The Economic Impacts of Climate Change on the Rice Production in Malaysia

Mode of gene action and heterosis for physiological, biochemical, and agronomic traits in some diverse rice genotypes under normal and drought conditions

Water scarcity is a crucial environmental stress that constrains rice growth and production. Thus, breeding for developing high-yielding and drought-tolerant rice genotypes is decisive in sustaining rice production and ensuring global food security, particularly under stress conditions. To this end, this study was conducted to evaluate the effects of water deficit on 31 genotypes of rice (seven lines, viz., Puebla, Hispagran, IET1444, WAB1573, Giza177, Sakha101, and Sakha105, and three testers, viz., Sakha106, Sakha107, and Sakha108) and their 21 crosses produced by line × tester mating design under normal and water deficit conditions; this was to estimate the combining ability, heterosis, and gene action for some traits of physiological, biochemical, and yield components. This study was performed during the summer seasons of 2017 and 2018. The results showed that water deficit significantly decreased relative water content, total chlorophyll content, grain yield, and several yield attributes. However, osmolyte (proline) content and antioxidant enzyme activities (CAT and APX) were significantly increased compared with the control condition. Significant mean squares were recorded for the genotypes and their partitions under control and stress conditions, except for total chlorophyll under normal irrigation. Significant differences were also detected among the lines, testers, and line × tester for all the studied traits under both irrigation conditions. The value of the σ²GCA variance was less than the value of the σ²SCA variance for all the studied traits. In addition, the dominance genetic variance (σ²D) was greater than the additive genetic variance (σ²A) in controlling the inheritance of all the studied traits under both irrigation conditions; this reveals that the non-additive gene effects played a significant role in the genetic expression of the studied traits. The two parental genotypes (Puebla and Hispagran) were identified as good combiners for most physiological and biochemical traits, earliness, shortness, grain yield, and 1,000-grains weight traits. Additionally, the cross combinations Puebla × Sakha107, Hispagran × Sakha108, and Giza177 × Sakha107 were the most promising. These results demonstrated the substantial and desirable specific combining ability effects on all the studied traits, which suggested that it could be considered for use in rice hybrid breeding programs.

Modelling nitrogen management in hybrid rice for coastal ecosystem of West Bengal, India

Hybrid rice requires adequate nitrogen (N) management in order to achieve good yields from its vegetative and reproductive development. With this backdrop, a field experiment was conducted at Regional Research Station (Coastal Saline Zone), Bidhan Chandra Krishi Viswavidyalaya, Kakdwip, West Bengal (India) to record growth and yield performance of hybrid rice (cv. PAN 2423) under varied N-fertilizer doses. A modelling approach was adopted for the first time in hybrid rice production system under coastal ecosystem of West Bengal (India). In the present study, the Agricultural Production Systems Simulator (APSIM) model was calibrated and validated for simulating a hybrid rice production system with different N rates. The APSIM based crop simulation model was found to capture the physiological changes of hybrid rice under varied N rates effectively. While studying the relationship between simulated and observed yield data, we observed that the equations developed by APSIM were significant with higher R² values (≥0.812). However, APSIM caused an over-estimation for calibrate data but it was rectified for validated data. The RMSE of models for all the cases was less than respective SD values and the normalized RMSE values were ≤20%. Hence, it was proved to be a good rationalized modelling and the performance of APSIM was robust. On the contrary, APSIM underestimated the calibrated amount of N (kg ha^-1) in storage organ of hybrid rice, which was later rectified in case of validated data. A strong correlation existed between the observed and APSIM-simulated amounts of N in storage organ of hybrid rice (R² = 0.94** and 0.96** for the calibration and validation data sets, respectively), which indicates the robustness of the APSIM simulation study. Scenario analysis also suggests that the optimal N rate will increase from 160 to 200 kg N ha^-1 for the greatest hybrid rice production in coming years under elevated CO₂ levels in the atmosphere. The APSIM-Oryza crop model had successfully predicted the variation in aboveground biomass and grain yield of hybrid rice under different climatic conditions.

