Production Of Rice Plants Research Articles

Productivity and Quality of Rice as Influenced by Foliar Spray of Different Silicon Sources and Rates Under Salinity Soil Conditions

A field experiment was carried out at El-Sirw Agriculture Research Farm at Damietta governorate, Egypt in 2018 and 2019 seasons. This investigation aimed to be study the effect of foliar application of three silicon sources at three rates for each, i.e. nano silica at 50, 100 and 150 ppm and potassium silicate as well as magnesium silicate at 500, 1000 and 1500 ppm for both of them on the productivity of rice plants grown in saline soil. Foliar application of Si at different tested sources and rates significantly increased each of physiological characters (chlorophyll content and stomatal conductance), morphological characters (plant height, number of tillers/ m2, leaf area index and dry matter production/ m2), chemical composition in the leaf (K %, K / Na ratio and Si %), yield components (number of panicles/ m2, panicle weight and length, number of filled grains/ panicle and 1000 - grain weight), yields/ ha (grain and straw), grain quality characters (hulling % , milling % , head rice %, protein and amylose %), while significantly decreased Na % in the leaf, number of unfilled grains/ panicle and chalkiness grains % as compared with untreated plants (control treatment) in both seasons. Spraying of nano silica at 150 ppm and potassium silicate at 1500 ppm were found to be more efficiency in increasing most abovementioned traits of rice plants grown in saline soil than the other tested silicon sources and rates.

Enhanced glutathione content improves lateral root development and grain yield in rice plants.

Enhanced glutathione content improves lateral root development by positively regulating the transcripts of root development genes responsive to glutathione treatment, thereby increasing the overall productivity of rice plants. Glutathione is primarily known as a cellular antioxidant molecule, but its role in lateral root development in rice plants has not been elucidated. Here, we have investigated its role in lateral root development of rice Oryza sativa L. Exogenous glutathione (GSH) promoted both the number and length of lateral roots in rice, and the GSH biosynthesis inhibitor buthionine sulfoximine (BSO) significantly reduced these parameters, compared to untreated plants. The inhibition by BSO was reversed with exogenous GSH. Transcript profiling by RNA-seq revealed that expression of the transcription factor genes DREB and ERF and the hormone-related genes AOS, LOX, JAZ, and SAUR were significantly downregulated in the BSO-treated plants and, in contrast, upregulated in plants treated with GSH and with GSH and BSO together. We generated OsGS-overexpressing transgenic plants in which the transgene is controlled by the abiotic-stress-inducible OsRab21 promoter to study the effect of endogenously increased GSH levels. In cold stress, transgenic rice plants enhanced stress tolerance and lateral root development by maintaining redox homeostasis and improving upregulating the expression of transcription factors and hormone-related genes involved in lateral root development. We observed improved root growth of OsGS-overexpressing plants in paddy fields compared to the wild-type controls. These traits may have alleviated transplanting stress during early growth in the field and accounted for the increased productivity. These results provide information and perspectives on the role of GSH in gene expression, lateral root development, and grain yield in rice.

Strong mitigation of greenhouse gas emission impact via aerobic short pre-digestion of green manure amended soils during rice cropping

