Different Varieties Of Rice Research Articles

Evaluation of thiamine and riboflavin in different varieties of rice grown in Kurigram district, Bangladesh

ContextRice is indeed a staple food in many parts of the world, including Bangladesh. This research aimed to evaluate the two essential vitamin levels in different processed rice sunned, parboiled, cooked sunned, cooked parboiled, and washed cooked rice. ObjectiveThe study focused on analyzing the thiamine (vitamin B1) and riboflavin (vitamin B2) contents in 10 different varieties of paddy samples grown in the Kurigram district of Bangladesh. MethodsA high performance liquid chromatographic (HPLC) technique assembled with fluorescence detector was employed for these analyses. Two calibration curves were generated to analyze vitamin B1 and B2 (for thiamine the regression coefficient, r2 = 0.9992 and riboflavin r2 = 0.9989). The study demonstrated a recovery rate of 96.88 % for vitamin B1 and 104.24 % for vitamin B2. Overall, these findings provide valuable insights into the vitamin B1 and B2 contents across different rice samples. Results and conclusionThe results showed that the parboiled samples had the highest thiamine content, ranging from 342.50 ± 0.3 to 673.0 ± 7.5 μg/100 g, compared to the sunned samples, which had a range of 209.5 ± 0.3 to 337.4 ± 4.3 μg/100 g. Conversely, the sunned samples had the highest riboflavin content, ranging from 26.4 ± 0.2 to 59.6 ± 0.3 μg/100 g, while the parboiled samples had a range of 3.0 ± 0.1 to 26.6 ± 0.01 μg/100 g. Additionally, it was observed that the steaming process increased the thiamine content and reduced the riboflavin content in parboiled rice samples but decreased both the thiamine and riboflavin in sunned rice samples. Another study showed a gradual decrease in the levels of both vitamins B1 and B2 in sunned, cooked sunned and washed cooked sunned rice samples. SignificanceThese findings provide valuable insights into the impact of processing methods, such as parboiling and steaming, on the thiamine and riboflavin contents in rice. The results suggest that parboiled rice may be a preferable choice for individuals seeking higher thiamine content in their diet, while sunned rice may contain higher levels of riboflavin. The results shed light on the nutritional profiles of different rice varieties and highlight the potential impact of processing techniques on the vitamin content of rice.

Simultaneously predicting SPAD and water content in rice leaves using hyperspectral imaging with deep multi-task regression and transfer component analysis.

Water content and chlorophyll content are important indicators for monitoring rice growth status. Simultaneous detection of water content and chlorophyll content is of significance. Different varieties of rice show differences in phenotype, resulting in the difficulties of establishing a universal model. In this study, hyperspectral imaging was used to detect the Soil and Plant Analyzer Development (SPAD) values and water content of fresh rice leaves of three rice varieties (Jiahua 1, Xiushui 121 and Xiushui 134). Both partial least squares regression and convolutional neural networks were used to establish single-task and multi-task models. Transfer component analysis (TCA) was used as transfer learning to learn the common features to achieve an approximate identical distribution between any two varieties. Single-task and multi-task models were also built using the features of the source domain, and these models were applied to the target domain. These results indicated that for models of each rice variety the prediction accuracy of most multi-task models was close to that of single-task models. As for TCA, the results showed that the single-task model achieved good performance for all transfer learning tasks. Compared with the original model, good and differentiated results were obtained for the models using features learned by TCA for both the source domain and target domain. The multi-task models could be constructed to predict SPAD values and water content simultaneously and then transferred to another rice variety, which could improve the efficiency of model construction and realize rapid detection of rice growth indicators. © 2024 Society of Chemical Industry.

Sustainable improvement of rice growth under salinity stress using an endophytic fungus-based biofertilizer