Rice Growth Performance, Nutrient Use Efficiency and Changes in Soil Properties Influenced by Biochar under Alternate Wetting and Drying Irrigation

Water-saving irrigation occasionally causes an inconsequential yield loss in rice; thereby, biochar incorporation in this context has great scope due to its properties, including the release of nutrients and improving soil physicochemical properties. An experiment was conducted to investigate the effect of biochar combined with fertilizer on physiological response, water and nutrient efficiency of rice and changes in biochemical properties of soil under AWD (alternate wetting and drying) irrigation system. Two types of irrigation practice, such as AWD and CF (continuous flooding), and four types of fertilizer combination, namely T1: 25% Rice husk biochar (RHB) + 75% of recommended fertilizer dose (RFD); T2: 25% oil palm empty fruit bunch biochar (EFBB) + 75% of RFD; T3: 100% RFD; and T0: 0% biochar and fertilizer, were assigned to assess their impacts. The AWD irrigation produced a sharply reduced grain yield (210.58 g pot−1) compared to CF irrigation (218.04 g pot−1), whereas the biochar combination treatments T1 and T2 produced greater yields (260.27 and 252.12 g pot−1, respectively), which were up to 12.5% higher than RFD. Within AWD, irrigation water usage by T1 and T2 (98.50 and 102.37 g L−1, respectively) was profoundly reduced by up to 28.8%, with improved water use efficiency (WUE). The main effect of biochar treatment T1 and T2 also increased photosynthesis rate during vegetative and maturing stage (up to 17.6 and 24.4%, respectively), in addition to boosting agronomic efficiency of nitrogen (N), phosphorous (P) and potassium (K) compared to RFD (T3). Nevertheless, T1 and T2 significantly enhanced the total carbon and nitrogen; dehydrogenase and urease enzyme activities also increased in both irrigation regimes. The results reveal that the integrated application of RHB and EFBB with fertilizer in the AWD regime significantly reduces irrigation water usage and improves nutrient use efficiency, WUE and soil biochemical properties with a minimum yield penalty for rice.

Climate change in Malaysia: Trends, contributors, impacts, mitigation and adaptations

PURPOSE

This paper reviews the past and future trends of climate change in Malaysia, the major contributors of greenhouse gases and the impacts of climate change to Malaysia. It also reviews the mitigation and adaptations undertaken, and future strategies to manage the impacts of regional climate change.

METHODOLOGY

The review encompasses historical climate data comprising mean daily temperature, precipitation, mean sea level and occurrences of extreme weather events. Future climate projections have also been reviewed in addition to scholarly papers and news articles related to impacts, contributors, mitigation and adaptations in relation to climate change.

FINDINGS

The review shows that annual mean temperature, occurrences of extreme weather events and mean sea level are rising while rainfall shows variability. Future projections point to continuous rise of temperature and mean sea level till the end of the 21st century, highly variable rainfall and increased frequency of extreme weather events. Climate change impacts particularly on agriculture, forestry, biodiversity, water resources, coastal and marine resources, public health and energy. The energy and waste management sectors are the major contributors to climate change. Mitigation of and adaptations to climate change in Malaysia revolve around policy setting, enactment of laws, formulation and implementation of plans and programmes, as well as global and regional collaborations, particularly for energy, water resources, agriculture and biodiversity. There are apparent shortcomings in continuous improvement and monitoring of the programmes as well as enforcement of the relevant laws.

ORIGINALITY/VALUE

This paper presents a comprehensive review of the major themes of climate change in Malaysia and recommends pertinent ways forward to fill the gaps of mitigation and adaptations already implemented.