To increase soil carbon (C) stock, cover crop cultivation during the fallow season and its biomass incorporation as green manure (GM) is strongly suggested in mono-rice paddy. On the other hand, biomass application can highly increase greenhouse gas (GHG) emission, in particular methane (CH4) during irrigated cropping season. Aerobic short pre-digestion of biomass applied soils was very effective to suppress CH4 emission. However, its effect on other GHG (CO2 and N2O) emissions was not clear. To assess the integrated influence of aerobic short pre-digestion of green manured soils on global warming impact, cover crop biomass as GM was amended with different time interval before flooding (0–30 days) and aerobically decomposed under upland condition. Aerobic short pre-digestion over 10 days significantly decreased seasonal CH4 flux, but did not affect N2O emission. As aerobic pre-digestion days became longer, net ecosystem C balance (NECB) which implies the difference between C input and output was slightly increased, but not statistically different. The net primary productivity of rice plant as a C input source was not significantly differentiated by aerobic short pre-digestion. As a C output source, the respired C loss that was composed with CO2-C and CH4-C emission was not considerably discriminated among 0–30 days of aerobic short pre-digestion. As a consequence, due to big reduction of CH4 emission, aerobic short pre-digestion significantly decreased net GWP which means integration of seasonal CH4 and N2O fluxes and NECB as CO2 equivalent. In conclusion, aerobic short pre-digestion of biomass applied soil could be a sustainable management practice to decrease GHG emission impact without SOC stock change in temperate rice paddy field.

Increasing the Growth and Production of Irrigated Rice Through the Integrated Application of Rice–Duck–Azolla

The application of integrated agriculture is an effort to reduce dependence up on agrochemicals and increase the absorption of nutrients, especially nitrogen, to increase plant growth and production. <em>Azolla </em>is an algae that can provide nitrogen for rice, while ducks can increase the availability of N, P, and K, as well as the efficiency of nitrogen use. This research aimed to evaluate the role of ducks and <em>Azolla </em>in increasing the growth and production of rice plants. This research was conducted from October 2018 to February 2019 using an experimental method with a nonfactorial randomized block design. The combinations of nitrogen fertilizers, <em>Azolla</em>, and ducks (K) were as follows: K1 = 115 kg N ha<sup>−1</sup>, without ducks, without <em>Azolla</em>; K2 = 86 kg N ha<sup>−1</sup>, without ducks, 1,000 kg <em>Azolla </em>ha<sup>−1</sup>; K3 = 86 kg N ha<sup>−1</sup>, 3,000 ducks ha<sup>−1</sup>, 1,000 kg <em>Azolla </em>ha<sup>−1</sup>; K4 = 58 kg N ha<sup>−1</sup>, 3,000 ducks ha<sup>−1</sup>, 1,000 kg <em>Azolla </em>ha<sup>−1</sup>; K5 = 29 kg N ha<sup>−1</sup>, 3,000 ducks ha<sup>−1</sup>, 1,000 kg <em>Azolla </em>ha<sup>−1</sup>; and K6 = without N fertilizer, 3,000 ducks ha<sup>−1</sup>, 1,000 kg <em>Azolla </em>ha<sup>−1</sup>. The results showed that the application of 58 kg N ha<sup>−1</sup>, 3,000 ducks ha<sup>−1</sup>, and 1,000 kg <em>Azolla </em>ha<sup>−1</sup> (K4) was able to decrease the N fertilizer application by 50% and increase the rice growth and yield by 12.17% and 20.32%, respectively. Therefore, the integrated application of rice–duck–<em>Azolla </em>would support sustainable agriculture.

Pest Detection Expert System And Method Using Bayes Rice Diseases

Indonesia is included in an agricultural country that is rich in agriculture, fertile land in Indonesia allows for the growth of various types of plants, one of which is rice. But in the cultivation of rice plants, it will never be separated from pests and diseases of rice plants, so that the growth of rice plants is not optimal. Due to the large number of pests and diseases that can attack rice plants, it is necessary to take proper care in dealing with pests and diseases of rice plants to avoid losses that can result in reduced production of rice plants. Therefore an expert system was created which was expected to help farmers in consulting about diseases and pests contained in their rice plants to the experts without having to meet with experts directly. In its identification, the expert system for diagnosing ahama and rice disease uses the Bayes method and uses the Website in its implementation.

