Rice-producing Regions Research Articles

Application of deep learning for rice leaf disease detection in the Mekong Delta

The Mekong River Delta, the largest rice-producing region in Vietnam with an annual output of over 25 million tons, plays a vital role in ensuring food security both within the country and globally. In recent years, it has undergone significant transformation in rice cultivation, which aims to support farmers here to plant rice more effectively. However, severe weather conditions and soil degradation have negatively impacted rice growth. Additionally, rice is highly susceptible to various diseases that must be identified and prevented promptly. As a result, leveraging technology such as AI and deep learning to diagnose rice diseases based on leaf symptoms is essential. This paper utilizes an image dataset of three common rice leaf diseases—leaf smut, brown spot, and bacterial leaf blight—and applies deep learning networks (MobileNet and ResNet) to evaluate and select the best model. A diagnostic program is then developed to detect these diseases. Experimental results show that the MobileNetV3-Small model (a variant of the MobileNet network) is the most optimal, offering fast training time, high accuracy, and acceptable levels of loss and error.

The effect of the Fitostemin-WP® biostimulator on yield and quality characteristics of rice (Oryza sativa L.)

In order to avoid yield and quality reduction of rice, it is essential to provide nutrition rice plants require. Therefore, a field experiment was conducted at the research area of the Institute of Agriculture - Skopje, Department of Field Crops, Ss. Cyril and Methodius University in Skopje, Republic of Macedonia, in Kochani, a rice production region. The experiment was set up to determine the effects of the Fitostemin-WP® biostimulator on some yield and quality properties of an Italian rice variety Opale during the vegetative seasons in 2020 and 2021. Standard agrotechnical methods for crop production were applied. Fitostemin-WP® is an herbal product in the form of powder and it consists of herbal extracts and minerals. It is used for increasing crop yield. The field experiment was arranged in a Zade method with a Fitostemin-WP® treatment and a control one in 3 replications. Only basic fertilizers (350kg/ha NPK and 200kg/ha Urea (46% N)) were applied on the control plot, while the treatment plot, besides basic fertilization, was also treated with Fitostemin-WP® with 100 g/ha dosage once during the vegetation period (tillering stage). The following parameters were examined in this study, namely the biological, grain and straw yield, the number of productive tillers/m2, panicle weight, and milling fractions. Results were analyzed with the ANOVA and LSD test. According to the results from this study, statistically significant differences were not found in these two years of field experiments for the examined parameters. However, the values for the brokens have shown some significant differences between the years, but not between the treatment and the control. This can result from the environmental impact during the vegetative period. More frequent usage of Fitostemin-WP® during the vegetation period of the rice plant may show more significant results.

Geographical Distribution and Abundance of Species of the Pycreus Genus in Rice Production Regions in Rio Grande do Sul

Theoretical Reference: Identifying, tracking, and analyzing weed infestation levels in rice crops are essential for developing more effective control strategies, ultimately enhancing efficiency, reducing costs, and minimizing environmental impact. This study focuses on the geographic distribution and abundance of species within the Pycreus genus (family Cyperaceae) in rice fields in Rio Grande do Sul (RS), Brazil. Method: During the 2005/06 growing season, collections and abundance assessments of Pycreus species were conducted across three irrigated rice fields located in three municipalities within five major rice production regions of RS. Plants were collected during vegetative or reproductive stages, dried, and identified using specialized literature. Specimens were then deposited as vouchers in the PEL Herbarium at the Department of Botany, Federal University of Pelotas. Results and Conclusion: The study revealed the presence of Pycreus species in rice fields across RS, with P. polystachyos (Rottb.) P. Beauv. being the most abundant and frequently observed species. P. macrostachyos (Lam.) J. Raynal and P. lanceolatus (Poir.) C.B. Clarke were also identified, though less commonly. The highest abundance of Pycreus species was recorded in the coastal physiographic region, particularly within the Internal Coastal Plain of Lagoa dos Patos and southern rice production areas. Implications of Research: These findings emphasize the need for targeted weed management strategies in rice cultivation, particularly in regions where Pycreus species are most prevalent, to enhance crop productivity and sustainability. Originality/Value: This study provides valuable insights into the distribution and abundance of Pycreus species in RS rice fields, contributing to the understanding of weed dynamics in rice production and offering a basis for the development of more effective control measures.

