High-yielding Rice Research Articles

Analysis of carbon flow at the metabolite level reveals that starch synthesis from hexose is a limiting factor in a high-yielding rice cultivar

Understanding the limiting factors of grain filling is essential for the further improvement of grain yields in rice (Oryza sativa). The relatively slow grain growth of the high-yielding cultivar 'Momiroman' is not improved by increasing carbon supply, and hence low sink activity (i.e. the metabolic activity of assimilate consumption/storage in sink organs) may be a limiting factor for grain filling. However, there is no metabolic evidence to corroborate this hypothesis, partly because there is no consensus on how to define and quantify sink activity. In this study, we investigated the carbon flow at a metabolite level from photosynthesis in leaves to starch synthesis in grains of three high-yielding cultivars using the stable isotope 13C. We found that a large amount of newly fixed carbon assimilates in Momiroman was stored as hexose instead of being converted to starch. In addition, the activity of ADP-glucose pyrophosphorylase and the expression of AGPS2b, which encodes a subunit of the ADP-glucose pyrophosphorylase enzyme, were both lower in Momiroman than in the other two cultivars in grains in superior positions on panicle branches. Hence, slower starch synthesis from hexose, which is partly explained by the low expression level of AGPS2b, may be the primary metabolic reason for the lower sink activity observed in Momiroman.

Optimised fertiliser suggestion in smart agriculture system based on fuzzy inference rule

ABSTRACT Rice crop is one of the major cultivating crops in India, especially in south India. Fertiliser plays an important role to achieve the highest rice yield. Each crop needs an adequate amount of fertiliser for its growth. Inadequate and overdose of fertiliser leads to nutrient deficiency and lesser yield of crops. Rice has a unique fertiliser recommendation based on climatic conditions and soil types but the issue is the random use of fertilisers by the farmer, without knowing their own land soil nutrition. Soil consists of primary nutrients and secondary nutrients. This supplement is used for crop growth. This paper discusses a proposed methodology of an optimised fertiliser simulation model for Cuddalore and Salem district and its sub talukas for rice and maize crops. In this research work, the fuzzy logic technique is used because this is one of the best ways for problem-solving techniques. In this fuzzy logic, Mamdani fuzzy logic-based tool is used. The Mamdani fuzzy logic tool is used for the suggestion of the fertilisers required according to the minerals present in their soil. In result total 45 rules are created for recommending the fertiliser use for paddy and maize crops.

Methane and nitrous oxide emissions from paddy fields with no fertilizer use under continuous irrigation with treated municipal wastewater.

Treated wastewater (TWW) irrigation has been recommended as an environmentally friendly agricultural practice and has been applied in many countries for decades. The effects of wastewater irrigation on rice yield and quality, as well as on the environment, with particular focus on greenhouse gas emissions from paddy fields with municipal wastewater irrigation, have gained substantial attention. In this study, bench-scale experiments were conducted in two cultivation seasons where seedlings of Bekoaoba, a large-grain high-yield rice variety, were transplanted and irrigated with TWW without fertilization. A control experiment was performed to simulate the cultivation conditions of normal paddy fields. The study aimed to quantify the effects of TWW irrigation on rice yield and quality, in addition to CH4 and N2O emissions. The highest rice yield (10.4tha-1) and protein content in brown rice (13.8%) was achieved when the soil was repeatedly subjected to bottom-to-top TWW irrigation without any synthetic fertilizer. Bottom-to-top TWW irrigation decreased CH4 emissions by up to 95.6% when compared with tap water irrigation, whereas bottom-to-top and top-to-top TWW irrigation increased N2O emissions by 5 and 15 times, respectively. Bottom-to-top irrigation of TWW could be considered a promising solution for reducing greenhouse gas emissions as TWW irrigation resulted in a lower combined global warming potential than tap water irrigation. Further, bottom-to-top irrigation of TWW produced less CH4 and N2O than top-to-top irrigation.

