Drought is considered one of the costliest natural disasters that result in water scarcity and crop damage almost every year. Drought monitoring and forecasting are essential for the efficient management of water resources and sustainability in agriculture. However, the design of a consistent drought prediction model based on the dynamic relationship of the drought index with its antecedent values remains a challenging task. In the present research, the SVR (support vector regression) model was hybridized with two different optimization algorithms namely; Particle Swarm Optimization (PSO) and Harris Hawks Optimization (HHO) for reliable prediction of effective drought index (EDI) 1 month ahead, at different locations of Uttarakhand State of India. The inputs of the models were selected through partial autocorrelation function (PACF) analysis. The output produced by the SVR-HHO and SVR-PSO models was compared with the EDI estimated from observed data using five statistical indicators, i.e., RMSE (Root Mean Square Error), MAE (Mean Absolute Error), COC (Coefficient of Correlation), NSE (Nash-Sutcliffe Efficiency), WI (Willmott Index), and graphical inspection of radar-chart, time-variation plot, box-whisker plot, and Taylor diagram. Appraisal of results indicates that the SVR-HHO model (RMSE = 0.535-0.965, MAE = 0.363-0.622, NSE = 0.558-0.860, COC = 0.760-0.930, and WI = 0.862-0.959) outperformed the SVR-PSO model (RMSE = 0.546-0.967, MAE = 0.372-0.625, NSE = 0.556-0.855, COC = 0.758-0.929, and WI = 0.861-0.956) in predicting EDI. Visual inspection of model performances also showed a better performance of SVR-HHO compared to SVR-PSO in replicating the median, inter-quartile range, spread, and pattern of the EDI estimated from observed rainfall. The results indicate that the hybrid SVR-HHO approach can be utilized for reliable EDI predictions in the study area.
This study introduces ensemble empirical mode decomposition (EEMD) coupled with the autoregressive integrated moving average (ARIMA) model for drought prediction. In the realm of drought forecasting, we assess the EEMD-ARIMA model against the traditional ARIMA approach, using monthly precipitation data from January 1970 to December 2019 in Herat province, Afghanistan. Our evaluation spans various timescales of standardized precipitation index (SPI) 3, SPI 6, SPI 9, and SPI 12. Statistical indicators like root-mean-square error, mean absolute error (MAE), mean absolute percentage error (MAPE), and R2 are employed. To comprehend data features thoroughly, each SPI series initially computed from the original monthly precipitation time series. Subsequently, each SPI undergoes decomposition using EEMD, resulting in intrinsic mode functions (IMFs) and one residual series. The next step involves forecasting each IMF component and residual using the corresponding ARIMA model. To create an ensemble forecast for the initial SPI series, the predicted outcomes of the modeled IMFs and residual series are finally added. Results indicate that EEMD-ARIMA significantly enhances drought forecasting accuracy compared to conventional ARIMA model.
The purposes of this research were to study the characteristics chemistry of pH, anions and cations in rainwater, and to identify the possible sources that contributing to the acid precipitation during southwest monsoon season with occurrence of extreme drought event. During the southwest monsoon season, it normally occurs along with haze phenomenon that every year will hit Southeast Asia. This condition will aggravate with high acidic particles in the atmosphere due to the prolonged drought. The analysed parameters which involved pH, anions (NO3-, SO42- and Cl-) and cations (Ca2+, Mg2+, Na+ and K+) were analysed using pH meter, Hach DR 2800, argentometric method and ICP-OES. From the findings, it showed that acid rain occurred during the southwest monsoon season with the range of pH values from 4.95 ± 0.13 to 6.40 ± 0.03 and the total average of pH 5.71 ± 0.32. Anions NO3-, SO42- and Cl- were found to be the dominant compositions of the acid rain occurrences with higher concentrations detected. In overall, rural area recorded with higher acidity of precipitation at total average of pH 5.54 ± 0.39 compared to urban area at pH 5.77 ± 0.26. Rural area surprisingly recorded higher frequency occurrences of acid rain with pH lesser than 5.6 and below compared to urban area. As for public health and safety, all rainwater samples during the acid rain event were found exceeded the allowable limits of NWQS and WHO standards, that shown not suitable for skin contact, recreational purposes even for drinking purposes.