Tracking paddy rice acreage, flooding impacts, and mitigations during El Niño flooding events using Sentinel-1/2 imagery and cloud computing

The frequent occurrence of El Niño events, in the context of climate change, brings heavy precipitation and extreme heat, severely disrupting agricultural production. Previous efforts have focused on monitoring crop planting areas and evaluating affected crops during disasters. Nevertheless, a comprehensive analysis, including crop planting area mapping, crop damage assessment, and mitigation effectiveness throughout the entire course of a disaster, has been seldom addressed. In this study, we built a comprehensive framework to rapidly investigate the areas of early rice, the extent of flooding impacts, and the post-flood mitigations of early rice during the El Niño flooding event in a typical rice production region – Jiangxi Province in 2023. Early rice planting areas were first mapped by integrating 15-day time series gap-filled Sentinel-1/2 datasets using the Google Earth Engine (GEE) platform, based on a random forest classifier built with the 55 optimized training features. Then the flood-affected early rice map was produced by integrating the early rice planting areas and the Sentinel-1 images-based flood map. Finally, the post-flood newly planted rice fields were identified using the random forest algorithm and classification features from the Sentinel-1/2 images composited during four phenology phases of newly planted rice. The results showed the early rice planting area map, the flooding map, and the newly planted early rice map have overall accuracies of over 90 %. The early rice planting areas reached 120 × 104 ha, and an area of 3.60 × 104 ha (3 %) was flooded due to the heavy rain, and 3.43 × 104 ha flooded areas were newly planted, eventually mitigating the flooding impacts on the production of early rice. This study showcases the potential of all the available Sentinel-1/2 data, cloud computing, and well-established mapping algorithms for tracking rice areas, flooding impacts, and mitigations (i.e., after-flooding replanting) during extreme climate events. The established framework is expected to serve as an early warning system for agricultural adaptation to extreme climate events.

Improved Paddy Rice Classification Utilizing Sentinel-1/2 Imagery in Anhui China: Phenological Features, Algorithms, Validation and Analysis

Enhancing the accuracy of paddy rice mapping is crucial for bolstering global food security. Prior research incorporating Sentinel imagery with phenological characteristics has identified paddy rice fields effectively. However, challenges such as reliance on a single index, cloud cover interference, and a lack of sufficient training samples continue to complicate the mapping of paddy rice. This study introduces a comprehensive paddy rice mapping framework that incorporates annual phenological features throughout the entire growth phase. This was achieved by expanding the sample size through the extraction of phenological features, and the visually verified samples were then integrated with distinct phenological phases and relevant indices, utilizing hybrid Sentinel-1/2 imagery to map paddy rice distribution. The accuracy of the generated rice map was validated against trusted samples, corroborative agricultural statistics, and another high-resolution 10 m mapping product. Compared with ground-truth samples, the algorithm has achieved an overall accuracy of approximately 92% in most rice production regions with a confusion matrix. Additionally, the estimated rice area in Anhui and several other rice-producing regions shows less than 10% error when compared with governmental statistical records from the yearbook. When compared with another recent paddy rice map at the same spatial resolution (10 m), our approach provided cleaner details and more effectively reduced omission errors. It received values of R2 = 0.991 and slope = 1.08 in a prefecture-level statistical comparison with a counterpart. Our proposed approach is proven to be valid and is expected to offer significant benefits to agricultural sustainability and technological applications in farming.