Beneficial Effect of Silicon Application and Intermittent Irrigation on Improving Rice Productivity in Indonesia

It is believed that silicon (Si) application could increase rice production, however studies related to those topics are still limited. The study determined the combination effect of Si application and water management on rice growth and productivity. This study was conducted at the experimental station of Indonesian Agricultural Environment Research Institute, Jakenan, Pati, Central Java at dry season. A split-plot in randomized complete block design with four replications was set. The main plots were different types of irrigation and subplots were Si fertilizer application. Results showed that the application of Si increased plant resistance on blast disease. This current result might be due to the increasing of Si concentration in leaves. IT water management significantly increased the yield compared to CF. IT increased root growth and gave an impact on increasing of plant growth and rice yield. Moreover, IT significantly increased Cu, Mn, and Zn concentration in rice grain. Combination of Si application with IT water management could increase rice plant productivity especially in area with water shortage.
 Keywords: blast disease, lodging, rice productivity, silicon application, water management

Nitrogen Deficiency Prediction of Rice Crop Based on Convolutional Neural Network

Nitrogen (N) concentration is a significant parameter to check the status of health in rice crop. Nitrogen (N) plays an essential role in the growth and productivity of rice plant. This paper proposes a convolutional neural network (CNN) based approach for prediction of rice nitrogen deficiency. The pre-trained CNN architecture is modified to improve the classification accuracy with the inclusion of pre-eminent classifier like support vector machine (SVM) by replacing the last output layer of CNN. Here, six leading deep learning architectures such as ResNet-18, ResNet-50, GoogleNet, AlexNet, VGG-16 and VGG-19 with SVM are used for prediction of nitrogen deficiency with 5790 number image samples. The performance of each classifier is measured and compared in terms of accuracy, sensitivity, specificity, false positive rate (FPR) and F1 score. Again, the statistical analysis is performed to choose the better classification model considering the results of 100 independent simulations. The statistical analysis confirmed the superiority of ResNet-50+SVM than the other five CNN-based classification models with an accuracy of 99.84%. Besides, the accuracy score of CNN classification models is compared with other traditional image classification models such as bag-of-feature, colour feature + SVM, local binary patterns (LBP) + SVM, histogram of oriented gradients (HOG)+SVM and Gray Level Co-occurrence Matrix (GLCM)+SVM.

Factors That Influence Adoption of Jajar Legowo Planting System in Sumber Makmur Farmer Group Kuwu Village, Balerejo, Madiun

The background of this research is the low interest of farmers in the village of Kuwu to implement the jajar legowo planting system. Even though some studies show that the Jajar Legowo planting system has succeeded in increasing the productivity of rice plants. Based on these conditions, this study aimed to determine what factors influence the adoption of farmers in the application of the Legowo row planting system. The method used in describing the formulation of the problem in this study is a survey method with AMOS 22 Structural Equation Modeling (SEM) data analysis. The object of study is the legowo row farmers who are members of Sumber Makmur Village, Kuwu Village. The results of this study indicate that the adoption model of farmers is influenced by the attitudes and characteristics of innovation through the mediator variabel of perception and attitude. Hypothesis test results state that there is an influence of innovation characteristics on perceptions and attitudes towards adoption with a significance value of 0.001 which is smaller than 0.05.

Rice Productivity Analysis by Province Using K-Means Cluster Algorithm

Rice (Oryza sativa L.) is a very important food crop in the world after wheat and corn. It is also a staple food for most of the world’s population, especially in Asia, like in Indonesia until now. In 2014 to 2018, rice productivity tended to change dynamically. In 2018, rice productivity in Indonesia was 51.92 (Ku/Ha). This research was conducted to classify rice productivity in 34 provinces in Indonesia in 2018. The data used were sourced from Statistics Indonesia. The method or approach used in this study is the K-Means cluster algorithm to classify rice productivity data by province in 2018. The results of the research are; (1) There are 19 provinces included in cluster 0 (Medium), (2) There are 4 provinces included in cluster 1 (High), and (3) There are 11 provinces that are included in cluster 2 (Low). Based on the results of the study, it was proven that there were 4 provinces in cluster 1 (High) they are West Java, Central Java, East Java and South Sulawesi, with the highest rice productivity. Three of them were on Java Island. It shows that Java still dominates the productivity of rice plants.

