Publications

Salinity is an ever-increasing problem in agriculture worldwide and especially in Australia. Improved genotypes that are well adapted to saline conditions are needed to enhance and sustain production in these areas. A screening of 263 accessions of chickpea, including 211 accessions from ICRISAT’s mini-core collection (10% of the core collection and 1% of the entire collection), showed a six-fold range of variation for seed yield under salinity, with several genotypes yielding 20% more than the previously-released salinity tolerant cultivar CSG8962. No significant relation was found between biomass at the late vegetative stage and final seed yield under salinity. Performance of seed yield under salinity was explained in part by the yield potential under control conditions, and a salinity tolerance component. The major trait related to salinity tolerance was the ability to maintain under salinity a large number of viable pods with seeds. In contrast, the relative seed size under salinity did not differ between tolerant and sensitive genotypes. Preliminary analysis of genotypic data for approximately 50 SSR markers on 211 genotypes revealed some associations with salinity tolerance that deserve a detailed analysis. Future effort should focus on the effect of salinity on the reproductive stage of development.

Root growth and proliferation are important for achieving the yield potential of chickpea in soils prone to waterlogging. Root growth characteristics and seed yield of the desi cultivar Rupali and the kabuli cultivar Almaz that differ in seed size and early vigour were investigated under well-drained and transiently-waterlogged conditions in glass-walled root boxes in a controlled-temperature glasshouse. Rooting parameters and detailed measurements of root growth and proliferation were made at 2-day intervals using a root mapping technique and by sampling the roots from the soil 14 days after the transient waterlogging ended. Although the roots of the kabuli cultivar Almaz had greater dry matter and length than the desi cultivar Rupali, the subsurface waterlogging promptly stopped the root growth of both genotypes. Root dry matter in both types of chickpea was reduced by two-thirds, 14 days after the cessation of the 12-day waterlogging treatment. The reduction resulted from an inhibition in root growth and proliferation, which led to a lower root length density down the soil profile, particularly in the top 0.6Â m of the waterlogged plants. While root length and root dry matter was higher in the kabuli cultivar Almaz than in the desi cultivar Rupali after waterlogging, they were not associated with a greater above-ground dry matter or seed yield at maturity. The transient waterlogging reduced the seed yield by 54% in the kabuli cultivar Almaz and by 44% in the desi cultivar Rupali. The reduction in seed yield in the kabuli cultivar Almaz resulted from 50% decline in the number of seeds per pod while in the desi cultivar Rupali it was a consequence of less pods and seeds per pod. Subsurface waterlogging changed the rooting pattern in chickpea, inhibiting root branching and the growth of the tap root and severely reducing the growth of root branches. The release from the waterlogging induced the production of new roots rather than regrowth of existing roots.

Cotton is the world’s most widely cultivated fiber crop and holds great significance in Xinjiang. However, unsuitable planting environments can hinder farmer income and result in a substantial waste of agricultural resources.This study explores suitability of cotton planting areas in Xinjiang to reduce agricultural inputs and pollution. The goal is to promote sustainable agricultural development by considering both climate change and soil fertility, factors often overlooked in previous research. We analyzed climate change trends in Xinjiang and used machine learning-transfer component analysis to build a transferable coupling model for total nitrogen (TN) and soil organic carbon (SOC) indicators, resulting in a cotton suitability zoning that accounts for climate and soil fertility factors. Xinjiang has seen an overall increase in cumulative temperature and rainfall, with southern Xinjiang showing the most significant rise (4.02% in temperature and 16.26% in rainfall). The random forest model (RF) outperformed multivariate linear regression (MLR) and support vector machines (SVM) in predicting soil fertility indicators (TN: R 2 = 0 . 80 , SOC: R 2 = 0 . 77 ). The RF-TCA coupling model enhanced adaptability, with better performance in TN prediction compared to SOC. The Xinjiang cotton suitability zoning, based on meteorological and soil data, indicates a northward shift in suitable cotton planting areas in northern Xinjiang, while southern Xinjiang continues to maintain a substantial number of suitable planting zones. Notably, the disparity in suitability between the two regions has been narrowing over time. The research offers valuable insights for optimizing cotton planting locations, enhancing resource efficiency, and promoting sustainable development in Xinjiang. • Gray relation and full subset analysis of remote sensing indices improved model prediction accuracy. • An RF-TCA coupled machine learning model was developed to enhance transferability. • A comprehensive system was established to identify suitable cotton planting areas in Xinjiang, using meteorology and soil fertility factors.

The effects of three mulch types (vermicompost, plastic, and straw) plus an untreated control, in factorial combination with three irrigation regimes (RFD: rainfed condition; SIF: one supplemental irrigation at the flowering stage; SIVF: two supplemental irrigations at the vegetative and flowering stages) on linseed growth, seed yield and oil composition, and biochemical status were investigated. Linseed plants under two irrigations and straw mulch showed the highest seed yield (300 g and 222.4 g m-2, respectively), biological yield (887.9 g m-2), and concentration of oleic and linoleic acids. The plastic mulch application under rainfed conditions or one irrigation increased stearic and palmitic acid concentrations, respectively. Water deficit stress encouraged the accumulation of proline (10.1 μmol g-1 fresh weight (FW)), total phenols (6.68 mg g-1 FW), and DPPH radical scavenging capacity (56.5%). Plants grown in straw mulched soil showed the highest total phenol content and DPPH radical scavenging capacity, while control plants displayed the highest proline concentration. Enzyme activities, including catalase and superoxide dismutase, were enhanced under straw and plastic mulch compared to control plants under rainfed conditions. Our findings suggest that straw mulch represents an effective, sustainable strategy to successfully manage linseed crops, mitigating the adverse effects of water deficit stress on plant performance.

