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Identifying key genes controlling flesh colour in mangoes using genome-wide association studies (GWAS)
No full textMango flesh colour when fully ripe can range from pale-yellow to dark orange, largely depending on the cultivar. The consumer preference of this pulp colour can vary depending on the geographical region and culture, leading to a need for breeders to efficiently produce cultivars of desired colours. This study utilised a genome-wide association study (GWAS) to identify candidate genes and potential molecular markers for flesh colour. The GWAS consisted of using genomic single nucleotide polymorphism (SNP) data and corresponding flesh colours across 201 cultivars of mangoes. After pruning of the SNP data set, the GWAS utilised 871,835 SNPs resulting in a total of 87 associated genes using the top 0.01% of -log10(P) values. A gene ontology (GO) enrichment analysis indicated an association with the category for ‘biotic stress response’ for biological processes, however further investigation is required to understand the direct or indirect effect of each of the 87 associated genes on flesh colour
Facilitating industry adoption of intensive mango practices and new ag-technologies in Australia
No full textThe Australian mango industry is valued at $ 218 million AUD per annum and is widely distributed across Australia’s remote, northern tropics. The adoption of intensive mango practices and the development of new ag-technologies is key to increasing industry efficiency, profitability, and sustainability. Two national projects, “Multi-scale Monitoring Tools for Managing Australian Tree Crops” (ST19001) and the “National Tree Crop Intensification in Horticulture Program” (AS18000) were implemented to facilitate greater industry awareness and adoption of new intensive practices and ag-technologies. Multiple communications and extension methods were used with farmers to increase awareness, interest and knowledgeability of the benefits of intensification and new ag-technologies. These included presentations, hard-copy and electronic resources, field tours and on-farm demonstration sites. The engagement of farmers as champions of intensification and hosts for demonstration trials was particularly effective in demonstrating the practicality and commerciality of these new practices. This strategy known as “farmer participatory research” harnesses the farmers practical experience and expertise, to improve the on-farm value of these innovations, which then facilitates greater industry adoption
Feature Wavelengths for Quantifying Methane Concentrations Using Shortwave Infrared Hyperspectral Imaging: A Controlled Condition Study
No full textMethane (CH4) is a significant greenhouse gas, and accurately quantifying its concentrations is essential for addressing climate change concerns. This study used controlled conditions to identify potential spectral regions or wavelengths within the short-wave infrared (SWIR) region that can be used for CH4 quantification using hyperspectral imaging (HSI). This study also validated the efficiency of the wavelengths that are currently used in remote sensing. Glass containers with constant CH4 flow rates were used for collecting HSI data (1010–2495 nm) at different CH4 concentrations (N = 18; 0–2.5% CH4). Partial least-squares regression (PLSR) was trained using the full 266-bands (1010–2495 nm). Regression coefficients and PLS weights were used to identify the potentially important regions and wavelengths. New PLSR models were developed using the important regions (multiband models). Individual wavelengths identified in the current study or previously used in remote sensing studies were also used to develop PLSR models individually or in two-band combinations. Potential overlaps between the identified spectral region and H2O absorption bands were investigated. The results indicated that using spectral regions (multiband) or combinations of two bands provided more accuracy compared to when single bands were used. The following spectral regions can be used for the quantification of CH4 in descending order: full 266-band (1010–2495 nm) > 1648 + 1670 nm > full 128-band (1010–1700 nm) > 2150–2243 nm > 1010–1185 nm. The results of this study were obtained under controlled conditions without interfering compounds. Testing these spectral regions in more complex environments will help confirm the best SWIR wavelengths
Seedling Emergence and Soil Seedbank Persistence of the Invasive Azadirachta indica A. Juss
No full textAzadirachta indica (Neem tree) has become widely naturalised and invasive across many countries and regions including northern Australia. To aid management of A. indica where it has become a weed, a series of studies were undertaken to determine its potential soil seed bank persistence. In a field trial, packets of seeds were buried, retrieved periodically over two years and the seed viability assessed. Viability declined rapidly, with a single viable seed retrieved after 12 months burial and none thereafter. Burial depth, soil type, and pasture cover (present and excluded) significantly influenced viability (%) at 3- and 6-month retrievals. Similar data were obtained from repeated runs of a controlled ageing laboratory experiment, which categorized seeds as forming a ‘transient’ seed bank. In a third trial, fresh fruits were placed on the soil surface in replicated field enclosures over two consecutive years and seedling emergence monitored fortnightly. In both years there was no emergence from pasture excluded soil plots and emergence ceased after 2.3 and 8.4 months in plots with pasture present. A fourth (glasshouse) trial found most seeds will emerge from the soil when buried from 1 to 4 cm. However, more fatal germination than successful emergence was recorded for seeds buried at 8 cm. Seed desiccation and fatal germination are factors in A. indica developing a transient soil seed bank, and infestations require shorter-term control programs where seed input is prevented
