Assessment of the potential impacts of plant traits across environments by combining global sensitivity analysis and dynamic modeling in wheat

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 most influential inputs, providing the simulation model is a credible description of the biological system. A sensitivity analysis was used to assess the simulated impact on yield of a suite of traits involved in major processes of crop growth and development, and to evaluate how the simulated value of such traits varies across environments and in relation to other traits (which can be interpreted as a virtual change in genetic background). The study focused on wheat in Australia, with an emphasis on adaptation to low rainfall conditions. A large set of traits (90) was evaluated in a wide target population of environments (4 sites x 125 years), management practices (3 sowing dates x 2 N fertilization) and $CO_2$ (2 levels). The Morris sensitivity analysis method was used to sample the parameter space and reduce computational requirements, while maintaining a realistic representation of the targeted trait x environment x management landscape ($\sim$ 82 million individual simulations in total). The patterns of parameter x environment x management interactions were investigated for the most influential parameters, considering a potential genetic range of +/- 20% compared to a reference. Main (i.e. linear) and interaction (i.e. non-linear and interaction) sensitivity indices calculated for most of APSIM-Wheat parameters allowed the identifcation of 42 parameters substantially impacting yield in most target environments. Among these, a subset of parameters related to phenology, resource acquisition, resource use efficiency and biomass allocation were identified as potential candidates for crop (and model) improvement.Comment: 22 pages, 8 figures. This work has been submitted to PLoS On

Impact of genotypic variations in transpiration rate on Australian wheat productivity

Crop water productivity has been receiving special attention in regards to productivity and food security. Limited-transpiration rate (LTR) at high vapour pressure deficit (VPD) has potential to improve drought adaptation. The quantification of the impact of LTR on water consumption, biomass accumulation and yield formation requires the use of dynamic crop modelling to simulate physiological and environmental processes at a suitable time scale and across environments. Here, a new module for the new generation of Agricultural Production Systems sIMulator (APSIM-NextGen) was developed and evaluated, which enables the simulation of atmospheric (VPD) and edaphic water effects on transpiration, biomass production and yield. The module was used to assess the potential of the LTR trait at improving transpiration efficiency at 60 sites across the Australian wheatbelt. Results showed that selection for the LTR trait could result in a 2.5% increase in grain yield nationally through significantly higher transpiration efficiency. Greatest productivity gains were found in eastern part of the wheatbelt where crops rely heavily on stored soil moisture and saving water mid-day (i.e. under high VPD) allows crops to consume it at more critical stages later during the crop cycle

Frost trends and their estimated impact on yield in the Australian wheatbelt

Radiant spring frosts occurring during reproductive developmental stages can result in catastrophic yield loss for wheat producers. To better understand the spatial and temporal variability of frost, the occurrence and impact of frost events on rain-fed wheat production was estimated across the Australian wheatbelt for 1957–2013 using a 0.05 ° gridded weather data set. Simulated yield outcomes at 60 key locations were compared with those for virtual genotypes with different levels of frost tolerance. Over the last six decades, more frost events, later last frost day, and a significant increase in frost impact on yield were found in certain regions of the Australian wheatbelt, in particular in the South-East and West. Increasing trends in frost-related yield losses were simulated in regions where no significant trend of frost occurrence was observed, due to higher mean temperatures accelerating crop development and causing sensitive post-heading stages to occur earlier, during the frost risk period. Simulations indicated that with frost-tolerant lines the mean national yield could be improved by up to 20 through (i) reduced frost damage (~10 improvement) and (ii) the ability to use earlier sowing dates (adding a further 10 improvement). In the simulations, genotypes with an improved frost tolerance to temperatures 1 °C lower than the current 0 °C reference provided substantial benefit in most cropping regions, while greater tolerance (to 3 °C lower temperatures) brought further benefits in the East. The results indicate that breeding for improved reproductive frost tolerance should remain a priority for the Australian wheat industry, despite warming climates

Detecting Sorghum Plant and Head Features from Multispectral UAV Imagery

In plant breeding, unmanned aerial vehicles (UAVs) carrying multispectral cameras have demonstrated increasing utility for high-throughput phenotyping (HTP) to aid the interpretation of genotype and environment effects on morphological, biochemical, and physiological traits. A key constraint remains the reduced resolution and quality extracted from “stitched” mosaics generated from UAV missions across large areas. This can be addressed by generating high-quality reflectance data from a single nadir image per plot. In this study, a pipeline was developed to derive reflectance data from raw multispectral UAV images that preserve the original high spatial and spectral resolutions and to use these for phenotyping applications. Sequential steps involved (i) imagery calibration, (ii) spectral band alignment, (iii) backward calculation, (iv) plot segmentation, and (v) application. Each step was designed and optimised to estimate the number of plants and count sorghum heads within each breeding plot. Using a derived nadir image of each plot, the coefficients of determination were 0.90 and 0.86 for estimates of the number of sorghum plants and heads, respectively. Furthermore, the reflectance information acquired from the different spectral bands showed appreciably high discriminative ability for sorghum head colours (i.e., red and white). Deployment of this pipeline allowed accurate segmentation of crop organs at the canopy level across many diverse field plots with minimal training needed from machine learning approaches