Microbiome Analysis Revealed the Effects of Environmental Factors on the Presence of Toxigenic Fungi and Toxin Production in Rice Grains

Fungal contamination in rice and mycotoxins present significant challenges to both rice quality and food safety. However, there is a dearth of comprehensive research on the compositional and structural changes within fungal colonies in rice, particularly in typical rice-producing regions, as well as their underlying influencing factors. In this study, a comprehensive analysis of fungal taxa in rice grains was conducted using amplicon sequencing and bioinformatics methods on 99 rice samples collected in three major rice-producing regions in China: Northeast Plain (NP), Yangtze River Basin (YR), and Southeast Coastal Area (SC). A total of 6,019,722 fungal ITS sequences were obtained with an average sequence length of 235 base pairs, and effective ASVs (2014) accounted for approximately 97.58% of the total ASVs (2064). The fungal community diversity in rice grains exhibited significant variations across the three regions, with deterministic processes playing a predominant role in shaping the ecological dynamics of fungal taxa. Among the core microbiota (92 shared ASVs), the first five species (Alternaria, Fusarium, Curvularia, Epicoccum, and Ustilaginoidea) accounting for a proportion greater than 5% had been reported as potential pathogens for plants. Geographical variations in fungal community composition were evident, with a significantly higher number of shared populations observed between YR and CS regions compared to those in the NP region. Nutrient elements and climatic conditions were the internal and external driving factors of rice fungal community composition. Additionally, notable regional variations in fungal functionality were observed. The findings have significant implications for gaining a comprehensive understanding of the distribution patterns of fungal communities in the major rice-producing regions in China. Additionally, it provides valuable insights into controlling key influencing factors to effectively reduce the occurrence of toxin-producing fungi and mitigate the associated risks related to mycotoxin contamination, thereby contributing to improved risk management and assessment.

Determining arsenic stress tolerance genes in rice (Oryza sativa L.) via genomic insights and QTL mapping with double haploid lines

Arsenic, a hazardous heavy metal with potent carcinogenic properties, significantly affects key rice-producing regions worldwide. In this study, we present a quantitative trait locus (QTL) mapping investigation designed to identify candidate genes responsible for conferring tolerance to arsenic toxicity in rice (Oryza sativa L.) during the seedling stage. This study identified 17 QTLs on different chromosomes, including qCHC-1 and qCHC-3 on chromosome 1 and 3 related to chlorophyll content and qRFW-12 on chromosome 12 related to root fresh weight. Gene expression analysis revealed eight candidate genes exhibited significant upregulation in the resistant lines, OsGRL1, OsDjB1, OsZIP2, OsMATE12, OsTRX29, OsMADS33, OsABCG29, and OsENODL24. These genes display sequence alignment and phylogenetic tree similarities with other species and engaging in protein-protein interactions with significant proteins. Advanced gene-editing techniques such as CRISPR-Cas9 to precisely target and modify the candidate genes responsible for arsenic tolerance will be explore. This approach may expedite the development of arsenic-resistant rice cultivars, which are essential for ensuring food security in regions affected by arsenic-contaminated soil and water.

Influence of soil properties on selenium concentration in paddy soil and rice grains in the hilly regions of southern China

BackgroundSelenium (Se) is essential for human health and is predominantly obtained from dietary sources, particularly rice in Hunan Province, a significant rice-producing region in southern China. Investigating the relationship between Se levels in paddy soil and rice grains, along with the associated influencing factors, is critical for enhancing Se-enriched food security.ResultsAnalysis of 128,992 samples collected between 2019 and 2022 revealed that the soil Se concentration in Hunan exceeded the global average, with rice grains showing promising potential for Se enrichment. Various analytical methods, including statistical analyses, co-occurrence networks, and correlation heatmaps, were utilized to scrutinize the extensive dataset. Additionally, partial least squares path analysis elucidated the interactive effects of influencing factors on soil Se concentration, rice grain Se concentration, and Se bioconcentration factor (BCF). Soil parent materials significantly affected soil Se concentration, rice grain Se concentration, and Se BCF (p < 0.01). Factors such as soil cation exchange capacity, soil organic matter, slope, and soil concentrations of Cu, Mn, and Zn demonstrated positive correlations with soil Se concentration. Similarly, these factors exhibited positive associations with rice grain Se concentration. Conversely, negative correlations were observed between certain factors and Se BCF. As a result, predictive models were developed for soil Se, rice grain Se concentration, and Se BCF.ConclusionsThis study contributes valuable insights to inform policy-making for Se-enriched food production and to ensure regional nutritional equilibrium. Caution is recommended in areas with excessive Se levels to prevent potential poisoning risks.

