Australian wheatbelt

Drought frequently limits Australian wheat production, and the expected future increase in temperatures and rainfall variability will further challenge productivity. A modelling approach captured plant×environment×management interactions to simulate …

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 …

Assessment of canopy growth and development for three wheat cultivars under different water and nitrogen regimes

Traits related to water productivity in dryland cropping interact in multiple ways to influence final grain yield. Crop modelling can be a useful tool to address the challenge of determining how to best combine region-specific traits and develop …

Improving the relationships used to define frost damage to wheat in crop models

In order to predict the consequences and value of frost adaptation through breeding and agronomy across Australia’s cropping region it is essential that a validated frost damage function is incorporated into our crop models. This paper reports on …

Economic assessment of wheat breeding options for potential improved levels of post head-emergence frost tolerance

Frost, during reproductive developmental stages, especially post head emergence frost (PHEF), can result in catastrophic yield loss for wheat producers. Breeding for improved PHEF tolerance may allow greater yield to be achieved, by (i) reducing …

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 …

Drought in wheat – Past and future trends

Understanding how climate is varying and is likely affecting crop productivity in the coming decades is essential for global food security. Climate change studies predict an increase in temperature and more rainfall variability in future decades, …

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 …

Dynamic monitoring of canopy structure by time serial photography of early stage growth of wheat

Early vigour is an important physiological trait to improve establishment, water-use efficiency and grain yield for wheat. Phenotyping large numbers of genotypes is challenging due to the fast growth and development of wheat seedlings. Several …

Identification of Earliness Per Se Flowering Time Locus in Spring Wheat through a Genome-Wide Association Study

Identification of earliness per se (Eps) flowering time loci in spring wheat are troublesome due to confounding effects of vernalization and photoperiod responses. The Wheat Association Mapping Initiative panel of 287 elite lines was assessed to …

Improvement of the model capacity and assessment traits related with water use efficiency for wheat in Australia

Traits related with water productivity in dryland cropping interact in multiple ways to influence final grain yield, with traits being of different value across environments. In recent years, crop models have been demonstrated as a useful tool to …

Recent changes in southern Australian frost occurrence: implications for wheat production risk

Frost damage remains a major problem for broadacre cropping, viticulture, horticulture and other agricultural industries in Australia. Annual losses from frost events in Australian broadacre agriculture are estimated at between $120 million and $700 …

Dynamic quantification of canopy structure to characterize early plant vigour in wheat genotypes

Early vigour is an important physiological trait to improve establishment, water-use efficiency, and grain yield for wheat. Phenotyping large numbers of lines is challenging due to the fast growth and development of wheat seedlings. Here we developed …

Do wheat breeders have suitable genetic variation to overcome short coleoptiles and poor establishment in the warmer soils of future climates?

Increases in air and soil temperatures will impact cereal growth and reduce crop yields. Little is known about how increasing temperatures will impact seedling growth and crop establishment. Climate forecast models predict that by 2060, mean and …

Assessment of the Potential Impacts of Wheat Plant Traits across Environments by Combining Crop Modeling and Global Sensitivity Analysis

A crop can be viewed as a complex system with outputs (e.g. yield) that are affected by inputs of genetic, physiology, pedo-climatic and management information. Application of numerical methods for model exploration assist in evaluating the major …

Velocity of temperature and flowering time in wheat – assisting breeders to keep pace with climate change

By accelerating crop development, warming climates may result in mismatches between key sensitive growth stages and extreme climate events, with severe consequences for crop yield and food security. Using recent estimates of gene responses to …

Breeding for the future: How to adapt to frost, drought and heat impacts in Australian wheat

While extreme climatic events (frost, heat and drought) can already severely limit wheat production, the expected future increase in extreme temperatures and rainfall variability will further challenge improvement in crop productivity. In addition, …

Projected impacts of climate change on drought stresses in Australian wheat

Wheat is one of the primary staple foods. Due to a rising population and improved living standards, demand for this crop continues to increase. Much of the wheat produced in Australia is grown in water-limited environments. Climate models project …

Quantification of direct and indirect cost of frost for the Australian wheatbelt

A single post head-emergence frosts (PHEF) event has the potential to devastate individual wheat crops by damaging stems and killing whole heads. Wheat crops are most sensitive after head emergence and hence management of crop phenology to avoid PHEF …

The shifting influence of drought and heat stress for crops in Northeast Australia

Characterization of drought environment types (ETs) has proven useful for breeding crops for drought-prone regions. Here, we consider how changes in climate and atmospheric carbon dioxide (CO2) concentrations will affect drought ET frequencies in …

Crop modelling to aid crop improvement

Substantial genotype x environment interactions impede breeding progress for yield. Identifying genetic controls associated with yield response is confounded by poor genetic correlations across testing environments. Part of this problem is related to …

Gene-based prediction of heading time to target real-time and future climate adaptation in wheat

Spring wheat production systems in Australia require fine-tuning of heading time in order to maximise the efficient use of resources (radiation, water, fertiliser) across the season, while minimising the risk of crop failure due to frost, heat and …

Predicting heading date and frost impact in wheat across Australia

Spring radiant frosts occurring when wheat is in reproductive developmental stages can result in catastrophic yield lost for producers. In wheat, heading time is the main determinant to minimize frost risks and to adapt new frost-tolerant cultivars …