Efficiency and risks of selenite combined with different water conditions in reducing uptake of arsenic and cadmium in paddy rice

The co-contamination of arsenic (As) and cadmium (Cd) in soils is a common problem. Selenium (Se) can reduce the uptake of As and Cd in plants, and in practice, the alternate wetting and drying is a common culture mode in rice production. However, it is unknown whether Se can efficiently reduce As and Cd concentrations in crops suffering from a high-level contamination of As and Cd under different soil water conditions. In this study, we assessed the efficiency and risks of selenite [Se(IV)], in a pot experiment, to reduce the uptake of As and Cd in a rice plant (YangDao No 6) growing in a heavily contaminated soil by As and Cd (pH 7.28) under different soil water conditions. The results showed that Se(IV) failed to control the grain total As and Cd concentrations within their individual limited standard (0.2 mg kg−1) despite that Se(IV) significantly reduced the grain total As and Cd concentrations. The soil drying treatment alone could reduce the accumulation of arsenite [As(III)] in the grains, but additional Se(IV) stimulated the accumulation of As(III) in the grains under soil drying conditions. In addition, the addition of Se(IV) enhanced the As and Cd concentrations in the shoots and/or roots of rice plants under certain conditions. The above results all suggested that the utilization of Se(IV) in a high contaminated soil by As and Cd cannot well control the total concentrations of As and Cd in plants. In this study, the available concentrations of As and Cd in the rhizosphere soil, the rhizosphere soil pH, the formation of root iron/manganese plaques and the concentrations of essential elements in the grains were monitored, and the related mechanisms on the changes of these parameters were also discussed. This study will give a guideline for the safe production of rice plants in a heavily co-contaminated soil by As and Cd.

Application of Bio Fertilizer and Biogas Sludge to Curly Red Chili (Capsicum annuum L.) at Wukirsari Village, Cangkringan, Sleman

Curly red chili (Capsicum sp.) is an important agricultural commodity in Indonesia. The pattern of conventional cultivation using inorganic fertilizers has caused high production costs. While the level of spiciness of chili determined by capsaicin levels is strongly influenced by nutrients in the growing media. Bio fertilizer and sludge biogas biogas which is one of the organic fertilizers proved to be able to increase the growth and productivity of rice plants. This study aimed to analyze growth parameters, chlorophyll content and measure capsaicin levels in curly red chili. Which given bio fertilizer and biogas sludge biogas in various dosage and determine the optimum dose of the fertilizer. The study was conducted at an agricultural demonstration plot in Wukirsari Village, Cangkringan, Sleman. The study design used RCBD (Randomized Complete Block Design), the data were analyzed by ANOVA (Analysis of Variance followed by Duncan's multiple distance test (DMRT) at the 95% confidence level. The highest growth parameters was obtained on curly red chili plants which were given sludge biogas 36 mL + bio fertilizer 10 L / ha. Thus, it can be concluded that the most appropriate dose of curly red chili is 36 mL sludge biogas + bio fertilizer 10 L/ha.Keywords: Bio-fertilizer; biogas; chili; growth;sludge; Wukirsari.

