Agriculture and Food Systems - Theses

Permanent URI for this collection

Search Results

Now showing 1 - 3 of 3
  • Item
    Thumbnail Image
    Increasing lentil (Lens culinaris) adaptation to acute high temperature for arable cropping
    Delahunty, Audrey Jane ( 2021)
    Lentil (Lens culinaris Medik.) is an important crop for providing a source of dietary protein globally and is produced over three distinct agroecological zones; Mediterranean, sub-tropical and temperate. Crop production is constrained by abiotic and biotic stresses, including acute high temperature (HT). For Mediterranean-type climates, such as southern Australia, low and unreliable winter rainfall (200 – 600 mm/year) and frequent acute HT events (heat waves) during the reproductive phase, limit production with yield losses up to 70%. Consequently, increasing the adaptation of commercial lentil varieties within contemporary breeding programs, by utilising global germplasm adapted to HT environments, is the critical next step. This project screened 135 lentil genotypes (global landraces and commercial cultivars) for tolerance to acute HT occurring during the reproductive period. Screening was through a combination of late sowing (summer - chronic and acute HT), controlled-environment (acute HT) and subsequent in-season validation (winter - acute HT), where a daily maximum temperature of greater than 30 degrees Celsius was classified as HT tolerant. Genotypes selected for screening were predominately from regions where HT occurs during the reproductive period (i.e. Mediterranean and sub-tropical). Across HT treatments ranging from acute (3 days) to chronic HT during the reproductive period, we observed that HT caused a 48% reduction in grain yield across genotypes screened, which translated to an average reduction of 0.14 and 0.19% per degree (>30 degrees Celsius) for global landraces and commercial cultivars respectively. We identified 15 landraces and the commercial cultivar, Nipper to have a high level of yield stability under HT. Within the 15 landraces identified, AGG 73838 and 73154 consistently exhibited HT tolerance under the multiple screening strategies employed in this study. The additional 13 landraces were identified within the late sowing field screening process. The identification of these 15 HT tolerant landraces provides a valuable source of material that can be immediately utilised by Australian lentil breeding programs. Optimal screening approaches for HT tolerance were also identified in this study, where field-based and controlled environment screening methods were tested and their utility to breeding programs, assessed. To align with current breeding strategies, several requirements were considered important; 1) reliable methods for identifying genetic diversity to HT response within global material, 2) high-throughput potential and (or) ability to measure parameters efficiently, and 3) methods to enable screening of large populations. Through assessing a range of screening methodologies, we determined that a multi-stage screening process integrating late sowing over spring/summer with subsequent winter validation, is required. This process enables the shortlisting of HT tolerant germplasm from a broad range of material and further validation of phenotype response in field conditions. To rank genotypes based on HT tolerance we determined that the indices, stress tolerant index (STI) and high temperature tolerance index (HTTI), which integrate the absolute and relative response of genotypes within the test population, were an effective means of ranking HT tolerance. The final component of this project assessed the combined effects of available soil water, night-time temperature and carbon dioxide concentration on HT response in lentil, which provided insight to the impact of other abiotic constraints associated with climate change. We determined that for HT, lentil response varied with available soil water and soil type. For lentil grown in a sandy loam soil, when HT and high water occurred together, HT caused a significant reduction in yield (33%), whereas under low water the application of HT did not further reduce yield. In contrast, for a clay soil there was a significant reduction in yield due to HT across both high and low water treatments. This highlights the effect of soil type on crop water availability and the potential variable response to acute HT depending on soil type and rainfall patterns of a growing region. For the impact of high night temperature, we observed no effect of night temperature when it occurs in conjunction with high day temperature. For the collective effect of HT and carbon dioxide concentration, elevated carbon dioxide did not alter the pattern of plant response to acute HT. This suggests that for lentil, the effects of HT are unlikely to be exacerbated or reduced under elevated carbon dioxide levels. Ultimately, this project contributes to the Australian lentil industry by identifying landraces with HT tolerance and through the development of a screening methodology that can be adopted by current breeding programs to increase the HT tolerance of future commercial lentil cultivars.