A natural allele of TAW1 contributes to high grain number and grain yield in rice

Grain number per panicle (GNP) is a complex trait controlled by quantitative trait loci (QTL), directly determining grain yield in rice. Identifying GNP-associated QTL is desirable for increasing rice yield. A rice chromosome segment substitution line (CSSL), F771, which showed increased panicle length and GNP, was identified in a set of CSSLs derived from a cross between two indica cultivars, R498 (recipient) and WY11327 (donor). Genetic analysis showed that the panicle traits in F771 were semidominant and controlled by multiple QTL. Six QTL were consistently identified by QTL-seq analysis. Among them, the major QTL qPLN10 for panicle length and GNP was localized to a 121-kb interval between markers N802 and N909 on chromosome 10. Based on quantitative real-time PCR and sequence analysis, TAWAWA1 (TAW1), a known regulator of rice inflorescence architecture, was identified as the candidate gene for qPLN10. A near-isogenic line, NIL-TAW1, was developed to evaluate its effects. In comparison with the recurrent parent R498, NIL-TAW1 showed increased panicle length (14.0%), number of secondary branches (20.9%) and GNP (22.0%), and the final grain yield per plant of NIL-TAW1 was increased by 18.6%. Transgenic experiments showed that an appropriate expression level of TAW1 was necessary for panicle development. Haplotype analysis suggested that the favorable F771-type (Hap 13) of TAW1 was introduced from aus accessions and had great potential value in high-yield breeding both in indica and japonica varieties. Our results provide a promising genetic resource for rice grain yield improvement.

Effect of Reducing Nitrogen and Applying Organic Fertilizer on Nitrogen Use Efficiency and Rice Yield in Red Soil Regions of the Southern China

To explore the amount of reducing N fertilizer, a 2-year field experiment was conducted to investigate the effects of reducing N fertilizer and applying organic fertilizer on nitrogen use efficiency (NUE) and rice yield in red soil regions of the Southern China. On the basis of applying 4500 kg/ha organic fertilizer and local custom fertilization with 204 kg/ha urea application, five treatments including no nitrogen fertilization (CK), local customary nitrogen application (N100), and nitrogen reduction of 10% (N90), 20% (N80), and 30% (N70) were conducted. The results showed that nitrogen agronomic efficiency (NAE), nitrogen recovery efficiency (NRE), nitrogen physiological efficiency (NPE) and nitrogen partial factor productivity (NPFP) of N90 treatment were significantly higher than those of other treatments, and the yield was as high as 9.33 t/ha, which showed a significant differences compared with CK and N100. The output value, benefit, and benefit-cost ratio of N90 were significantly higher than those of N100, which increased by 6.38%, 6.42%, 8.35%, and 8.20%, respectively. In addition, while applying the same amount of organic fertilizer, the rate of nitrogen reduction has little effect on the soil organic matter content, meaning that N90 can achieve high NUE and high yield in rice. It is good to provide the theory basis for fertilizer decision-making in practice.

Growth and yield of several rice varieties in swampland agroecosystems in Mesuji Regency, Lampung Province

Swampland agroecosystem is a potential area for rice extensification program in order to increase food production. This study aimed to examine the growth and yield of several rice varieties planted in swampland agroecosystems in Mesuji Regency, Lampung Province. The experiment was conducted from November 2020 until March 2021. The planting location was in Tanjung Mas Jaya Village, Mesuji Timur District, Mesuji Regency, Lampung Province. The rice varieties planted were IAARD’s Superior varieties (Cilamaya Muncul, Inpara-2, Inpara-8, and Inpari IR Nutrizinc), multinational varieties (Mapan and Supadi) and existing local variety (Kebo). The observed variables were components of the growth and production of rice plants. The data were analyzed using Duncan test. The results showed that the yield was significantly different between the rice varieties planted. The lowest rice yield was obtained from the Inpara-2 variety (7.573 ton ha-1of HDG). The highest yield of rice was in the Kebo variety (10.400 ton ha-1of HDG). In order to gain optimal rice production in an area, it is necessary to use superior varieties of rice that have been adaptive to the local area.