Ανάπτυξη Web εφαρμογής για συσχέτιση γονιδίων

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 direct frost damage and (ii) facilitating earlier crop sowing to reduce the risk of late season drought and/or heat stress. This paper provides an economic feasibility analysis of breeding options for PHEF tolerant wheat varieties. It compares the economic benefit to growers with the cost of a wheat breeding program aimed at developing PHEF tolerant varieties. The APSIM wheat model, with a frost-impact and a phenology gene-based module, was employed to simulate direct and indirect yield benefits for various levels of improved frost tolerance. The economic model considers optimal profit, based on sowing date and nitrogen use, rather than achieving maximum yield. The total estimated fixed cost of breeding program was AUD 1293 million, including large scale seed production to meet seed demand, with AUD 1.2 million year(-1) to run breeding program after advanced development and large scale field experiments. The results reveal that PHEF tolerant varieties would lead to a significant increase in economic benefits through reduction in direct damage and an increase in yield through early sowing. The economic benefits to growers of up to AUD 4841 million could be realised from growing PHEF tolerant lines if useful genetic variation can be found. Sensitivity analyses indicated that the benefits are particularly sensitive to increases in fixed costs, seed replacement, discount rate, and to delays in variety release. However, the investment still remains viable for most tested scenarios. Based on comparative economic benefits, if breeders were able to develop PHEF tolerant varieties that could withstand cold temperatures -4 degrees C below the current damage threshold, there is very little further economic value of breeding total frost tolerant varieties

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 direct frost damage and (ii) facilitating earlier crop sowing to reduce the risk of late-season drought and/or heat stress. This paper provides an economic feasibility analysis of breeding options for PHEF tolerant wheat varieties. It compares the economic benefit to growers with the cost of a wheat breeding program aimed at developing PHEF tolerant varieties. The APSIM wheat model, with a frost-impact and a phenology gene-based module, was employed to simulate direct and indirect yield benefits for various levels of improved frost tolerance. The economic model considers optimal profit, based on sowing date and nitrogen use, rather than achieving maximum yield. The total estimated fixed cost of breeding program was AUD 1293 million, including large scale seed production to meet seed demand, with AUD 1.2 million year−1 to run breeding program after advanced development and large scale field experiments. The results reveal that PHEF tolerant varieties would lead to a significant increase in economic benefits through reduction in direct damage and an increase in yield through early sowing. The economic benefits to growers of up to AUD 4841 million could be realised from growing PHEF tolerant lines if useful genetic variation can be found. Sensitivity analyses indicated that the benefits are particularly sensitive to increases in fixed costs, seed replacement, discount rate, and to delays in variety release. However, the investment still remains viable for most tested scenarios. Based on comparative economic benefits, if breeders were able to develop PHEF tolerant varieties that could withstand cold temperatures −4 °C below the current damage threshold, there is very little further economic value of breeding total frost tolerant varieties

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 Kaggle, GWHD_2020 has successfully attracted attention from both the computer vision and agricultural science communities. From this first experience, a few avenues for improvements have been identified regarding data size, head diversity, and label reliability. To address these issues, the 2020 dataset has been reexamined, relabeled, and complemented by adding 1722 images from 5 additional countries, allowing for 81,553 additional wheat heads. We now release in 2021 a new version of the Global Wheat Head Detection dataset, which is bigger, more diverse, and less noisy than the GWHD_2020 version

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 reference for selecting or developing adaptive varieties in target environments. In this study, we collected 100 winter wheat varieties with ecological adaptability in North China and identified the anthesis date under field conditions for three consecutive years from 2016 to 2019 with mapped photoperiod and vernalization alleles. Our results showed that the number of the photoperiod-insensitive Ppd-D1a allele increased with variety replacement, while the haplotype Ppd-A1b + Ppd-D1b + vrn-D1 (A4B2) decreased from the 1940s to 2000s. The anthesis date of A4B2 was significantly delayed due to the photoperiod-insensitive alleles Ppd-A1b and Ppd-D1b. The additive main effect and multiplicative interaction (AMMI) model and GGI biplot analysis were used for data analysis. A large portion of the total variation was explained by growing seasons (66.3%), while genotypes and GGIs explained 21.9% and 10.1% of the anthesis dates, respectively. The varieties from the 1940s and before had a great influence on the anthesis date, suggesting these germplasms tend to avoid premature anthesis and could facilitate the development of phenological resilient varieties

Improving Grain Yield via Promotion of Kernel Weight in High Yielding Winter Wheat Genotypes

Improving plant net photosynthetic rates and accelerating water-soluble carbohydrate accumulation play an important role in increasing the carbon sources for yield formation of wheat (Triticum aestivum L.). Understanding and quantify the contribution of these traits to grain yield can provide a pathway towards increasing the yield potential of wheat. The objective of this study was to identify kernel weight gap for improving grain yield in 15 winter wheat genotypes grown in Shandong Province, China. A cluster analysis was conducted to classify the 15 wheat genotypes into high yielding (HY) and low yielding (LY) groups based on their performance in grain yield, harvest index, photosynthetic rate, kernels per square meter, and spikes per square meter from two years of field testing. While the grain yield was significantly higher in the HY group, its thousand kernel weight (TKW) was 8.8% lower than that of the LY group (p < 0.05). A structural equation model revealed that 83% of the total variation in grain yield for the HY group could be mainly explained by TKW, the flag leaf photosynthesis rate at the grain filling stage (Pn75), and flag leaf water-soluble carbohydrate content (WSC) at grain filling stage. Their effect values on yield were 0.579, 0.759, and 0.444, respectively. Our results suggest that increase of flag leaf photosynthesis and WSC could improve the TKW, and thus benefit for developing high yielding wheat cultivars