This study's primary purpose was to investigate the possible amelioration of limited irrigation conditions by mycorrhiza (AMF), vermicompost, and green manure for lingrain plants. This experiment was accomplished as a factorial based on the completely randomized design with three replications. The first factor was green manure (without green manure and with Trifolium pratense as green manure); the second factor consisted of Rhizophagus irregularis mycorrhiza, vermicompost, a combination of mycorrhiza and vermicompost and none of them, and also the third factor was irrigation regime (full irrigation and late-season water limitation). Green manure, vermicompost, and mycorrhiza single-use enhanced the plant's underwater limitation conditions compared to the control. However, vermicompost and green manure or mycorrhiza developed a positive synergistic effect on most traits. Combining green manure with the dual fertilizer (mycorrhiza + vermicompost) resulted in the vermicompost and mycorrhiza synergistic effects, especially under limited irrigation. Consequently, the combination of green manure, mycorrhiza, and vermicompost experienced the highest amount of leaf relative water content, root colonization, leaf nitrogen, chlorophyll a, chlorophyll b, carotenoids, antioxidant enzymes activity, grain yield, and oil yield, which would lead to more resistance of plants to limited irrigation conditions.
Aliphatic glucosinolate is an important secondary metabolite responsible in plant defense mechanism and carcinogenic
activity. It plays a crucial role in plant adaptation towards changes in the environment such as salinity and drought.
However, in many plant genomes, there are thousands of genes encoding proteins still with putative functions and
incomplete annotations. Therefore, the genome of Arabidopsis thaliana was selected to be investigated further to identify
any putative genes that are potentially involved in the aliphatic glucosinolate biosynthesis pathway, most of its gene are
with incomplete annotation. Known genes for aliphatic glucosinolates were retrieved from KEGG and AraCyc databases.
Three co-expression databases i.e., ATTED-II, GeneMANIA and STRING were used to perform the co-expression network
analysis. The integrated co-expression network was then being clustered, annotated and visualized using Cytoscape plugin,
MCODE and ClueGO. Then, the regulatory network of A. thaliana from AtRegNet was mapped onto the co-expression
network to build the transcriptional regulatory network. This study showed that a total of 506 genes were co-expressed
with the 61 aliphatic glucosinolate biosynthesis genes. Five transcription factors have been predicted to be involved
in the biosynthetic pathway of aliphatic glucosinolate, namely SEPALLATA 3 (SEP3), PHYTOCHROME INTERACTING FACTOR
3-like 5 (AtbHLH15/PIL5), ELONGATED HYPOCOTYL 5 (HY5), AGAMOUS-like 15 (AGL15) and GLABRA 3 (GL3). Meanwhile,
three other genes with high potential to be involved in the aliphatic glucosinolates biosynthetic pathway were identified,
i.e., methylthioalkylmalate-like synthase 4 (MAML-4) and aspartate aminotransferase (ASP1 and ASP4). These findings
can be used to complete the aliphatic glucosinolate biosynthetic pathway in A. thaliana and to update the information
on the glucosinolate-related pathways in public metabolic databases.
In the modern world, wheat, a vital global cereal and the second most consumed, is vulnerable to climate change impacts. These include erratic rainfall and extreme temperatures, endangering global food security. Research on hydrogen-rich water (HRW) has gained momentum in plant and agricultural sciences due to its diverse functions. This study examined the effects of different HRW treatment durations on wheat, revealing that the 4-h treatment had the highest germination rate, enhancing potential, vigor, and germination indexes. This treatment also boosted relative water content, root and shoot weight, and average lengths. Moreover, the 4-h HRW treatment resulted in the highest chlorophyll and soluble protein concentrations in seeds while reducing cell death. The 4-h and 5-h HRW treatments significantly increased H2O2 levels, with the highest NO detected in both root and shoot after 4-h HRW exposure. Additionally, HRW-treated seeds exhibited increased Zn and Fe concentrations, along with antioxidant enzyme activities (CAT, SOD, APX) in roots and shoots. These findings suggest that HRW treatment could enhance wheat seed germination, growth, and nutrient absorption, thereby increasing agricultural productivity. Molecular analysis indicated significant upregulation of the Dreb1 gene with a 4-h HRW treatment. Thus, it shows promise in addressing climate change effects on wheat production. Therefore, HRW treatment could be a hopeful strategy for enhancing wheat plant drought tolerance, requiring further investigation (field experiments) to validate its impact on plant growth and drought stress mitigation.