Comparative Cost Benefit Analysis of Conventional Farming and Agroecological Farming for Paddy Cultivation in Bachok, Kelantan

In Malaysia, conventional rice farming is the predominant method of rice cultivation with attendant problems like the harmful effects of the utilisation of synthetic pesticides and synthetic fertilisers. Thus, conventional rice farming was compared to the System of Rice Intensification (SRI) method, a variant of agroecological rice farming, in Kampung Klerek, Bachok District, and Kelantan. It must be noted that the agroecological rice farming method is the farmer’s maiden attempt. Agroecological rice farming is a much more environmentally friendly approach. The aim of this paper is to compare conventional rice farming vis-à-vis agroecological rice farming from a financial perspective. Comparative Cost Benefit Analysis has been adopted to determine which the better alternative is. However, the results go beyond financial consideration as conventional rice farming is chemically driven whereas agroecological rice farming is grounded on environmentalism. The results indicated that agroecological rice farming is a better financial alternative with higher revenue and lower cost of production. The higher revenue is due to higher production yield whereas the lower cost of production is due to contributory factors like lower labour cost, lower seed utilisation and ancillary cost, zero cost for synthetic fertilisers and lower fuel and ancillary cost for machinery despite higher organic fertiliser cost. Thus, on a long-term basis, with the effect of the learning and experience curve, the cost of production can be lowered further. Moreover, the higher rice yield, less seed wastage, utilisation of organic fertilisers, organic pesticides and natural pest control methods are in sync with good environmental practices.

Classification of Rice Yield Using UAV-Based Hyperspectral Imagery and Lodging Feature

High-yield rice cultivation is an effective way to address the increasing food demand worldwide. Correct classification of high-yield rice is a key step of breeding. However, manual measurements within breeding programs are time consuming and have high cost and low throughput, which limit the application in large-scale field phenotyping. In this study, we developed an accurate large-scale approach and presented the potential usage of hyperspectral data for rice yield measurement using the XGBoost algorithm to speed up the rice breeding process for many breeders. In total, 13 japonica rice lines in regional trials in northern China were divided into different categories according to the manual measurement of yield. Using an Unmanned Aerial Vehicle (UAV) platform equipped with a hyperspectral camera to capture images over multiple time series, a rice yield classification model based on the XGBoost algorithm was proposed. Four comparison experiments were carried out through the intraline test and the interline test considering lodging characteristics at the midmature stage or not. The result revealed that the degree of lodging in the midmature stage was an important feature affecting the classification accuracy of rice. Thus, we developed a low-cost, high-throughput phenotyping and nondestructive method by combining UAV-based hyperspectral measurements and machine learning for estimation of rice yield to improve rice breeding efficiency.

Automatic Identification Algorithm of the Rice Tiller Period Based on PCA and SVM

The tillering period of rice is the crucial phenological period for the cultivation of high-quality and high-yield rice. Currently, human inspection is mainly used for identification, but it is time-consuming, laborious, and prone to mistakes. To efficiently and accurately identify the start date of rice tillering in the monitoring area, this paper proposed a new algorithm called rice tiller period recognition combining principal component analysis (PCA) and a support vector machine (SVM) (RTR-CPS). This algorithm characterizes the problem of identifying the rice tiller stage as a binary classification problem of rice either entering or not entering the tiller stage. To improve the image segmentation quality of traditional visual segmentation methods, the algorithm was designed to extract five image feature values to describe the rice tiller stage in a multi-featured way, reducing the impact of single feature value bias on the identification of the rice tiller stage. To improve the performance of the rice tiller stage recognition model, the algorithm selects ideal principal features in limited sample data by the PCA algorithm and optimizes SVM classification model hyper-parameters by combining 5-fold cross-validation. The experimental results showed that the accuracy of the algorithm for identifying the tillering date of potted rice was as high as 97.76%, which is significantly higher than other competitive methods, and the maximum error between the detection results and human inspection of potted rice tillering period was no more than 2 days. The rice tillering stage recognition model was applied to the field, and the images of field rice planted by two different methods were tested, which verified that the algorithm proposed in this paper is generalizable. These results fully demonstrate the feasibility and superiority of the algorithm in this paper.