Modeling salinity effect on rice growth and grain yield with ORYZA v3 and APSIM-Oryza

Development and testing of reliable tools for simulating rice production in salt-affected areas are presented in this paper. New functions were implemented in existing crop models ORYZA v3 and the cropping systems modelling framework APSIM. Field experiments covering two years, two different sites, and three varieties were used to validate both improved models. We used the salt balance module in the systems model APSIM to simulate the observed daily soil salinity with acceptable accuracy (RMSEn <35%), whereas ORYZA v3 used measured soil salinity at a given interval of days as a model input. Both models presented similarly good accuracy in simulating aboveground biomass, leaf area index, and grain yield for IR64 over a gradient of salinity conditions. The model index of agreement ranged from 0.86 to 0.99. Variability of yield under stressed and non-stressed conditions was simulated with a RMSE, of 191 kg ha^-1 and 222 kg ha^-1 _, respectively, for ORYZA v3 and APSIM-Oryza, corresponding to an RMSE_n of 14.8% and 17.3%. These values are within the bounds of experimental error, therefore indicating acceptable model performance. The model test simulating genotypic variability of rice crop responses resulted in similar levels of acceptable model performance with RMSE_n ranging from 11.3 to 39.9% for observed total above ground biomass for IR64 and panicle biomass for IR29, respectively. With the improved models, more reliable tools are now available for use in risk assessment and evaluation of suitable management options for rice production in salt-affected areas. The approach presented may also be applied in improving other non-rice crop models to integrate a response to soil salinity - particularly in process-based models which capture stage-related stress tolerance variability and resource use efficiency.

Canopy Light Utilization and Yield of Rice under Rain-Catching and Controlled Irrigation

In the middle and lower reaches of the Yangtze River, the rainfall is greater in summer. The technology of rain catching and controlled irrigation of rice help to save water by raising the water depth of the field after rain while the soil water content during the rest period is maintained at 70–100% of field capacity. The objectives of this study were to evaluate rice growth, canopy light utilization, and yield of rice under different rain-catching and controlled irrigation modes (T1: light drought and low storage, T2: light drought and high storage), and to find the optimal storage depth after rain for rice. Measurements included the rice plant height, tiller number, high tiller growth, leaf angle, canopy interception rate, and yield shape. The plot experiment was conducted in 2012 and 2013 using Nanjing 44 (Oryza sativa L.) as the test material. The results showed that T1 treatment improved the height of rice plants and the number of effective tillers in the late growth stage. The number of high tillers had a great influence on the total leaf dry quality; compared with conventional irrigation (CK), the number of high tillers increased by 11.36% and 7.87% in T1 and T2, respectively; the canopy interception rate of T1 above 0 cm was higher than that in T2 and CK; and the leaf area index (LAI) was closely related to the 0–40 cm of canopy light distribution. The number of grains per panicle in T1 was lower than in CK and T2; however, the number of grains in T1 was less, and the 1000 grain weight was higher. On the 63 days and 83 days after transplanting in 2012 and 78 days after transplanting in 2013, the first, second, and third leaf angles of T1 were larger. Rain-catching and controlled irrigation can increase the dry weight and shoot dry weight of rice, and light drought and low storage (T1) conditions are good for maintaining a high yield because of more tiller number, more grains per panicle and reasonable light distribution.

From ORYZA2000 to ORYZA (v3): An improved simulation model for rice in drought and nitrogen-deficient environments

The worldwide usage of and increasing citations for ORYZA2000 has established it as a robust and reliable ecophysiological model for predicting the growth and yield of rice in an irrigated lowland ecosystem. Because of its focus on irrigated lowlands, its computation ability is limited to the representation of the effects of the highly dynamic environments of upland, rainfed, and aerobic ecosystems on rice growth and yield. Additional modules and routines to quantify daily variations in soil temperature, carbon, nitrogen, and environmental stresses were then developed and integrated into ORYZA2000 to capture their effects on primary production, assimilate allocation, root growth, and water and nitrogen uptake. The newest version has been renamed "ORYZA version 3 (v3)". Case studies have shown that the root mean square errors (RMSE) between simulated and measured values for total biomass and yields ranged from 11.2% to 16.6% across experiments in non-drought and drought and/or nitrogen-deficient environments. ORYZA (v3) showed a significant reduction of the RMSE by at least 20%, thereby improving the model's capability to represent values measured under extreme conditions. It has also been significantly improved in representing the dynamics of soil water and crop leaf nitrogen contents. With an enhanced capability to simulate rice growth and development and predict yield in non-stressed, water-stressed and nitrogen-stressed environments, ORYZA (v3) is a reliable successor of ORYZA2000.