Performance of Rice Production and Pest in Riau Province

Production of rice plants is affected by pest attacks. This study aimed to (i) analyze the trend of rice production and pest in Riau Province over the past 10 years, (ii) to predict the trend of pests and rice production of Riau Province for the next 5 years, and (iii) to formulate policy alternatives in order to increase rice production and pest attack control in Riau Province. Secondary data covering production data and paddy pests were obtained from related institutions. For validation and completion of some secondary data, the primary data was collected from direct observation and various competent sources. The data were analyzed in tabulative, regression and simple descriptive to answer the research objectives. The results showed that there has been a decline in rice production in Riau Province for the last 5 years was quite high (23.0%). The decline in production is mainly due to a decrease in harvested area. The decline in production is also caused by pest attacks. The type and extent of rice pest attack show a fluctuating trend. There are 8 types of pests causing rice crop failure (puso), namely bird, rice bug, golden apple snail, stem borer, brown spot disease, blast, and bacteria leaf blight. The total area of rice pests attack by category of puso 161.4 ha. In the next 5 years, Riau rice production is predicted to increase every year while pest attack will decrease every year. Rice production can be increased through increasing harvested area, reducing land conversion, water availability. While pest attack can be suppressed through the use of resistant varieties, early detection, simultaneous control, and intensify counseling.

Improvement of rice plant productivity by native Cr(VI) reducing and plant growth promoting soil bacteria Enterobacter cloacae

Rapid industrialization and anthropogenic activities have produced huge amount of noxious Cr(VI), which accumulate in the soil for longer period. As a consequence, that decreases rice plant productivity in contiguous agricultural field of Sukinda mining area, Odisha. Thus, the high Cr(VI) resistant native bacterial strain CTWI-06 was selected for the study, which depicted resistance to 3500 ppm of Cr(VI) and wide array of other metals. Under optimized condition, the multi-metal resistant bacteria reduced 94% Cr(VI) within 92 h and Cr(VI) reduction was confirmed by FTIR and XRD analysis. Plant growth promoting traits like N2 fixation; phosphate (146.87 ppm), potassium (12.55 ppm) and Zn solubilization; ammonification; IAA production (114 μg mL−1) and suppression of fungal phytopathogens such as Rhizoctonia solani (ITCC 2060) and Phytium debaryanum (ITCC 5488) were also recorded. The bacterial strain was identified as Enterobacter cloacae CTWI-06 by 16S rDNA sequence (Accession No. MG757378). It significantly improved growth traits as well as productivity of Mahalakshmi rice variety in pot culture. Thus, the potential Cr(VI) reducing and PGPB strain may be utilized for long term bioremediation of Cr(VI) in chromium contaminated soil and to maintain soil fertility.

Humic Acid and Water Management to Decrease Ferro (Fe2+) Solution and Increase Productivity of Established New Rice Field

The purpose of this research was to gain a technological breakthrough in controlling Fe toxicity (Fe2+) on Ultisol in a new established rice field by using humic acid from rice straw compost and water management, so that optimal production of rice plants could be achieved. The experiment was designed using a 2 × 4 factorials with 3 replications in a split plot design. The main plot was water management consists of 2 levels: continuous and intermittent irrigation (2 weeks flooded and 2 weeks field capacity). Small plot was humic acid which was extracted from rice straw compost by NaOH 0.5 N which consists of 4 levels: 0, 200, 400, and 600 mg kg-1. The results showed that applications of humic acid from 0 to 600 mg kg-1 that was followed by 2 weeks of intermittent irrigation decreased Fe2+ concentration. It was approaching levels that were not toxic to plants, with soil Fe2+ between 180-250 mg kg-1. The best treatment was found at the application of 600 mg kg-1 humic acid extracted from rice straw compost combined with 2 week flooded – 2 weeks field capacity of water management. Those treatment decreased Fe2+ concentration from 1,614 to 180 mg kg-1 and increased the dry weight of grain from 5.15 to 16.73 g pot-1 compared to continuous flooding and without humic acid application.