Salinity stress adversely affects rice (Oryza sativa L.) growth, development and overall productivity. Multiple strategies have been implemented to enhance the resilience of rice plants, enabling them to grow better in saline environments. Use of biofertilizers, a sustainable alternative to chemical fertilizers, has gained significant attention in modern agriculture due to their potential to improve soil fertility, enhance crop productivity, and mitigate environmental concerns. Biofertilizers encompass a diverse group of microorganisms, including bacteria, fungi, and algae, which interact with plants through various mechanisms. These beneficial microbes have been reported to convert atmospheric nitrogen into plant-available forms and break down insoluble phosphates and zinc complexes in the soil. Additionally, they can also produce growth regulators, enhance nutrient availability, and protect plants against pathogens. In our previous study, a salt-tolerant endophytic fungus isolated from the halophytic wild rice, Oryza coarctata, was identified as Aspergillus welwitschiae Ocstreb1 by whole genome sequence analysis. During the in-vitro experiments, the endophyte showed several plant growth promoting activities such as, zinc and phosphate solubilization, siderophore, IAA, and ACC-deaminase production, nitrogen fixation, etc. in both normal and 900 mM salt stress. In this study, the endophyte was used to formulate a biofertilizer in combination with talcum powder to enhance the growth and yield of rice plants under salinity stress. This research investigated the effectiveness of the biofertilizer in four distinct salinity tanks under both non-saline and 6 dS/m saline conditions, each containing three different varieties of rice. Treatment of BRRI dhan28 (BD-28), BRRI dhan67 (BD-67) and BRRI dhan87 (BD-87) rice plants with the formulated biofertilizer significantly enhanced their yield in both non-saline and saline conditions. Among the three rice varieties, BD-28 showed the highest significant (p<0.05) yield increase, with 104.20% under normal conditions and 3080.56% under salt stress. BD-67 exhibited a 45.15% increase in normal conditions and 153.64% under salt stress (P<0.05). BD-87 showed a significant yield increase only under salt stress, at 293.63% (p<0.05). From the results of the study, it can be proposed that the formulated biofertilizer is a potential eco-friendly and cost-effective solution to improve cultivation and yield of rice in the highly saline coastal regions of Bangladesh. Bioresearch Commu. 10(2): 1474-1481, 2024 (July)

A novel method combining deep learning with the Kennard-Stone algorithm for training dataset selection for image-based rice seed variety identification.

Different varieties of rice vary in planting time, stress resistance, and other characteristics. With advances in rice-breeding technology, the number of rice varieties has increased significantly, making variety identification crucial for both trading and planting. This study collected RGB images of 20 hybrid rice seed varieties. An enhanced deep super-resolution network (EDSR) was employed to enhance image resolution, and a variety classification model utilizing the high-resolution dataset demonstrated superior performance to that of the model using the low-resolution dataset. A novel training sample selection methodology was introduced integrating deep learning with the Kennard-Stone (KS) algorithm. Convolutional neural networks (CNN) and autoencoders served as supervised and unsupervised feature extractors, respectively. The extracted feature vectors were subsequently processed by the KS algorithm to select training samples. The proposed methodologies exhibited superior performance over the random selection approach in rice variety classification, with an approximately 10.08% improvement in overall classification accuracy. Furthermore, the impact of noise on the proposed methodology was investigated by introducing noise to the images, and the proposed methodologies maintained superior performance relative to the random selection approach on the noisy image dataset. The experimental results indicate that both supervised and unsupervised learning models performed effectively as feature extractors, and the deep learning framework significantly influenced the selection of training set samples. This study presents a novel approach for training sample selection in classification tasks and suggests the potential for extending the proposed method to image datasets and other types of datasets. Further exploration of this potential is warranted. © 2024 Society of Chemical Industry.

Higher adiposity predicts greater intra-individual inconsistencies in postprandial glycemic measurements-an analysis of three randomized controlled trials in Asian populations.

Acute glycemic responses offer important insights into glucose homeostasis although the repeatability of these measurements particularly in Asian populations remains unclear. This research aimed to critically investigate the inconsistencies of the postprandial glycemic profile within individuals, and identify potential variables predicting greater inconsistencies. This was a secondary analysis of three randomized controlled trials which fed subjects with glucose (and other carbohydrate-rich foods), and measured postprandial blood glucose at regular intervals. Intra-individual rank-order consistency in the glycemic profile between acute glucose treatments was evaluated and compared against demographic, anthropometric and cardio-metabolic health related indicators to delineate potential confounding variables. Correlations between the incremental area under curve at 120 min (iAUC120 min) for glucose and the carbohydrate-rich foods were further explored. Rank-order consistency was identified to be moderate, with intra-individual inconsistencies marginally lower than inter-individual inconsistencies. Notably, greater inconsistencies within individuals were directly correlated with BMI and fat-mass index (P < 0.01) albeit non-significant for age, ethnicity, and other cardio-metabolic health-related risk indicators. Across the trials, there were positive monotonic correlations between the iAUC120 min for glucose and simple sugars (sucrose, isomaltulose), as well as different varieties of rice (jasmine white, Bapatla brown, Bapatla white; p < 0.05). However, there were a lack of associations between iAUC120 min for glucose with pastas (semolina and wholegrain penne, spaghetti) and mee pok noodles. There are inherent inconsistencies in postprandial glycemic measurements within individuals, particularly among those with higher adiposity. These confounders need to be kept in mind for appropriate and meaningful interpretations of glycemia.