Mapping quantitative trait loci for seminal root angle in a selected durum wheat population
No full textSeminal root angle (SRA) is an important root architectural trait associated with drought adaptation in cereal crops. To date, all attempts to dissect the genetic architecture of SRA in durum wheat (Triticum durum Desf.) have used large association panels or structured mapping populations. Identifying changes in allele frequency generated by selection provides an alternative genetic mapping approach that can increase the power and precision of QTL detection. This study aimed to map quantitative trait loci (QTL) for SRA by genotyping durum lines created through divergent selection using a combination of marker-assisted selection (MAS) for the major SRA QTL (qSRA-6A) and phenotypic selection for SRA over multiple generations. The created 11 lines (BC1F2:5) were genotyped with genome-wide single-nucleotide polymorphism (SNP) markers to map QTL by identifying markers that displayed segregation distortion significantly different from the Mendelian expectation. QTL regions were further assessed in an independent validation population to confirm their associations with SRA. The experiment revealed 14 genomic regions under selection, 12 of which have not previously been reported for SRA. Five regions, including qSRA-6A, were confirmed in the validation population. The genomic regions identified in this study indicate that the genetic control of SRA is more complex than previously anticipated. Our study demonstrates that selection mapping is a powerful approach to complement genome-wide association studies for QTL detection. Moreover, the verification of qSRA-6A in an elite genetic background highlights the potential for MAS, although it is necessary to combine additional QTL to develop new cultivars with extreme SRA phenotypes
Temporal changes in ruminal microbiota composition and diversity in dairy cows supplemented with a lactobacilli-based DFM
No full textIntroductionThis study aimed to evaluate the impact of lactobacilli-based direct-fed microbial (DFM) supplementation on the composition and diversity of the ruminal microbiota in dairy cows. Understanding how DFM influences microbial populations can inform strategies to enhance animal health and productivity.MethodsOver a 16-month period (September 2021 to January 2023), ruminal fluid samples were collected from fifty dairy cows assigned to either a DFM-supplemented group (DFM; n = 25) or an unsupplemented control group (CON; n = 25). Microbial DNA was extracted and subjected to 16S rRNA gene amplification and sequencing. Microbial diversity was assessed using alpha- and beta-diversity metrics (p < 0.05), and linear discriminant analysis effect size (LEfSe) was employed to identify differentially abundant taxa. Multivariable analyses were used to explore associations with age, average milk production, days in milk (DIM), time, and supplementation.ResultsThe dominant bacterial phyla identified were Bacillota and Bacteroidota, while Methanobacteriaceae was the predominant archaeal family. The DFM group showed significantly higher abundance of genera such as Eubacterium_Q, Atopobium sp. UBA7741, and Sharpea (p < 0.05). Conversely, Bacillus_P_294101 and SFMI01 were more abundant in the CON group. Temporal changes in microbial composition were observed, with significant differences in community diversity and structure between groups over time.DiscussionThese findings demonstrate that lactobacilli-based DFM supplementation can significantly alter the ruminal microbial ecosystem in dairy cows. The observed microbial shifts, including increases in beneficial bacterial taxa, highlight the potential of DFM as a nutritional strategy to modulate rumen function and improve dairy cow performance
Correlation between gastrointestinal morphological changes, enteric microbiota, and changes in live weight in dairy calves
No full textThis study aimed to quantify the association between fecal microbiota biomarkers, gastrointestinal tract morphology, and ADG of dairy calves from birth until weaning in response to feeding a direct-fed microbial (DFM) supplement as part of their milk diet. We randomly assigned 44 newborn Holstein-Friesian calves to treatment (TRT) and control (CON) groups. The TRT group calves received a once-daily dose of Lacticaseibacillus- and Lentilactobacillus-based DFM liquid formulation. Four genera, Prevotella7, Succiniclasticum, Terrisporobacter, and Carnobacterium, were enriched and identified as biomarkers of low ADG. A total of 14 bacterial taxa were associated with measured gastrointestinal histopathology variables in TRT and CON groups. Although this study lists several bacterial taxa that have known roles in fermentation and nutrient metabolism vital for rumen function, their specific contributions to gastrointestinal development and weight gain remain to be fully understood. Our findings support a strategic approach to probiotic use in heifers to boost health and productivity
Seed Germination Ecology and Longevity of the Invasive Aquatic Plant Sagittaria platyphylla