Deficit irrigation for rice farming with production risk due to weather variability

Deficit irrigation is one of the keys in overcoming the problem of weather variability and limited water resources. Farmers can reduce the amount of irrigation water use without affecting too much on the productivity of rice plants by using deficit irrigation. The level of deviation of rice production increases when the water level changes between the ranges of 0-2.5 cm. The tendency to decrease from the level of deviation of agricultural production is seen when the water level increases in the range of 2.5-10 cm. At a water level of 12.5 cm there is a considerable increase in deviation. However, there was a significant decrease in the level of deviation of rice production when the water level was at 15 cm. Based on this, it can be concluded that the risk management of rice production will be better when the water level is above 2.5 cm and below 15 cm. The results of this study not only can be used for the development of risk-based farmers’ decision models but can also be used as input for the development of government policies in resource sharing and development of agricultural insurance

Korelasi Komponen Pertumbuhan dan Hasil pada Pertanian Terpadu Padi-Azolla

Safriyaniet al, 2018. Correlation of Growth and Product Components on Integrated farming Padi-Azolla. JLSO 7(1):In order to increase the growth and production of rice plants that support sustainable agriculture can be done with the azolla application. This study aimed to evaluate the correlation of the components of growth and yield on rice-azolla production. The research was conducted on Karang Ketuan Subdistrict South Lubuklinggau II Subdistrict Lubuklinggau City from January to April 2018. This study used a randomized block consisting of K1=250 kg urea ha-1 without azolla, K2=250 kg urea ha-1+azolla 1000 kg ha-1, K3=187.5 kg urea ha-1+azolla 1000 kg ha-1, K4=125 kg urea ha-1+azolla 1000 kg ha-1, K5=62.5 kg urea ha-1+azolla1000 kg ha-1, K6=without Urea+azolla1000 kg ha-1. Data analysis used correlation and path analysis. The results showed that plant height and number of pithy grains correlated on grain weight with higher values than other growth components. Dry weight of straw and harvest index had a direct and positive effect on grain weight with cross coefficients value namely 1.086 and 0.755 representatives. Plant height and number of pithy grains could be used as an indicator of crop production.

Classification of rice plant fertilizer needs based on leaf color chart using radial basis function neural network

Management of nitrogen fertilizers in rice plants plays an important role in the productivity of rice plants. Excessive use of fertilizers may result in rice leaves becoming pale, yellowish that can lead to its death. Fertilizer should be given based on the content of nitrogen in rice leaves which is indicated by the color of rice leaf. The color of rice leaf can be checked through tools called Leaf Color Chart (LCC). However, farmers are still likely to experience differences in color perception while classifying the color of the leaf so that farmers sometimes give an inaccurate dose of nitrogen fertilizer. Therefore, this study has the objective to organize the needs of rice nutrient based on leaf color chart and to provide information on the fertilizer dose which is recommended to be given to reduce errors in the use of nitrogen fertilizer. This study used the classification process by looking at the greenish color of the leaf based on leaf color chart using the Radial Basis Function (RBF). The classification process was divided into three classes, namely Green1, Green2, and Green3. This study used 60 images as training data and 30 images as testing data with 90% of accuracy rate.

Simultaneous mitigation of tissue cadmium and lead accumulation in rice via sulfate-reducing bacterium

The objectives of this study were to investigate the mechanism responsible for Cd and Pb immobilization by sulfate reduction to sulfide and effectiveness of decreasing Cd2+ and Pb2+ bioavailability in culture solution and paddy soils via sulfate-reducing bacterium (SRB1-1). The SRB1-1 strain, exhibiting high resistances to Cd2+ and Pb2+, was isolated from bulk soils in the metal(loid)-contaminated paddy field. During the culture of the SRB1-1 strain, the removal percentages of Cd2+ and Pb2+ from culture solution reached 99.5% and 76.0% in 72 h, respectively. The surface morphology and composition of metal precipitates formed by SRB1-1 strain were analyzed by transmission electron microscopy (TEM) and further confirmed to be CdS and PbS by X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS). When living SRB1-1 strain was applied in Cd and Pb-contaminated soils, the SRB1-1 strain could stably colonize using its resistance to rifampicin, and showed significantly impact on the bacterial community composition. Cd and Pb contents in rice grains were decreased by 29.5% and 26.2%, respectively, while Cd and Pb contents in the roots, culms, leaves, and husk were also decreased ranging from 19.1% to 43%, respectively. Due to growth in highly Cd and Pb contaminated soils, Cd content of the rice grains did not meet the standard for limit of Cd and Pb, but safe production of rice plants may be obtained in slightly or moderately metal(loid)-contaminated soils in the presence of the living SRB1-1 strain. These results indicated that the SRB1-1 strain could effectively reduce the Cd and Pb bioavailability in soils and uptake in rice plants. Our results highlighted the possibility to develop a new bacterial-assisted technique for reduced metal accumulation in rice grains, and also showed potential for effective synergistic bioremediation of SRB1-1 strain and rice plants in metal(loid)-contaminated soils.