Policy Constructivity and Food Security Strategies: Vulnerability Issues of Rice in Kota Belud, Sabah

The recent escalation in imported rice prices, coupled with a domestic shortfall in rice production, has significantly impacted Malaysian residents, particularly affecting the economically vulnerable B40 group which constitutes a substantial portion of the population. This scenario has contributed to a consistent increase in the cost of food items. Concurrently, the domestic scarcity of white rice is attributed to heightened demand triggered by the inflated prices of imported rice. Despite Malaysia’s 130,282 hectares dedicated to rice cultivation contributing to 40% of its total rice production, with Kota Belud, Sabah being one of the most prolific rice-producing regions spanning 7,092 hectares, the country still faces a critical vulnerability in rice and paddy supply. Notable, the area under rice cultivation in Kota Belud expanded by 1000 hectares to 9392 hectares in under three years, as of 2019. This paradox raises questions about the sufficiency of national rice supply amidst such expansion. This study aims to dissect the multifaceted factors contributing to rice supply shortages, focusing on stakeholder engagement, selection processes, and their leverage in policy-making. These elements critically affect policy space choices, alongside the feasibility and effectiveness of policy interventions. Employing qualitative methodologies, the research integrates structured interviews with key informants and the analysis of secondary data for empirical backing. Furthermore, to enrich the study's findings, questionnaires are distributed to 100 villagers in a qualitative exploration aiming for a comprehensive understanding of the issue. Preliminary findings underscore the necessity of prioritizing food security at the national level. To enhance food security concerns in Sabah and across Malaysia, the study suggests engaging the youth, enhancing road networks, developing adequate drainage and irrigation systems, and promoting a balanced cultivation of commercial and paddy crops, among other strategic interventions. These approaches are pivotal in navigating the complexities of food security and establishing a resilient rice supply chain.

Metabolomics analysis of the effects of chelerythrine on Ustilaginoidea virens.

Rice false smut (RFS) caused by Ustilaginoidea virens is widely distributed in major rice-producing regions. Previous studies have shown that treating RFS with chelerythrine can decrease the germination of fungus spores by 86.7% and induce fungal cell apoptosis. In the present study, the effects of chelerythrine on the metabolism of U. virens explored using metabolomics and analyses of differentially accumulated metabolites and altered metabolic pathways. The top 15 metabolites in random forest analysis were significantly different between groups. In positive ion mode, purine, phenylalanine metabolism, phenylalanine, tyrosine, tryptophan biosynthesis, pyrimidine metabolism, and nitrogen metabolism were dominant. Alanine, aspartate, glutamate metabolism, and phenylalanine metabolism were enriched in negative ion mode. Differentially expressed genes and altered metabolic pathways of U. virens were effected by chelerythrine. The findings support future research on the prevention and treatment of RFS by chelerythrine and provide a theoretical basis for targeted drug delivery.