No full textSagittaria platyphylla (Engelm.) J.G.Sm. is an invasive aquatic plant of concern in Australian freshwater systems. Understanding its seed germination ecology and seedbank longevity is critical for effective management. This study examined environmental influences on germination and longevity through three controlled experiments. Seeds germinated between 17 and 29 °C, with optimal germination (96 ± 2%) at 21 °C under a 12/12 h light/dark photoperiod. High germination (93–99%) also occurred under light in diurnal regimes of 15/5 °C, 25/15 °C, and 30/20 °C. In a burial experiment, seedlings emerged only from surface-sown seeds (76 ± 4%); no emergence occurred from buried seeds, though viability remained high, peaking at 98 ± 2% at 2.5 cm depth. A controlled aging test indicated a 50% viability loss (P50) in 36 days under warm, moist laboratory conditions. Based on established criteria, S. platyphylla produces short-lived seeds, which are likely to persist in the substrate seedbank for <1 to 3 years. The strong light dependence of germination suggests that sediment disturbance, which exposes buried seeds to light, could significantly enhance recruitment, highlighting the importance of minimizing disturbance for effective long-term management
A novel real-time PCR for New World Screwworm Fly (Cochliomyia hominivorax) and its application in a non-destructive multiplex for efficient detection of screwworm flies
No full textSurveillance and diagnostics are critical for the early detection, containment and eradication of exotic pests. For screwworm fly, this is usually via targeted surveillance and exclusion testing of trap-caught flies, as well as identification of larvae associated with myiasis wounds. We present a specific and sensitive real-time PCR assay for detection of the New World screwworm fly, Cochliomyia hominivorax Coquerel (Diptera: Calliphoridae). The assay targets the cytochrome oxidase subunit 1 (cox1) gene from adult flies or larvae and retains high analytical sensitivity when multiplexed with an existing assay for the Old World screwworm fly, Chrysomya bezziana Villeneuve (Diptera: Calliphoridae), achieving a limit of detection of less than 1 copy per microlitre of reaction. To assess its utility for surveillance and diagnostics, a novel non-destructive DNA extraction method was performed on spiked trap catches of field-caught flies, and on boiled and unboiled specimens of larval instars. The multiplexed assay detected 95% of spiked flies, and all screwworm flies from positive samples were retrieved and morphologically identified. Results from larval instars confirmed that the assay can be used for larvae, with higher sensitivity observed for unboiled larval instars. This molecular assay enables the simultaneous detection of Co. hominivorax and Ch. bezziana, offering a reliable alternative to existing single-target and destructive methods of bulk fly testing. It also holds potential for broader application in the identification of larval stages
UMono: Physical-Model-Informed Hybrid CNN–Transformer Framework for Underwater Monocular Depth Estimation
No full textUnderwater monocular depth estimation serves as the foundation for tasks such as 3-D reconstruction of underwater scenes. However, due to the water medium and the absorption and scattering of light in water, the underwater environment undergoes a distinctive imaging process, which presents challenges in accurately estimating depth from a single image. The existing methods fail to consider the unique characteristics of underwater environments, leading to inadequate estimation results and limited generalization performance. Furthermore, underwater depth estimation requires extracting and fusing both local and global features, which is not fully explored in existing methods. In this article, an end-to-end learning framework for underwater monocular depth estimation called UMono is presented, which incorporates underwater image formation model characteristics into the network architecture, and effectively utilizes both local and global features of an underwater image. Specifically, UMono consists of an encoder with a hybrid architecture of a convolutional neural network (CNN) and Transformer and a decoder guided by a medium transmission map. First, we develop an underwater deep feature extraction (UDFE) block, which leverages the CNN and Transformer in parallel to achieve comprehensive extraction of both local and global features. These features are effectively integrated via the proposed local–global feature fusion (LGFF) module. By stacking the UDFE block as the basic unit, we constructed a hybrid encoder that generates four-stage hierarchical features. Subsequently, the medium transmission map is incorporated into the network as underwater domain knowledge, together with the encoded hierarchical features, is fed into the underwater depth information aggregation (UDIA) module, which aggregates depth information from the physical model and the neural network by a proposed cross attention mechanism. Then, the aggregated features serve as the guiding information for each decoding stage, facilitating the model in achieving comprehensive scene understanding and precise depth estimation. The final estimated depth map is obtained through consecutive upsampling processing. Experimental results demonstrate that the proposed method is effective for underwater monocular depth estimation and outperforms the existing methods in both quantitative and qualitative analyses