  • Item
    Thumbnail Image
    Advancing Genomics Resources and Phenotyping Methods to Improve Salt Tolerance in Lentil
    Dissanayake Ralalage, Ruwani Prasangika Dissanayake ( 2021)
    Pulses, also known as grain legumes, are members of the family Leguminosae and are grown for their edible seeds, containing high amounts of proteins and fibre. The work performed in this thesis is focused on lentil (Lens sp.), which is a self-pollinating, diploid, cool-season grain legume. Lentil production is constrained by multiple biotic and abiotic stresses that reduce growth and grain yield. The development of lentil varieties/cultivars with improved characteristics, including better yield, adaptation, and resistance to biotic and abiotic stresses, is a priority for international breeding programs. Therefore, the thesis investigated advanced genomic and phenomic approaches to characterize lentil germplasm for breeding purposes. Cultivated lentil (Lens culinaris Medik.) has a relatively narrow genetic base. Therefore, characterization of genetic diversity and genomic differentiation of wild gene pools is essential to identify any favorable alleles/genes that can be introduced into elite germplasm. A total of 467 wild and cultivated lentil accessions originating from multiple geographical locations were assessed for understanding genetic and allelic variations using transcriptome sequencing. An enriched single nucleotide polymorphic (SNP) resource (c. 422,101) has been delivered to lentil breeders for mining diverse genotypes for hybridization in future research and breeding. Understanding the relationship between lentil accessions and their geographical origins is also vital for identifying favorable alleles/traits that can be introgressed into the lentil germplasm. However, a weak correlation was observed between the lentil accessions, except for some accessions belong to L. culinaris and L. ervoides. Therefore, the study proposed that identifying lentil accessions with wide genetic distance variations within the same gene pool is more promising for selecting lentil accessions for breeding purposes, which also avoids crossing barriers between different gene pools. Lentil accessions that belong to L. culinaris, L. ervoides and L. nigricans were shown broad genetic distance boundaries. Therefore, these accessions with specific agronomic traits can be used to widen the lentil germplasm for breeding purposes. The genomic differentiation in each lentil species/subspecies was also analyzed using the allele-frequency-based analysis. The major genomic differentiation was observed on Chromosome 1 (Chr1; c. 1.0 Mbp), and results implied that L. nigricans was distantly related to other lentil species/subspecies. A total of five candidate genes were identified on c. 1.0 Mbp physical distance; however, the functionality of these genes in relation to wild and cultivated lentil species/subspecies still needs to be understood. One of the major abiotic stresses affecting gross profit and yield stability in Australian lentil cultivation is soil salinity. Identification of salt-tolerant varieties is the most viable and long-term option to maintain lentil productivity. However, this requires reliable and efficient screening methods. Salt tolerance assessment in lentil is currently based on morpho-physiological characterization and visual score ratings, which are often time-consuming, labor-intense and error-prone. Therefore, a novel high-throughput phenotyping (HTP) approach based on an image-based screen was developed using the LemnaTec 3D scanalyzer system to circumvent the limitations faced by current methods and accelerate the identification of the salt-tolerant varieties. The optimal salt concentration (100 mmol) and growth stages that distinguish salt tolerance levels were identified. Among the multiple phenotypic traits measured, area and color parameters were identified as the most informative traits for salt tolerance in lentil. The significant correlation observed between traditional and image-based screens (r = 0.55; p < 0.0001) demonstrated the accuracy of the developed protocol for salt tolerance in lentil, thereby can replace the conventional phenotyping approach. In addition to the phenotypic approaches, the understanding of the genetic basis of salt tolerance in lentil is important to develop salt-tolerant varieties. Recently, genome-wide association studies (GWAS) have been identified as a powerful tool to dissect the genetic basis of many phenotypic traits in diverse germplasm. Advances in resequencing approaches such as genotyping-by-sequencing (GBS) methods have also enabled the generation of a panel of SNP markers for large genome species like lentil. Two GBS approaches, targeted-capture (tGBS) and