Precipitation patterns are changing across the globe causing more severe and frequent drought for many forest ecosystems. Although research has focused on the resistance of tree populations and communities to these novel precipitation regimes, resilience of forests is also contingent on recovery following drought, which remains poorly understood, especially in aseasonal tropical forests. We used rainfall exclusion shelters to manipulate the interannual frequency of drought for diverse seedling communities in a tropical forest and assessed resistance, recovery and resilience of seedling growth and mortality relative to everwet conditions. We found seedlings exposed to recurrent periods of drought altered their growth rates throughout the year relative to seedlings in everwet conditions. During drought periods, seedlings grew slower than seedlings in everwet conditions (i.e., resistance phase) while compensating with faster growth after drought (i.e., recovery phase). However, the response to frequent drought was species dependent as some species grew significantly slower with frequent drought relative to everwet conditions while others grew faster with frequent drought due to overcompensating growth during the recovery phase. In contrast, mortality was unrelated to rainfall conditions and instead correlated with differences in light. Intra-annual plasticity of growth and increased annual growth of some species led to an overall maintenance of growth rates of tropical seedling communities in response to more frequent drought. These results suggest these communities can potentially adapt to predicted climate change scenarios and that plasticity in the growth of species, and not solely changes in mortality rates among species, may contribute to shifts in community composition under drought.
This paper aims to select the most appropriate rain-based meteorological drought index for detecting drought characteristics and identifying tropical drought events in the Johor River Basin (JRB). Based on a multi-step approach, the study evaluated seven drought indices, including the Rainfall Anomaly Index (RAI), Standardized Precipitation Index (SPI), China-Z Index (CZI), Modified China-Z Index (MCZI), Percent of Normal (PN), Deciles Index (DI), and Z-Score Index (ZSI), based on the CHIRPS rainfall gridded-based datasets from 1981 to 2020. Results showed that CZI, MCZI, SPI, and ZSI outperformed the other indices based on their correlation and linearity (R2 = 0.96-0.99) along with their ranking based on the Compromise Programming Index (CPI). The historical drought evaluation revealed that MCZI, SPI, and ZSI performed similarly in detecting drought events, but SPI was more effective in detecting spatial coverage and the occurrence of 'very dry' and 'extremely dry' drought events. Based on SPI, the study found that the downstream area, north-easternmost area, and eastern boundary of the basin were more prone to higher frequency and longer duration droughts. Furthermore, the study found that prolonged droughts are characterized by episodic drought events, which occur with one to three months of 'relief period' before another drought event occurs. The study revealed that most drought events that coincide with El Niño, positive Indian Ocean Dipole (IOD), and negative Madden-Julian Oscillation (MJO) events, or a combination of these events, may worsen drought conditions. The application of CHIRPS datasets enables better spatiotemporal mapping and prediction of drought for JRB, and the output is pertinent for improving water management strategies and adaptation measures. Understanding spatiotemporal drought conditions is crucial to ensuring sustainable development and policies through better regulation of human activities. The framework of this research can be applied to other river basins in Malaysia and other parts of Southeast Asia.