Pemanfaatan Berbagai Jenis Limbah Rumput Laut terhadap Produktivitas Padi Sawah

Various ways have been made to increase the productivity of rice plants as a source of staple food of Indonesian society. One ofthem is the addition of nutrients in the soil (fertilization). Currently, the innovation use of seaweed as fertilizer is widely used in several countries in the world, because seaweed contains phosphorus, potassium, and some other micro elements. This study aimed to analyze the use of various types of waste seaweed to improve the productivity of paddy rice on the ground Vertisol. The study lasted from December 2014 through Sept. 2015, at Greenhouse, Teaching Farm, Faculty of Agriculture, University of Hasanuddin Makassar. The research method is a randomized block design consisting of eight treatments and six replications (48 pot experiment). Each treatment is C0 (control), C1 (fertilizer N 300 kg / ha, P 100 kg / ha and K 100 kg / ha), G1 (Gracilaria 10 g / pot), G2 (Gracilaria 100 g / pot), S1 (Sargassum 10 g / pot), S2 (Sargassum 100 g / pot), K1 (Kappaphycus 10 g / pot), and K2 (Kappaphycus 100 g / pot). The addition of Sargassum seaweed fertilizer waste 100 g / pot and Kappaphycus dose of 100 g / pot can increase K-dd, Na- dd, base saturation, increase the value of N, P, K, and Ca-dd, but administration with concentrations of 100 g / no maximum pot for rice crop production by causing toxicity in plants. The addition of seaweed fertilizer waste treatment Gracilaria 100 g / pot is effective in improving Vertisol soil chemical properties and can provide maximum results for the productivity of rice plants

Impacts of climate change on soil nitrogen kinetics and rice production in Andisol paddy fields

ABSTRACTWe constructed a new rice growth model, SIMRIWk, and discuss the impact of climate change on the growth and production of rice plants in relation to soil nitrogen (N) kinetics. We developed a model simulating N availability for rice plants associated with soil N kinetics and rice plant N uptake and combined it with the existing rice growth model SIMRIW to construct SIMRIWk. The model parameters were determined from rice plant growth and soil N experimental data obtained over 25 years under four soil management regimes. SIMRIWk successfully simulated the annual changes and upward trend observed during the 25 years in all treatments. The relationship between measured yields and SIMRIWk calculations in all treatments over the 25 years formed one aggregation defined by the regression equation y = 1.00x and showed a significant correlation (r2 = 0.894). According to SIMRIWk, increasing temperature in the cold season increases the formation of easily decomposable organic N produced under dry conditions and N mineralization during the next warm season, suggesting that rice growth is influenced by both warm-season and cold-season temperatures. We forecast rice yield and soil N kinetics from 2016 to 2100 using SIMRIWk and climate change predictions based on the IPCC’s climate change scenario RCP8.5. Atmospheric warming, a rise in CO2 partial pressure, and increased soil N mineralization caused by soil warming will increase rice plant growth, but the decreased radiation absorbed owing to the shortened growing season and high-temperature sterility will prevent any significant change in yield. Furthermore, the acceleration of soil organic N decomposition will decrease soil organic N concentrations. Understanding the influences of climate change on soil organic matter kinetics is absolutely critical for predicting the future soil production capacity.