Herbicide Strategies for Weed Control in Rice Cultivation: Current Practices and Future Directions

Rice, as a staple food for more than half of the world's population, plays a crucial role in global food security. However, weed competition poses a significant challenge to rice cultivation, affecting yield and quality. To address this challenge, rice farmers have increasingly turned to chemical herbicides as a cost-effective alternative to labor-intensive manual weeding. This review paper explores the current practices and future directions in herbicide strategies for weed control in rice cultivation, with a specific focus on diverse approaches adopted in various agro-ecological regions, particularly in Pakistan. The paper begins by highlighting the importance of rice cultivation in global agriculture and the economic significance of the crop, emphasizing the need for effective weed management to ensure sustainable production. It discusses the impact of labor shortages and rising labor costs on weed control practices, driving the adoption of chemical herbicides, especially in direct-seeded rice cultivation. Additionally, the review underscores the importance of integrated weed management systems, which combine cultural practices, targeted herbicide applications, and legislative measures to optimize crop productivity while minimizing environmental impact. Furthermore, the paper evaluates the efficacy of different herbicides and their timing of application in managing weeds and maximizing rice yield. It synthesizes findings from recent studies to provide insights into the effectiveness of pre-emergence and post-emergence herbicides, as well as their impact on weed-crop competition and overall crop health. By analyzing the strengths and limitations of existing herbicide strategies, the review identifies opportunities for innovation and improvement in weed management practices. Overall, this review paper offers a comprehensive overview of herbicide strategies for weed control in rice cultivation, highlighting the need for sustainable and integrated approaches to address weed challenges while ensuring food security and environmental sustainability in rice-producing regions.

Analysis on Farmers' Decision-Making Processes Regarding Sustainable Agricultural Practices: A Case Study in Kademangan, Pagelaran, Malang, Indonesia

Pagelaran, located in Malang, is among the seven key rice-producing regions, encompassing an agricultural expanse of 2,592 hectares. Despite this, a notable scarcity persists in the adoption of sustainable agricultural practices among local farmers, such as the utilization of organic fertilizers and integrated pest and disease management within their agricultural enterprises. The investigation centered on Kademangan, Pagelaran, Malang, Indonesia. Employing a purposive sampling approach, the study engaged 66 respondents. Data synthesis encompassed primary and secondary sources. Methodologies encompassed descriptive analysis, Structural Equation Model (SEM), and Analytical Hierarchy Process (AHP). Outcomes underscored the significant impact of innovation characteristics on farmers' attitudes, intentions, and decisions. Additionally, attitudes and moral norms emerged as influential determinants of farmers' intentions and decisions. Perceived behavioral control and intentions were pivotal in shaping farmers' decisions. Notably, strategies aimed at enhancing farmer capacity pertaining to sustainable agriculture emerged as paramount in augmenting its implementation, as per the study's findings.

Optimizing the role of rice central market in Java, Indonesia: the effect of toll roads construction to the rice market integration

Rice is considered as the primary staple food that Indonesian people mostly consume on daily basis. The need of rice in Indonesia is always increasing. However, the production of rice in Indonesia has not meet its demand. One of the factors resulting the number of paddy field decreasing is the construction of toll roads. The government of Indonesia has invested intensely in the development of a toll road network. The length of toll road operation has increased from around 750 km in 2014 to over 2,500 km in 2022. The construction encroaching paddy fields and resulting the production of rice decreasing every year. The paper objective is to investigate the implications of toll road investment to the rice market integration by focusing on Java as the central rice-producing region in Indonesia. We used the Vector Error Correction Model (VECM) approach to analyze the long-ranging daily rice price data series. The result of the study found that Cipinang Central Market in Jakarta has not the significant spatial market integration with rice markets in Java. Despite the fact that West Java, East Java, and Central Java with Cipinang Central Market have a major business tie, prices are not increasing. This shows a severe lack of market integration. The phrase “optimal market integration” refers to a more efficient market, especially when it comes to establishing rice market prices.