transcriptome-based sequencing (GBS-t), were tested to generate high-confidence SNP markers for association study. Among them, tGBS delivered the highest number of SNP markers with uniform distribution across the genome. Genomic regions for salt tolerance in lentil were identified on Chromosome 2 as well as on Chromosome 4. A high-affinity potassium transporter (HKT) gene was identified as the most possible candidate gene for salt tolerance in lentil. Mineral composition analysis performed on salt-treated and control lentil accessions has also been identified; Na+ ions absorbed by tolerant lentil accessions actively re-translocated them into roots or hold within the roots, supporting the candidate gene identified through GWAS. Pedigree analysis performed on salt-tolerant lentil genotypes identified two lentil accessions, ILL7685 and ILL1719, that could have been potential sources of allele contribution to salt tolerance in the lentil population. Overall, the study enriched the genomic and phenomic resources associated with lentil, thereby assisting future lentil research and breeding.
  • Item
    Thumbnail Image
    Rapid screening methods for superior trait selections in lentil and field pea breeding
    McDonald, Linda Sally ( 2020)
    Most of the lentil and field pea grown in Australia are exported to India and surrounding countries, to the Middle East, Turkey and North Africa. While each country may utilise pulses differently, common to all, is that quality is based on the visual characteristics of the whole-grain and split-pulse, and its cooking quality. One of the objectives of pulse-breeding programs is to ensure that the quality traits of new varieties align with the preferences defined by the export markets. Pulse-quality traits were historically determined using empirical tests to quantify seed size, colour, contamination and defects. Since many of these tests are time-consuming to perform, comprehensive quality evaluation is reserved for advanced germplasm. Therefore, adoption of rapid and objective methods would improve efficiency and consistency of quality evaluation and enable comprehensive assessment of early generation lines. Technological advances in digital imaging and machine learning has seen a broad application of machine vision to assess agricultural products. While there is extensive research in this field, there are still relatively few machine vision methods which have been developed for the quality-assessment of lentil and field pea grains. Within this study, rapid and objective methods were developed to assess three grain-traits, which related to visual characteristics of lentil and field pea and were identified to be important within breeding programs. The targeted applications were the classification of broad market classes of field pea, quantitation of bleaching discoloration within the ‘green pea’ market class and classification of split and dehulled fractions of lentil and field pea post milling. Machine vision algorithms were developed based on the analysis of multispectral images. Linear discriminant analysis, based on image-derived colour, shape and size features, was used for the classification of field pea market classes. The model was applied to sound and defective grain samples, achieving perfect classification of sound grain and distinguishing sound from defective grain with 97% accuracy. The extent of bleaching in green field pea samples was quantified through an objective model which was developed on visible reflectance spectra (spectrophotometric analysis) and subsequently adapted for image-based analysis of grain colour. The image-derived colour scores closely matched the spectrophotometric analysis and additionally enabled the distribution or uniformity of bleaching to be objectively quantified within each sample. Furthermore, through the image analysis scoring system, the relative susceptibility to bleaching, of each genotype, was also quantified. Milled fractions of lentil and field pea were classified through the application of artificial neural networks, where network architectures and inputs were compared. A convolutional neural network, trained on image-derived feature distributions, was found to be the most accurate and computationally efficient model. Machine vision is an expanding field of research which offers the potential for consistent, accurate and rapid product-quality evaluation. The results of this study demonstrate the efficacy of machine vision applications throughout the pulse value chain and particularly within germplasm enhancement programs. Adoption of machine vision systems can increase the capacity for comprehensive screening at all stages of breeding which is currently not practicable through standard assessment methods.