Maize is an imperative grain crop used as a staple food in several countries around the world. Water deficiency is a serious
problem limiting its growing area and production. Identification of drought tolerant maize germplasm is comparatively
easy and sustainable approach to combat this issue. Present research was conducted to evaluate 50 maize genotypes
for drought tolerance at early growth stage. Drought tolerance was assessed on the basis of several morphological
and physiological parameters. Analysis of variance showed significant variation among the tested maize genotypes for
recorded parameters. Principal component analysis revealed important morpho-physiological traits that were playing
key role in drought tolerance. Correlation studies depicted significant positive correlation among the attributes such as
fresh shoot length (FSL), fresh root length (FRL), dry shoot weight (DSW), dry root weight (DRW), relative water contents
(RWC) and total dry matter (TDM) while a strongly negative correlation was observed among RWC and excised leaf
water loss. Results concluded that the parameters fresh shoot weight, fresh root weight, FRL, DRW, TDM, cell membrane
thermo stability (CMT) and RWC can be useful for rapid screening of maize germplasm for drought tolerance at early
growth stages. Furthermore, the genotypes 6, 16, 18, 40, 45 and 50 can be used as a drought tolerant check in breeding
programs. Moreover, biplot analysis along with other indices was proved to be a useful approach for rapid and cost
efficient screening of large number of genotypes against drought stress condition.
Accurate prediction of any type of natural hazard is a challenging task. Of all the various hazards, drought prediction is challenging as it lacks a universal definition and is getting adverse with climate change impacting drought events both spatially and temporally. The problem becomes more complex as drought occurrence is dependent on a multitude of factors ranging from hydro-meteorological to climatic variables. A paradigm shift happened in this field when it was found that the inclusion of climatic variables in the data-driven prediction model improves the accuracy. However, this understanding has been primarily using statistical metrics used to measure the model accuracy. The present work tries to explore this finding using an explainable artificial intelligence (XAI) model. The explainable deep learning model development and comparative analysis were performed using known understandings drawn from physical-based models. The work also tries to explore how the model achieves specific results at different spatio-temporal intervals, enabling us to understand the local interactions among the predictors for different drought conditions and drought periods. The drought index used in the study is Standard Precipitation Index (SPI) at 12 month scales applied for five different regions in New South Wales, Australia, with the explainable algorithm being SHapley Additive exPlanations (SHAP). The conclusions drawn from SHAP plots depict the importance of climatic variables at a monthly scale and varying ranges of annual scale. We observe that the results obtained from SHAP align with the physical model interpretations, thus suggesting the need to add climatic variables as predictors in the prediction model.
Less than half of anthropogenic carbon dioxide emissions remain in the atmosphere. While carbon balance models imply large carbon uptake in tropical forests, direct on-the-ground observations are still lacking in Southeast Asia. Here, using long-term plot monitoring records of up to half a century, we find that intact forests in Borneo gained 0.43 Mg C ha-1 per year (95% CI 0.14-0.72, mean period 1988-2010) above-ground live biomass. These results closely match those from African and Amazonian plot networks, suggesting that the world's remaining intact tropical forests are now en masse out-of-equilibrium. Although both pan-tropical and long-term, the sink in remaining intact forests appears vulnerable to climate and land use changes. Across Borneo the 1997-1998 El Niño drought temporarily halted the carbon sink by increasing tree mortality, while fragmentation persistently offset the sink and turned many edge-affected forests into a carbon source to the atmosphere.
Climate change is one of the major challenges societies round the world face at present. Apart from efforts to achieve a reduction of emissions of greenhouse gases so as to mitigate the problem, there is a perceived need for adaptation initiatives urgently. Ecosystems are known to play an important role in climate change adaptation processes, since some of the services they provide, may reduce the impacts of extreme events and disturbance, such as wildfires, floods, and droughts. This role is especially important in regions vulnerable to climate change such as the African continent, whose adaptation capacity is limited by many geographic and socio-economic constraints. In Africa, interventions aimed at enhancing ecosystem services may play a key role in supporting climate change adaptation efforts. In order to shed some light on this aspect, this paper reviews the role of ecosystems services and investigates how they are being influenced by climate change in Africa. It contains a set of case studies from a sample of African countries, which serve the purpose to demonstrate the damages incurred, and how such damages disrupt ecosystem services. Based on the data gathered, some measures which may assist in fostering the cause of ecosystems services are listed, so as to cater for a better protection of some of the endangered Africa ecosystems, and the services they provide.