The decline in global plant diversity has raised concerns about its implications for carbon fixation and global greenhouse gas emissions (GGE), including carbon dioxide (CO₂), nitrous oxide (N₂O) and methane (CH₄). Therefore, we conducted a comprehensive meta-analysis of 2103 paired observations, examining GGE, soil organic carbon (SOC) and plant carbon in plant mixtures and monocultures. Our findings indicate that plant mixtures decrease soil N₂O emissions by 21.4% compared to monocultures. No significant differences occurred between mixtures and monocultures for soil CO₂ emissions, CH₄ emissions or CH₄ uptake. Plant mixtures exhibit higher SOC and plant carbon storage than monocultures. After 10 years of vegetation development, a 40% reduction in species richness decreases SOC content and plant carbon storage by 12.3% and 58.7% respectively. These findings offer insights into the intricate connections between plant diversity, soil and plant carbon storage and GGE-a critical but previously unexamined aspect of biodiversity-ecosystem functioning.

Cadmium (Cd) is a hazardous heavy metal, toxic to our ecosystem even at low concentrations. Cd stress negatively affects plant growth and development by triggering oxidative stress. Limited information is available on the role of iron (Fe) in ameliorating Cd stress tolerance in legumes. This study assessed the effect of Cd stress in two lentil (<i>Lens culinaris</i> Medik.) varieties differing in seed Fe concentration (L4717 (Fe-biofortified) and JL3) under controlled conditions. Six biochemical traits, five growth parameters, and Cd uptake were recorded at the seedling stage (21 days after sowing) in the studied genotypes grown under controlled conditions at two levels (100 μM and 200 μM) of cadmium chloride (CdCl₂). The studied traits revealed significant genotype, treatment, and genotype × treatment interactions. Cd-induced oxidative damage led to the accumulation of hydrogen peroxide (H₂O₂) and malondialdehyde in both genotypes. JL3 accumulated 77.1% more H₂O₂ and 75% more lipid peroxidation products than L4717 at the high Cd level. Antioxidant enzyme activities increased in response to Cd stress, with significant genotype, treatment, and genotype × treatment interactions (<i>p</i> < 0.01). L4717 had remarkably higher catalase (40.5%), peroxidase (43.9%), superoxide dismutase (31.7%), and glutathione reductase (47.3%) activities than JL3 under high Cd conditions. In addition, L4717 sustained better growth in terms of fresh weight and dry weight than JL3 under stress. JL3 exhibited high Cd uptake (14.87 mg g^-1 fresh weight) compared to L4717 (7.32 mg g^-1 fresh weight). The study concluded that the Fe-biofortified lentil genotype L4717 exhibited Cd tolerance by inciting an efficient antioxidative response to Cd toxicity. Further studies are required to elucidate the possibility of seed Fe content as a surrogacy trait for Cd tolerance.

In Timor-Leste, most paddy fields are abandoned after rice harvest due to limited water resources for another rice production cycle, particularly in lowland coastal areas. There is substantial scope for including legumes and other crops in the rice–fallow system in Timor-Leste. This study investigated the adaptation of grain legumes to terminal drought. The experiment was undertaken in 2018 and 2019 at field sites in Vemase and Laleia, respectively, on the northeast coast of Timor-Leste. The experiments used a split-plot design with two factors (water treatment and species) and three blocks (Vemase site) or four blocks (Laleia site). In 2018, the water treatments were well-watered control (W0), water withheld from flower initiation to maturity (W1), and water withheld after seedling establishment to maturity (W2). In 2019, the water treatments were well-watered control (W0) and water withheld from flower initiation to maturity (W1). Grain legumes were mungbean and soybean tested against grass pea (cv. Ceora), a well-known drought-adapted grain legume. The measured parameters included soil water content, crop phenology, plant growth and development, yield and yield components. The experiments revealed that mungbean is the most suitable grain legume crop after rice harvest under moderate drought conditions, while soybean is the preferred option under severe drought. Grass pea could be the best adaptive grain legume under severe drought in Timor-Leste when combined with the worsening conditions of climate change.

Drought stress induces a range of physiological changes in plants, including oxidative damage. Ascorbic acid (AsA), commonly known as vitamin C, is a vital non-enzymatic antioxidant capable of scavenging reactive oxygen species and modulating key physiological processes in crops under abiotic stresses like drought. Chickpea (Cicer arietinum L.), predominantly cultivated in drought-prone regions, offers an ideal model for studying drought tolerance. We explored the potential of AsA phenotyping to enhance drought tolerance in chickpea. Using an automated phenomics facility to monitor daily soil moisture levels, we developed a protocol to screen chickpea genotypes for endogenous AsA content. The results showed that AsA accumulation peaked at 30% field capacity (FC)-when measured between 11:30 am and 12:00 noon-coinciding with the maximum solar radiation (32 °C). Using this protocol, we screened 104 diverse chickpea genotypes and two control varieties for genetic variability in AsA accumulation under soil moisture depletion, identifying two groups of genotypes with differing AsA levels. Field trials over two consecutive years revealed that genotypes with higher AsA content, such as BDNG-2018-15 and PG-1201-20, exhibited enhanced drought tolerance and minimal reductions in yield compared to standard cultivars. These AsA-rich genotypes hold promise as valuable genetic resources for breeding programs aimed at improving drought tolerance in chickpea.