Niche differentiation and biogeography of Bathyarchaeia in paddy soil ecosystems: a case study in eastern China

Bathyarchaeia (formerly Bathyarchaeota) is a group of highly abundant archaeal communities that play important roles in global biogeochemical cycling. Bathyarchaeia is predominantly found in sediments and hot springs. However, their presence in arable soils is relatively limited. In this study, we aimed to investigate the spatial distributions and diversity of Bathyarchaeia in paddy soils across eastern China, which is a major rice production region. The relative abundance of Bathyarchaeia among total archaea ranged from 3 to 68% in paddy soils, and Bathy-6 was the dominant subgroup among the Bathyarchaeia (70–80% of all sequences). Bathyarchaeia showed higher migration ability and wider niche width based on the neutral and null model simulations. Bathy-6 was primarily assembled by deterministic processes. Soil pH and C/N ratio were identified as key factors influencing the Bathyarchaeia composition, whereas C/N ratio and mean annual temperature influenced the relative abundance of Bathyarchaeia. Network analysis showed that specific Bathyarchaeia taxa occupied keystone positions in the archaeal community and co-occurred with some methanogenic archaea, including Methanosarcina and Methanobacteria, and ammonia-oxidizing archaea belonging to Nitrososphaeria. This study provides important insights into the biogeography and niche differentiation of Bathyarchaeia particularly in paddy soil ecosystems.

Identifying Spatial Determinants of Rice Yields in Main Producing Areas of China Using Geospatial Machine Learning

Rice yield is essential to global food security under increasingly frequent and severe climate change events. Spatial analysis of rice yields becomes more critical for regional action to ensure yields and reduce climate impacts. However, the understanding of the spatially varied geographical, climate, soil, and environmental factors of rice yields needs to be improved, leading to potentially biased local rice yield prediction and responses to climate change. This study develops a spatial machine learning-based approach that integrates machine learning and spatial stratified heterogeneity models to identify the determinants and spatial interactions of rice yields in the main rice-producing areas of China, the world’s largest rice-producing nation. A series of satellite remote sensing-derived variables are collected to characterize varied geographical, climate, soil, and environmental conditions and explain the spatial disparities of rice yields. The first step is to explore the spatial clustering patterns of the rice yield distributions using spatially global and local autocorrelation models. Next, a Geographically Optimal Zones-based Heterogeneity (GOZH) model, which integrates spatial stratified heterogeneity models and machine learning, is employed to explore the power of determinants (PD) of individual spatial variables in influencing the spatial disparities of rice yields. Third, geographically optimal zones are identified with the machine learning-derived optimal spatial overlay of multiple geographical variables. Finally, the overall PD of various variables affecting rice yield distributions is calculated using the multiple variables-determined geographically optimal zones and the GOZH model. The comparison between the developed spatial machine learning-based approach and previous related models demonstrates that the GOZH model is an effective and robust approach for identifying the spatial determinants and their spatial interactions with rice yields. The identified spatial determinants and their interactions are essential for enhancing regional agricultural management practices and optimizing resource allocation within diverse main rice-producing regions. The comprehensive understanding of the spatial determinants and heterogeneity of rice yields of this study has a broad impact on agricultural strategies and food security.

Water properties and quality of the largest rice production region in Japan and their influence on the reproduction of zebrafish.