Rice is the most important staple crop in Malaysia and is cultivated all over the country, including the state of Sabah. The uniqueness of rice cultivation in Sabah lies in the type of rice itself, deriving mainly from local or non-commercial cultivars but with distinctive characteristics including long grains, aromatic properties, and drought tolerance. However, despite having these important agricultural traits, information on the genetic diversity of Sabah rice remains limited. Hence, the purpose of this study was to determine the genetic polymorphisms of Sabah rice using random amplification of polymorphic DNA (RAPD) markers. A total of 101 alleles were profiled, from which 94% were identified as polymorphic. Phylogenetic analysis grouped the rice samples into three clusters, with two clusters classifying the ability of rice to grow under different planting conditions, suitable for growth irrigate and upland condition. The first cluster was dominated by cultivars that could survive in wet (irrigated) areas, while the other featured those that were found in dry (upland) areas. Furthermore, two alleles, OPA-05-B2 and OPA-01-B11, were found to be unique to cultivars within the upland cluster and were thus proposed to be involved in dry environmental adaptation. The results of the present study provide an insight into the genetic relationships and diversity of Sabah rice.
CBF/DREB1 is a group of transcription factors that are mainly involved in abiotic stress tolerance in plants. They belong to the AP2/ERF superfamily of plant-specific transcription factors. A gene encoding a new member of this group was isolated from ripening oil palm fruit and designated as EgCBF3. The oil palm fruit demonstrates the characteristics of a climacteric fruit like tomato, in which ethylene has a major impact on the ripening process. A transgenic approach was used for functional characterization of the EgCBF3, using tomato as the model plant. The effects of ectopic expression of EgCBF3 were analyzed based on expression profiling of the ethylene biosynthesis-related genes, anti-freeze proteins (AFPs), abiotic stress tolerance and plant growth and development. The EgCBF3 tomatoes demonstrated altered phenotypes compared to the wild type tomatoes. Delayed leaf senescence and flowering, increased chlorophyll content and abnormal flowering were the consequences of overexpression of EgCBF3 in the transgenic tomatoes. The EgCBF3 tomatoes demonstrated enhanced abiotic stress tolerance under in vitro conditions. Further, transcript levels of ethylene biosynthesis-related genes, including three SlACSs and two SlACOs, were altered in the transgenic plants' leaves and roots compared to that in the wild type tomato plant. Among the eight AFPs studied in the wounded leaves of the EgCBF3 tomato plants, transcript levels of SlOSM-L, SlNP24, SlPR5L and SlTSRF1 decreased, while expression of the other four, SlCHI3, SlPR1, SlPR-P2 and SlLAP2, were up-regulated. These findings indicate the possible functions of EgCBF3 in plant growth and development as a regulator of ethylene biosynthesis-related and AFP genes, and as a stimulator of abiotic stress tolerance.
Climate change exposes vegetation to unusual levels of drought, risking a decline in productivity and an increase in mortality. It still remains unclear how trees and forests respond to such unusual drought, particularly Southeast Asian tropical rain forests. To understand leaf ecophysiological responses of tropical rain forest trees to soil drying, a rainfall exclusion experiment was conducted on mature canopy trees of Dryobalanops aromatica Gaertn.f. (Dipterocarpaceae) for 4 months in an aseasonal tropical rain forest in Sarawak, Malaysia. The rainfall was intercepted by using a soft vinyl chloride sheet. We compared the three control and three treatment trees with respect to leaf water use at the top of the crown, including stomatal conductance (gsmax), photosynthesis (Amax), leaf water potential (predawn: Ψpre; midday: Ψmid), leaf water potential at turgor loss point (πtlp), osmotic potential at full turgor (π100) and a bulk modulus of elasticity (ε). Measurements were taken using tree-tower and canopy-crane systems. During the experiment, the treatment trees suffered drought stress without evidence of canopy dieback in comparison with the control trees; e.g., Ψpre and Ψmid decreased with soil drying. Minimum values of Ψmid in the treatment trees decreased during the experiment, and were lower than πtlp in the control trees. However, the treatment trees also decreased their πtlp by osmotic adjustment, and the values were lower than the minimum values of their Ψmid. In addition, the treatment trees maintained gs and Amax especially in the morning, though at midday, values decreased to half those of the control trees. Decreasing leaf water potential by osmotic adjustment to maintain gs and Amax under soil drying in treatment trees was considered to represent anisohydric behavior. These results suggest that D. aromatica may have high leaf adaptability to drought by regulating leaf water consumption and maintaining turgor pressure to improve its leaf water relations.