Study of rice genotypes and their use in the process of selection

This research was aimed the use of non-traditional, biochemical marker-based selection methods in synchronization with classical methods in rice selection, rapid adaptation to adverse environmental factors, disease tolerance, lodging and shedding resistance, high yield and technological quality of rice. According to the results of the experiment, 42 varieties in 2018, 28 in 2019 and 39 in 2020 with a total of 109 combinations of 7172 flowers were selected with the participation of varieties and specimens that are resistant to various environmental influences and diseases, high yield, high grain quality. was carried out. The results of the hybridization showed that 118 (or 3.78%) in 2018, 117 (or 5.35%) in 2019, 81 (or 4.35%) in 2020, a total of 316 (or 4.4%) hybrid populations were taken. F1 generation hybrids obtained from the combinations of Chongwang x TShD 15-13 and Chongwang x 227-09, was recommended not to use these combinations in future studies due to the low dominance of “Ruvak” (paniculo is a type of plant inflorescence) length and 1000 grain weight.

The use of superior varieties to increase rice yields in lowland irrigated of Southeast Sulawesi

In order to increase national rice production, the Ministry of Agriculture has released some high yielding varieties. The research was aimed to obtain superior rice varieties adapted to irrigated lowland agro-ecosystems of Southeast Sulawesi. In the first planting season, research was carried out in Olo-oloho Village, Uepai sub district and the second season at the Wawotobi Experimental Garden. Eight varieties were tested, i.e. Inpari 31, Inpari 34, Inpari 35, Inpari 38, Inpari 39, Inpari 41, Inpari 42, Inpari 43 and Mekongga. The variables observed were growth, yield and pest and disease dynamics. The results shows that there was variation growth and yield of the tested varieties. The growth and yield also varied depend on the season. In the first planting season, Inpari 34 and Inpari 43 showed better growth than others, but Inpari 31 resulted the highest rice yield (4.83 t/ha). In the second planting season, only Inpari 34 showed consistent growth, but the variety that had showed the highest yield was Inpari 43 (8.13 t/ha).

Environmental Loading in Pig Farming with Solid-state Anaerobic Digestion and High-yielding Rice Cultivation

Environmental Loading in Pig Farming with Solid-state Anaerobic Digestion and High-yielding Rice Cultivation

Determination of Critical Limit for Copper in Soil-Plant and Grain for Predicting Response of Rice to Copper Application in Soil

ABSTRACT In order to identify critical limit of copper (Cu) in soil, grain, and straw of rice plant, soil samples were collected from twenty; 12, 5, and 3 soil locations of low, medium, and high Cu status from Madurai district, Tamil Nadu, India for pot culture experiment. Based on the results of pot culture experiment, the critical limits of Cu established for straw and grain of rice both by graphical and statistical methods were 8.07 and 5.22 mg kg−1 respectively. Similarly, critical limits of soil available Cu as per the graphical and statistical methods was found to be 0.98 and 0.97 mg kg−1 respectively. Rice plants were highly responded to Cu application in soils below this critical limit whereas soils with Cu greater than 0.98 mg kg−1 did not respond. The grain and straw yield of rice increased with increasing levels of Cu and application of 1 mg kg−1 Cu or 8 kg ha−1 as copper sulfate was sufficient to alleviate the Cu deficiency and also to attain higher yield of rice in the district.

Jian Feng Ma.

Jian Feng Ma.