The health of freshwater aquarium fish and their breeding success depend critically on the quality of tap water. In general, tap water in Japan is potable, although the properties of tap water vary among regions in Japan. The city of Niigata is located in the largest rice production region of Japan. We have faced challenges concerning the reproduction of freshwater aquarium fish in Niigata. To determine whether water properties and quality affect the reproduction of aquarium fish in Niigata, we investigated the chemical properties of water and raised zebrafish in water from three different sources, namely tap water of Niigata in May, artificial freshwater (i.e., prepared via reverse osmosis), and natural spring water of Gosen, to document any effects on their sexual maturation and reproduction. We found that the tap water of Niigata was not stable throughout a year (median electrical conductivity = 147.1 μS/cm; SD = 25.6), with springtime lower than the first quartile. We also found that low concentrations of four pesticides in the tap water have been detected in May (max. concentration in 2020, bromobutide 2,000ng/L, butachlor 600ng/L, pyraclonil 200ng/L, ipfencarbazone 20ng/L). Moreover, rearing zebrafish in tap water negatively influenced both fish growth and reproduction: The sex ratio of adults was male biased (proportion of F0 male 70.8%); the average total length (30.5mm) and weight (182mg) of F0 males was decreased; the GSI of F0 females (9.7%) was decreased; the fecundity (the mating success 58.7%; the number of F1 eggs 63.1) of adults was reduced. Rearing in artificial freshwater could improve these outcomes (the sex ratio 55.7%; the total length of F0 males 31.8mm; the weight of F0 males 211mg; the GSI of F0 females 11.7%; the mating success 72.6%; the number of F1 eggs 99.0), whereas rearing in natural spring water from Gosen could improve the sex ratio (56.3%) and the weight of F0 males (200mg), but not the others. Therefore, artificial freshwater made via reverse osmosis should be used for breeding freshwater aquarium fish in rice production region like Niigata. Finally, our results demonstrate that the reproduction of freshwater aquarium fish can serve as a bioindicator of low levels of organic pollutants in tap water and thus provide a basis for evaluating the safety of tap water for human consumption.

Paddy Rice Mapping Based on Phenology Matching and Cultivation Pattern Analysis Combining Multi-Source Data in Guangdong, China

Paddy rice mapping is crucial for cultivation management, yield estimation, and food security. Guangdong, straddling tropics and subtropics, is a major rice-producing region in China. Mapping paddy rice in Guangdong is essential. However, there are 2 main difficulties in tropical and subtropical paddy rice mapping, including the lack of high-quality optical images and differences in paddy rice planting times. This study proposed a paddy rice mapping framework using phenology matching, integrating Sentinel-1 and Sentinel-2 data to incorporate prior knowledge into the classifiers. The transplanting periods of paddy rice were identified with Sentinel-1 data, and the subsequent 3 months were defined as the growth periods. Features during growth periods obtained by Sentinel-1 and Sentinel-2 were inputted into machine learning classifiers. The classifiers using matched features substantially improved mapping accuracy compared with those using unmatched features, both for early and late rice mapping. The proposed method also improved the accuracy by 6.44% to 16.10% compared with 3 other comparison methods. The model, utilizing matched features, was applied to early and late rice mapping in Guangdong in 2020. Regression results between mapping area and statistical data validate paddy rice mapping credibility. Our analysis revealed that thermal conditions, especially cold severity during growing stages, are the primary determinant of paddy rice phenology. Spatial patterns of paddy rice in Guangdong result from a blend of human and physical factors, with slope and minimum temperature emerging as the most important limitations. These findings enhance our understanding of rice ecosystems’ dynamics, offering insights for formulating relevant agricultural policies.

Spatial and variety distributions, risk assessment, and prediction model for heavy metals in rice grains in China.

In this study, 6229 brown rice grains from three major rice-producing regions were collected to investigate the spatial and variety distributions of heavy metals in rice grains in China. The potential sources of heavy metals in rice grains were identified using the Pearson correlation matrix and principal component analysis, and the health risks of dietary exposure to heavy metals via rice consumption were assessed using the hazard index (HI) and total carcinogenic risk (TCR) method, respectively. Moreover, 48 paired soil and rice samples from 11 cities were collected to construct a predicting model for Cd accumulation in rice grains using the multiple linear stepwise regression analysis. The results indicated that Cd and Ni were the main heavy metal pollutants in rice grains in China, with approximately 10% of samples exceeding their corresponding maximum allowable limits. The Yangtze River basin had heavier pollution of heavy metals than the Southeast Coastal Region and Northeast Plain, and the indica rice varieties had higher heavy metal accumulation abilities compared with the japonica rice. The Cu, Pb, and Cd mainly originated from anthropogenic sources, while As, Hg, Cr, and Ni originated from both natural and anthropogenic sources. The mean HI and TCR values of dietary exposure to heavy metals via rice consumption ranged from 2.92 to 4.31 and 9.74 × 10-3 to 1.44 × 10-2, respectively, much higher than the acceptable range, and As and Ni were the main contributor to the HI and TCR for Chinese adults and children, respectively. The available Si (ASi), total Cd (TCd), available Mo (AMo), and available S (AS) were the main soil factors determining grain Cd accumulation. A multiple linear stepwise regression model was constructed based on ASi, TCd, AMo, and AS in soils with good accuracy and precision, which could be applied to predict Cd accumulation in rice grains and guide safe rice production in contaminated paddy fields.