Non-destructive Machine Vision System based Rice Classification using Ensemble Machine Learning Algorithms

Aims and Background: Agriculture plays a major role in the global economy, providing food, raw materials, and jobs to billions of people and driving economic growth and poverty reduction. Rice is the most widely consumed crop domestically, making it a particularly important crop for rural populations. The exact number of rice varieties worldwide is difficult to determine as new varieties are constantly being developed and marketed. Objectives: The most common method of rice variety identification is a comparison of its physical and chemical properties to a reference collection of known types. Methodology: This is a relatively quick and cost-effective approach that can be used to accurately differentiate between distinct varieties. In some cases, genetic testing may be used to confirm the identity of a variety, although this technique is more expensive and time-consuming. However, we can also utilize efficient, precise, and cost-effective digital image processing and machine vision techniques. Results: This study describes different types of ensemble methods, such as bagging (Decision Tree, Random Forest, Extra Tree), boosting (AdaBoost, Gradient Boost, and XGBoost), and voting classifiers to classify five different varieties of rice. Extreme Gradient Boosting (XGBoost) has achieved the highest average classification accuracy of 99.60% among all the algorithms. Conclusion: The findings of the performance measurement indicated that the proposed model was successful in classifying the various varieties of rice.

The Rapid Non-Destructive Differentiation of Different Varieties of Rice by Fluorescence Hyperspectral Technology Combined with Machine Learning.

A rice classification method for the fast and non-destructive differentiation of different varieties is significant in research at present. In this study, fluorescence hyperspectral technology combined with machine learning techniques was used to distinguish five rice varieties by analyzing the fluorescence hyperspectral features of Thai jasmine rice and four rice varieties with a similar appearance to Thai jasmine rice in the wavelength range of 475-1000 nm. The fluorescence hyperspectral data were preprocessed by a first-order derivative (FD) to reduce the background and baseline drift effects of the rice samples. Then, a principal component analysis (PCA) and t-distributed stochastic neighborhood embedding (t-SNE) were used for feature reduction and 3D visualization display. A partial least squares discriminant analysis (PLS-DA), BP neural network (BP), and random forest (RF) were used to build the rice classification models. The RF classification model parameters were optimized using the gray wolf algorithm (GWO). The results show that FD-t-SNE-GWO-RF is the best model for rice classification, with accuracy values of 99.8% and 95.3% for the training and test sets, respectively. The fluorescence hyperspectral technique combined with machine learning is feasible for classifying rice varieties.

Metabolome regulation and restoration mechanism of different varieties of rice (Oryza sativa L.) after lindane stress

There is a lack of studies on the ability of plants to metabolize chlorinated organic pollutants (COPs) and the dynamic expression changes of metabolic molecules during degradation. In this study, hybrid rice Chunyou 927 (CY) and Zhongzheyou 8 (ZZY), traditional rice subsp. Indica Baohan 1 (BH) and Xiangzaoxian 45 (XZX), and subsp. Japonica Yangjing 687 (YJ) and Longjing 31 (LJ) were stressed by a typical COPs of lindane and then transferred to a lindane-free culture to incubate for 9 days. The cumulative concentrations in the roots of BH, XZX, CY, ZZY, YJ and LJ were 71.46, 65.42, 82.06, 80.11, 47.59 and 56.10 mg·kg−1, respectively. And the degradation ratios on day 9 were 87.89 %, 86.92 %, 94.63 %, 95.49 %, 72.04 % and 82.79 %, respectively. On the 0 day after the release of lindane stress, the accumulated lindane inhibited the normal physiological activities of rice by affecting lipid metabolism in subsp. Indica BH, amino acid metabolism and synthesis and nucleotide metabolism in hybrid CY. Carbohydrate metabolism of subsp. Japonica YJ also was inhibited, but with low accumulation of lindane, YJ regulated amino acid metabolism to resist stress. With the degradation of lindane in rice, the amino acid metabolism of BH and CY, which had high degradation ratios on day 9, was activated to compound biomolecules required for the organism to recover from the damage. Amino acid metabolism and carbohydrate metabolism were disturbed and inhibited mainly in YJ with low degradation ratios. This study provides the difference of the metabolic capacity of the metabolic capacity of different rice varieties to lindane, and changes at the molecular level and metabolic response mechanism of rice during the metabolism of lindane.