This study was carried out to evaluate the genetic effect of quantitative trait loci (QTLs) conferring drought tolerance in wheat. A population of 120 F(2) individuals from the cross between the drought-tolerant S-78-11 and drought-sensitive Tajan cultivars were analyzed for their segregation under drought stress conditions. The relative water content under drought stress conditions exhibited continuous variation, indicating the minor gene effects on the trait. Single-marker analysis (SMA) was carried out to detect the main QTL association with drought tolerance. The SMA results revealed that the simple sequence repeat markers GWM182 and GWM292 on chromosome 5D and GWM410 on chromosome 5A exhibited significant association with drought tolerance, accounting for 30, 22, and 21% of the total variation, respectively. The 3 genetic loci, especially GWM182, can be used in marker-assisted selection methods in drought tolerance breeding in wheat.
Rice is an important grain that is the staple food for most of the world's population. Drought is one of the major stresses that negatively affects rice yield. The nature of drought tolerance in rice is complex as it is determined by various components and has low heritability. Therefore, to ensure success in breeding programs for drought tolerant rice, QTLs (quantitative trait loci) of interest must be stable in a variety of plant genotypes and environments. This study identified stable QTLs in rice chromosomes in a variety of backgrounds and environments and conducted a meta-QTL analysis of stable QTLs that have been reported by previous research for use in breeding programs. A total of 653 QTLs for drought tolerance in rice from 27 genetic maps were recorded for analysis. The QTLs recorded were related to 13 traits in rice that respond to drought. Through the use of BioMercartor V4.2, a consensus map containing QTLs and molecular markers were generated using 27 genetic maps that were extracted from the previous 20 studies and meta-QTL analysis was conducted on the consensus map. A total of 70 MQTLs were identified and a total of 453 QTLs were mapped into the meta-QTL areas. Five meta-QTLs from chromosome 1 (MQTL 1.5 and MQTL 1.6), chromosome 2 (MQTL2.1 and MQTL 2.2) and chromosome 3 (MQTL 3.1) were selected for functional annotation as these regions have high number of QTLs and include many traits in rice that respond to drought. A number of genes in MQTL1.5 (268 genes), MQTL1.6 (640 genes), MQTL 2.1 (319 genes), MQTL 2.2 (19 genes) and MQTL 3.1 (787 genes) were annotated through Blast2GO. Few major proteins that respond to drought stress were identified in the meta-QTL areas which are Abscisic Acid-Insensitive Protein 5 (ABI5), the G-box binding factor 4 (GBF4), protein kinase PINOID (PID), histidine kinase 2 (AHK2), protein related to autophagy 18A (ATG18A), mitochondrial transcription termination factor (MTERF), aquaporin PIP 1-2, protein detoxification 48 (DTX48) and inositol-tetrakisphosphate 1-kinase 2 (ITPK2). These proteins are regulatory proteins involved in the regulation of signal transduction and gene expression that respond to drought stress. The meta-QTLs derived from this study and the genes that have been identified can be used effectively in molecular breeding and in genetic engineering for drought resistance/tolerance in rice.