Rat Population Increase And Damage To Rice Plantations With Different Irrigation Systems In Wajo Regency, South Sulawesi Province

One of the rice producing regions in Indonesia is South Sulawesi. Wajo Regency is the second highest rice producing area in South Sulawesi, after Bone Regency. Based on the irrigation system, rice cultivation in Wajo Regency consists of technical irrigation, rainfed rice fields, and rice cultivation or dry land. Agriculture with various irrigation systems has an impact on pest population levels and the intensity of attacks. The decline in rice productivity is caused by many factors, one of which is the attack of rice rat pests that occur in several areas in Wajo Regency. There are several techniques and strategies for field rat management, ranging from sanitation, technical culture or plant cultivation, mechanical, biological, and chemical physical. All techniques and strategies of rice rat management must be applied integrated, continuously, and together in one stretch. This study aims to measure the potential presence of rice rats in several irrigation systems in Wajo Regency (irrigation, rainfed rice fields, and dryland rice), analyze the management of rice rats carried out by farmers, and the factors that affect it. The method used is observing rice planting patterns based on irrigation systems, estimating the population level of rice rats with single live traps and the level of attack on several rice planting irrigation systems. Likewise, rice rat population management in several rice planting irrigation systems, data analysis, and economic analysis. The result of this study is that the highest estimate of rats is in dryland rice plantations. The intensity of rat attacks was highest in dry land Pr&gt;F 0.045 the area of attack was highest in rainfed land Pr&gt;F was 0.0171, for intensity and area of attack in generative phase 1. The success of cultivation in dry land was 16.3% in generative phase 1 which was 16.48%. The presence of rats correlates both the intensity of the attack and the area of each addition of rats will increase the intensity of the attack by 0.155% and the area of attack by 0.308%.

Projecting the impact of climate change and elevated CO2 concentration on rice irrigation water requirement in China

Climate change and elevated CO2 concentrations significantly affect rice growth and water consumption. Understanding the specific impacts of climate change and elevated CO2 concentrations on rice physiological phenology, crop water demand (ETC), and irrigation water requirement (IR) is of great significance for the sustainable utilization of water resources and food security. This is particularly true in China, the world's largest rice producer. In this study, with the help of two rice phenological models, the modified Penman-Monteith equation, and the paddy water balance model, we project the changes in rice phenological period, ETC, and IR in four main rice-producing regions of China in the period 2015–2100 based on the 11 GCM outputs. The results show that the rice growing period is shortened in most rice-producing regions, except for the parts of the middle and lower reaches of the Yangtze River. Meanwhile, the trend of ETC and IR of rice varies slightly among regions in the future scenario, with almost all regions decreasing yearly except for the middle and lower reaches of the Yangtze River, where the trend is increasing. The progressively increasing atmospheric CO2 concentration has a “fertilization effect” on the crop, which can reduce the water requirements of rice. In the SSP585 scenario, the “ CO2 fertilization effect” can reduce up to 8.87 × 108 m3 of ETC and 6.94 × 108 m3 of IR in the middle and lower reaches of the Yangtze River in the period of 2090s. This study provides beneficial references to understand the response of rice ETC and IR to future climate change and CO2 concentration elevation in China and highlights that the simulation in terms of crop irrigation must account for the “CO2 fertilization effect”.