ORCID Profile
0000-0001-6289-241X
Current Organisations
Jahangirnagar University
,
University of Adelaide
,
University of Tasmania
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Publisher: Springer Science and Business Media LLC
Date: 08-11-2017
Publisher: Springer Science and Business Media LLC
Date: 19-07-2016
Publisher: Hindawi Limited
Date: 2017
DOI: 10.1155/2017/6287156
Abstract: Climate change will impact on rice food security in many parts of the world, including Bangladesh. Little attention has been given to understanding the impact of climate on rice yield for three main ecotypes (Aus, Aman, and Boro) in different areas of the country. The aim of this paper was to analyse the spatiotemporal dynamics of rice yield and climatic variables and the spatially variable climate effects on rice yield for these ecotypes in Bangladesh during 1981–2010 by employing linear mixed models and generalized linear models. The results demonstrated the substantial spatiotemporal variations of rice yield for all ecotypes across the country. Rice yield for ecotypes was more susceptible to temperature changes than rainfall effects. Modelling of a 1°C temperature increase in the country showed strong regional differences in rice yield for these ecotypes. The study concludes that future temperature changes are likely to change regional rice yield for all ecotypes and hence impact food security. The results have important consequences for food security by indicating the need for appropriate region-specific adaptation measures to reduce rice yield variability in the future. The results show the need to consider spatial differences for policy development to improve food security in Bangladesh.
Publisher: Elsevier BV
Date: 11-2021
Publisher: CSIRO Publishing
Date: 2019
DOI: 10.1071/CP19063
Abstract: This review examines the prospect of improving perennial legume adaptation to grazed mixed pasture swards across the higher-altitude regions of south-eastern Australia through improved management, particularly as it relates to soil fertility. The range of adapted perennial species available to farmers often remains limited to only one perennial forage legume species, white clover (Trifolium repens L.). Despite recent advances in cultivars for increased persistence in dryland environments, white clover remains sensitive to drought with its inherently shallow root system and limited capacity to restrict water loss from herbage. With few alternative species likely to become widely available in the foreseeable future, prospects for extending the boundaries of perennial legume adaptation likely rely on a dual approach of improving soil fertility and further genetic improvement in white clover. Improved soil fertility would focus on overcoming soil acidity and addressing nutrient deficiencies, particularly of phosphorus, potassium, boron and molybdenum, which tend to be more widespread in the target region. Addressing these soil constraints would alleviate periodic moisture stress by: (1) increased water availability through improved infiltration and soil hydraulic properties (2) increased root growth to maximise exploration of the soil volume and (3) better maintenance of plant cell structures to foster improved osmotic regulation. However, the extent to which white clover adaption may be extended remains an issue of further research. This review highlights an opportunity for further genetic improvement of white clover by focusing on improving the capacity to recover from periodic droughts through seedling regeneration. Further breeding efforts in white clover should examine the feasibility of selecting for hard seed characteristics more similar to the best-adapted subterranean clover (Trifolium subterraneum L.) cultivars across this region to promote ongoing seedling regeneration.
Publisher: Elsevier BV
Date: 08-2021
Publisher: Oxford University Press (OUP)
Date: 12-12-2021
DOI: 10.1093/INSILICOPLANTS/DIAA013
Abstract: Seasonal pasture monitoring can increase the efficiency of pasture utilization in livestock grazing enterprises. However, manual monitoring of pasture over large areas is often infeasible due to time and financial constraints. Here, we monitor changes in botanical composition in Tasmania, Australia, through application of supervised learning using satellite imagery (Sentinel-2). In the field, we measured ground cover and botanical composition over a 12-month period to develop a supervised classification approach used to identify pasture classes. Across seasons and paddocks, the approach predicted pasture classes with 75–81 % accuracy. Botanical composition varied seasonally in response to biophysical factors (primarily climate) and grazing behaviour, with seasonal highs in spring and troughs in autumn. Overall, we demonstrated that 10-m multispectral imagery can be reliably used to distinguish between pasture species as well as seasonal changes in botanical composition. Our results suggest that farmers and land managers should aim to quantify within-paddock variability rather than paddock average cover, because the extent and duration of very low ground cover puts the paddock/field at risk of adverse grazing outcomes, such as soil erosion and loss of pasture biomass, soil carbon and bio ersity. Our results indicate that satellite imagery can be used to support grazing management decisions for the benefit of pasture production and the improvement of environmental sustainability.
No related grants have been discovered for Iffat Ara.