A cross between IR64 (high-yielding but drought-susceptible) and Aday Sel (drought-tolerant) rice cultivars yielded a stable line with enhanced grain yield under drought screening field trials at International Rice Research Institute. The major effect qDTY4.1 drought tolerance and yield QTL was detected in the IR77298-14-1-2-10 Backcrossed Inbred Line (BIL) and its IR87705-7-15-B Near Isogenic Line (NIL) with 93.9% genetic similarity to IR64. Although rice yield is extremely susceptible to water stress at reproductive stage, currently, there is only one report on the detection of drought-responsive microRNAs in inflorescence tissue of a Japonica rice line. In this study, more drought-responsive microRNAs were identified in the inflorescence tissues of IR64, IR77298-14-1-2-10 and IR87705-7-15-B via next-generation sequencing. Among the 32 families of inflorescence-specific non-conserved microRNAs that were identified, 22 families were up-regulated in IR87705-7-15-B. Overall 9 conserved and 34 non-conserved microRNA families were found as drought-responsive in rice inflorescence with 5 conserved and 30 non-conserved families induced in the IR87705-7-15-B. The observation of more drought-responsive non-conserved microRNAs may imply their prominence over conserved microRNAs in drought response mechanisms of rice inflorescence. Gene Ontology annotation analysis on the target genes of drought-responsive microRNAs identified in IR87705-7-15-B revealed over-representation of biological processes including development, signalling and response to stimulus. Particularly, four inflorescence-specific microRNAs viz. osa-miR5485, osa-miR5487, osa-miR5492 and osa-miR5517, and two non-inflorescence specific microRNAs viz. osa-miR169d and osa-miR169f.2 target genes that are involved in flower or embryonic development. Among them, osa-miR169d, osa-miR5492 and osa-miR5517 are related to flowering time control. It is also worth mentioning that osa-miR2118 and osa-miR2275, which are implicated in the biosynthesis of rice inflorescence-specific small interfering RNAs, were induced in IR87705-7-15-B but repressed in IR77298-14-1-2-10. Further, gene search within qDTY4.1 QTL region had identified multiple copies of NBS-LRR resistance genes (potential target of osa-miR2118), subtilisins and genes implicated in stomatal movement, ABA metabolism and cuticular wax biosynthesis.
Never in the history of modern Malaysia, the general population at all levels are being threatened by food security. Food becoming less available and more expensive. Many factors, both long- and short-term, have contributed to the shortage. At a global level, available data seems to indicate that we have been consuming more than what we produce. Then came the shortfall in global rice production caused by the impact of climate change such as the widespread drought in India and China in 2002, typhoons in the Philippines in 2006, and the major flooding in Bangladesh in 2007. This was followed by the returns of pests such as planthoppers, and the various virus diseases transmitted particularly at regions with growing seasons having abnormally higher temperatures caused by climate change. Since the crisis started, scientists particularly breeders all over the world were requested to strengthen and upgrade the breeding program and facilities for the development of new varieties with increased tolerance to drought, flooding, and salinity as well resistant to insects and diseases. An important pre-requisite for such activities is the free flow of plant genetic resources for food and agriculture (pgrfa). The adoption of the Convention on Biological Diversity (CBD) has drastically slowed down the movement of many plant genetic resources and this has threatened the future supply of food. The International Treaty on Plant Genetic Resource for Food and Agriculture (ITPGRFA or the Treaty) is a global reaction to the rising tide of measures taken by many governments as a result CBD to extend their sovereign control over genetic resources. Many countries felt that those measures are inappropriate for food and agricultural crop genetic resources. The Treaty on the other hand recognizes that access and benefit sharing for agricultural biodiversity must be treated differently from the way it is generally treated under CBD. This paper discusses some of the key points and provisions from the treaty and some issues arising from its negotiation and future implementation in Malaysia.
Over the last century, the earth’s climate has changed. It is a serious global, long-term problem which involves complex interactions. A lot of evidence suggests that most of the observed factors contributing to the crisis over the last 50 years can be attributed to human activities. Malaysia has always been vulnerable to extreme climatic events such as typhoons, floods and drought. We expect climate change to exacerbate these vulnerabilities. To ensure, that our water resources will always be secure and ready for use. We need to create awareness in the public and the policy makers so that they will acknowledge that the climate change issue is real. They also need to accept that actions to adapt with our vulnerabilities should be immediately put in place. We can do this by integrating the various sector policies and securing the participation of all stakeholders in Malaysia and other countries.