Keragaman Hama dan Musuh Alami pada Pertanaman Padi (Oryza sativa) di Wawotobi, Sulawesi Tenggara

Obtaining an optimum high yield of rice is confronted by pests that disrupt the productivity. Pest control by applying chemical pesticide is dangerous for the natural enemies therefore, it is necessary to introduce an integrated pest management, based on the natural enemies conservation in the field. Research was conducted in Wawotobi, Konawe Regency, Southeast Sulawesi from Februari to Juni 2019, aimed to understand the diversity of pests and natural enemies in rice crop, particularly arthropods group. The information is useful as a resource base in the implementation of an integrated pest management on rice agroecosystem. Pest observation was done by catching the insects using sweep net and were directly counted at the location. Diversity index of pest was analyzed using Shannor-Weinner equation and insect dominance using Simpson Index of Dominance equation. The utilization of improved rice varieties greatly affected the population of pests and natural enemies. Total of 7 species of pest arthropods and 6 species of natural enemy arthropods were identified at the experimental location. Therefore, the population of pests and natural enemy arthropods were considered at balance. The most dominance pest arthropods was brown planthopper, particularly on Tarabas variety and spider was the most dominant natural enemy.

Genetic Basis of Tiller Dynamics of Rice Revealed by Genome-Wide Association Studies.

A tiller number is the key determinant of rice plant architecture and panicle number and consequently controls grain yield. Thus, it is necessary to optimize the tiller number to achieve the maximum yield in rice. However, comprehensive analyses of the genetic basis of the tiller number, considering the development stage, tiller type, and related traits, are lacking. In this study, we sequence 219 Korean rice accessions and construct a high-quality single nucleotide polymorphism (SNP) dataset. We also evaluate the tiller number at different development stages and heading traits involved in phase transitions. By genome-wide association studies (GWASs), we detected 20 significant association signals for all traits. Five signals were detected in genomic regions near known candidate genes. Most of the candidate genes were involved in the phase transition from vegetative to reproductive growth. In particular, HD1 was simultaneously associated with the productive tiller ratio and heading date, indicating that the photoperiodic heading gene directly controls the productive tiller ratio. Multiple linear regression models of lead SNPs showed coefficients of determination (R2) of 0.49, 0.22, and 0.41 for the tiller number at the maximum tillering stage, productive tiller number, and productive tiller ratio, respectively. Furthermore, the model was validated using independent japonica rice collections, implying that the lead SNPs included in the linear regression model were generally applicable to the tiller number prediction. We revealed the genetic basis of the tiller number in rice plants during growth, By GWASs, and formulated a prediction model by linear regression. Our results improve our understanding of tillering in rice plants and provide a basis for breeding high-yield rice varieties with the optimum the tiller number.

Identification and analysis of low light tolerant rice genotypes in field conditions and their SSR-based diversity in various abiotic stress tolerant lines

The yield potentiality of kharif rice is not completely used even under well-irrigated agro-ecosystem, mainly due to low irradiance by overcast cloud throughout the growing season in eastern India. We observed more than 50% yield reduction compared to the performance of 100 high-yield genotypes for consecutive three years both under open and 30-35% reduced light intensity, mainly by 34%, 25% and 12% reduction of panicle number, grains per panicle and test weight. As per the analysis of variance, genotypic variance explained 39% of the total yield-variation under shade with 58% heritability. Overall, the maintenance of equal panicle per plant in both open and shade has the highest association with shade tolerance. Purnendu, Sashi and Pantdhan19 showed less than 28% yield-reduction by maintenance or even by increasing grain numbers under shade and test weight. On the other hand, maintenance of an equal number of panicle under both situations was the key to the tolerance of Bhasamanik, Sasarang, Rudra and Swarnaprabha. As compared to open, we noticed the improvement of chlorophyll a and b under shade but saw a poor correlation with the shade tolerance index. Comparing the net photosynthesis rate (Pn) in eight genotypes, we found the best tolerant line ranked last with least Pn at low light intensity (400 μmol m-2 s-1). We also identified diverse parental combinations between newly identified shade tolerant and abiotic stress tolerant high-yielding rice lines following diversity analysis using 54 simple-sequence repeats. Thus, the selected tolerant lines from a large set of genotypes with different adjustment ability to keep up high yield under low light intensity can be used for physiological, molecular analysis as well as pyramiding of traits.