Morphological, Structural, Thermal, Pasting, and Digestive Properties of Starches Isolated from Different Varieties of Rice: A Systematic Comparative Study.

The aim of this study was to compare the properties of isolated starches from ten commonly consumed rice varieties in China and to investigate their possible association. In addition, principal component analysis (PCA) and correlation analysis were performed to demonstrate the weight or relevance of different properties. The starch granules had an irregular polyhedral structure. The crystalline structure had an orthogonal arrangement, which is characteristic of A-type starch with nanocrystals with an orthorhombic crystal structure. In addition, higher levels of rapidly digestible starch (72.43 to 74.32%) and resistant starch (2.27 to 2.3%) were found in glutinous rice starch. The highest content of slowly digestible starch (59.48%) was found in starch isolated from black rice, which may be an ideal rice variety for controlling blood glucose and weight. Starch isolated from red Hani terrace rice showed the highest thermal stability during cooking and the highest resistance to a high shear force treatment. In addition, the PCA suggests that the amylose content of starch largely determines the functional properties of starch and positively correlates with the peak viscosity and setback viscosity of the starch pasting. The results of this study will enrich the scientific knowledge of various rice starches and promote their application in the food industry and other industries.

Optimizing extrusion processes: Development of extrudates utilizing ISP and wheat gluten, incorporating diverse concentrations of rice or legume varieties

The physiochemical, textural and nutritional properties of novel extrudates generated from various kinds of rice and legume (beans) varieties were comprehensively evaluated and compared in this study. The developed extruded products were composed of 5 %, 10 %, 15 %, or 20 % of different varieties of rice, including brown rice (R1), Asemi (R2), solchanmi (R3), sechanmi (R4), sejongchal (R5), and seosi 1 (R6), and legumes varieties including soybean (B1), chickpea (B2), great northern bean (B3), pea (B4), lentil (B5), and black bean (B6). Visible appearance analysis reveals that legumes (beans) and rice extrudates appeared more compact as the concentration of ingredients increased. Meanwhile, the integrity index decreased as the concentration level of treatment group content decreased (p < 0.05). A marginal difference in textural values is observed between legume (beans) and rice varieties compared to the control. Furthermore, analysis of nutritional composition indicates that the crude protein and water holding capacity (WHC) decreased as the concentration of both extrudates groups decreased (p < 0.05). This study provides useful information regarding the optimization of the extrusion process and the development of various extrudates by comparative analysis of rice- and legume-based extrudates.

Floods stress in lowland rice production: experiences of rice farmers in Kilombero and Lower-Rufiji floodplains, Tanzania

The resilience of rice production to floods is a crucial aspect of agricultural development in flood-prone regions. However, little is known about the farming practices and challenges of rice farmers in two river basins in Tanzania: Lower-Rufiji and Kilombero, where rice is the main crop grown. This study aimed to investigate the experiences of farmers in these two rice-growing floodplains regarding the impact of floods on lowland rice production and farmer livelihoods, and the strategies they use to cope with floods. The study used a mixed-methods approach that involved household surveys, key informant interviews, and transect walks to collect data from 180 rice farmers and 14 experts and community leaders. The data analysis revealed that floods were the dominant stressor affecting rice production, occurring mostly during the long rainy season and experienced by all farmers in both locations. Floods not only caused significant crop losses, especially in Lower-Rufiji where farmers reported losing between 75 and 100% of their yield in cases of extreme floods, but also made it difficult to establish and manage crops, leading to crop land abandonment. Floods also affected the livelihoods of rice farmers by forcing them to abandon, rent, or sell their farms. Coexistence of floods with other biotic and abiotic stresses such as crop diseases and droughts also limited the use of short maturing high yielding rice varieties. Farmers have adopted on-farm strategies such as adjusting planting schedules, using different varieties of rice, changing to other crops or activities after the floods to cope with floods, but these practices face numerous challenges. The study recommends the development of early warning systems, breeding for flood-tolerant rice varieties, introgression of tolerance traits to multiple stresses and improving crop establishment methods to enhance the resilience of farmers to floods and other extreme climate events.