Comparison of Growth and Yield Characteristics of Mid-Season Hybrid Rice under Different Yield Levels

Analysis of growth and yield characteristics of rice with different yield levels is very important for the breeding of high-yield rice cultivators. To investigate the yield components’ variation, morphological characteristics of the panicles, leaves, and stems of rice varieties under different yield levels, a two-year field experiment was conducted in Chongqing China. The 20 mid-season Indica hybrid rice varieties were classified into three groups based on yield, comprising high-yield group (HG), mid-yield group (MG), and low-yield group (LG). The main reason for the superior yield of HG is that the varieties of this group had a significantly higher number of effective panicles per unit area than the MG and LG. In plant type factors, the leaf type factors were the most important reason causing yield difference of HG, MG, and LG. The average leaf roll index, average leaf length to width ratio, average leaf base angle, average leaf droop angle, and average leaf pillow distance of the upper three leaves were significantly or significantly negatively correlated with the yield, while the average leaf width, average leaf area, and the average distance of leaf edge were significantly or significantly positively correlated with yield, and the leaf droop angle was the most important plant type factor affecting the yield. Based on these results, we further quantified the plant type factors of HG and constructed an ideal plant type model for high-yield hybrid mid-season rice. Theoretical and practical basis could be provided for breeding mid-season Indica hybrid rice with super-high yield in the future to ensure food security.

Weed control in transplanted rice with post-emergence herbicides and their effects on subsequent rapeseed in Eastern India

Effective broad-spectrum herbicides are needed to address the issues of herbicide resistance and weed shifts in common cropping systems. A field experiment was conducted in 2016 and 2017 in West Bengal, India to compare the performance of three post-emergence herbicides (bispyribac-sodium; fenoxaprop-p-ethyl; penoxsulam) in monsoon rice (Oryza sativa L.) and their residual effects on succeeding rapeseed (Brassica rapa L.). Rice yield loss due to competition with Echinochloa colona (L.) Link, Leersia hexandra Sw., Cyperus iria L., Ludwigia parviflora L., and Monochoria vaginalis (Burm f.) C. Presl. Ex Kunth was 64% compared with weed-free control. Bispyribac-sodium 10% SC applied at 30 g a.i. ha−1 20 days after transplanting reduced weed density over the weedy control, ranging from 37% (M. vaginalis) to 87% (L. hexandra). Fenoxaprop-p-ethyl and penoxsulam applied, respectively, at 86 and 20 g a.i. ha−1 were effective in controlling grasses, but less effective against sedges and broadleaves. Bispyribac-sodium application resulted in highest rice yield (5.45 t ha−1), net return (Indian Rupees 42,677 ha−1), and benefit cost ratio (1.72). Bispyribac-sodium had neither adverse effect on soil microbes nor phytotoxic effect on rice and subsequent rapeseed. We recommend bispyribac-sodium for weed control in transplanted rice under rice-rapeseed system in eastern India.

Methane and nitrous oxide emission characteristics of high-yielding rice field.

As representative varieties of the four phases of the super rice breeding project in China, Lianyoupei 9 (LYP9), Y Liangyou 1 (YLY1), Y Liangyou 2 (YLY2), and Y Liangyou 900 (YLY900) achieved higher yield under optimal cultivation techniques. However, the impact of these high-yield rice varieties on greenhouse gas (GHG) emissions under high-yield cultivation management practices remains poorly understood. In this study, we conducted field experiments to investigate CH4 and N2O emissions from paddies containing four elite rice varieties, managed with field drying at the ineffective tillering stage and alternate wet/dry irrigation at the grain-filling stage. The plants were fertilised with nitrogen (N) at three different rates. The results showed that CH4 emission was highest at the tillering stage. N2O emission flux was dramatically increased by field drying at the ineffective tillering stage, and with the rate of N application. Rice variety was among the most important factors affecting CH4 emission and global warming potential (GWP). N2O emission was mainly related to N application rate rather than rice variety. YLY2 achieved higher yield than LYP9, YLY1, and YLY900, and lower GHG emission than YLY900. Our results indicate that rice variety should be considered as a key factor to reduce GHG emissions from rice paddies under high-yield cultivation practices. Based on its high yield and low GHG emission at the study site, YLY2 may be an optimal rice variety.