IDENTITY, ETHNIC CUISINE, AND COOKING TECHNIQUES OF THE TAI-KHAMYANG TRIBE IN ASSAM, INDIA

The traditional knowledge of the Tai-Khamyang, a small tribe in Assam, has been presented, with a focus on their food sources, cooking methods, identity, and sociocultural significance. The use of wild plants as healthy and nutritious vegetables is very common among the Tai-Khamyang. These are cooked with rice, which is the most important crop consumed by this community, whether as a sweet and salty dessert or as a staple diet prepared from it. Different varieties of rice (Oryza sativa) are cultivated, viz., lahi, bora, joha and black rice, and consumed in various forms. Bora rice is primarily consumed by making snacks and desserts from it. Lahi rice balls wrapped in Phrynium imbricatum leaves are especially served at special occasions and ceremonies. Fermented foods such as bamboo shoot are commonly used as accompaniments for rice dishes. This article focuses on the use of various plants as ingredients in traditionally prepared foods which reflects the unique identity of this minor group of people.

Comparative Analysis of Amylase Enzyme Produced by Aspergillus niger Using Rice and Maize Bran as Substrates

Amylase is used in the degradation of starch-containing materials into its simpler constituents. This study was aimed at comparing amylase production by Aspergillus niger isolated from different sources on different varieties of rice and maize bran. Different strains of A. niger were isolated from different sources and were identified using cultural, morphological and molecular characteristics. A. niger USGB:1024 isolated from soil obtained from a maize mill and A. niger BGSU:17-00030 isolated from spoiled tomato were used for amylase enzyme production as both gave positive results during screening. Amylase enzyme was produced using 15g of substrates, temperature 30 C, pH 6 and inoculum density of 1 ×106. A. niger USGB:1024 was found to produce an amylase enzyme with the highest activity (3.15±0.1 IU) on Chinese rice bran at fermentation day 5. A. niger BGSU:17-00030 also produced amylase enzyme with the highest activity (1.46±0.01 IU) on Chinese rice bran at 5 days of fermentation. The result has shown that A. niger USGB:1024 produced amylase enzyme with the highest activity than A. niger BGSU:17-00030.

Formulation and Antioxidant Activity Test of Rice Bran Extract Cream from Two Varieties of White Rice

Rice bran extract contains high antioxidant compounds. Formulation and antioxidant activity testing of cream preparations containing rice bran extract has been carried out. This study aims to formulate and evaluate cream preparations containing bran extract from two varieties of white rice and their antioxidant activity. The white rice varieties used were the Kalpatali variety (FI) and the Rice 64 (FII) variety. There were three cream formulas, namely the basic formula (F0) and the formula containing rice bran extract with a concentration of 3.1% each (FI and FII). Evaluation of cream preparations included organoleptic test, homogeneity, pH, washability, stability, irritation test, and antioxidant activity test. This study showed that FI has an antioxidant activity of 87.23% and FII has an antioxidant activity of 64.08%. Different varieties of rice show differences in antioxidant activity in cream preparations containing bran extract. The best formula is FI which has good physical properties and higher antioxidant activity compared to FII.

Influence of Foliar Application of Zinc on Growth and Yield in Different Varieties of Rice (Oryza sativa L.) and Yield Validation Using SPSS Model

Agronomy Department, Farm, Sam Higginbottom University of Agriculture, Technology, and Sciences, Prayagraj (U.P.), India. to research the effects of zinc treatment on rice (Oryza sativa L.) growth and yield. The medications include the verities MTU-7029, BPT -5204, and RNR15048, as well as zinc concentrations of 0.2%, 0.3%, and 0.4%. The pH of the soil in the experimental plot was 7.8, the texture was sandy loamy, and the amount of organic carbon was low (0.35%). The larger plant height (117.68 cm), greater number of tillers per hill (13.64), Application of RNR-15048 + ZnSo4 - 0.4% significantly increased plant dry weight (55.47 g/plant), number of panicles/hill (10.01), number of grains/panicle (141.37), 1000 seed weight (22.27 gm), grain yield (6.43 t/ha), and stove yield (12.11 t/ha). Higher B:C ratio (2.37) and higher gross return (INR 1,52,860/ha), net return (INR 1,07,531/ha), and net return (INR 1,07,531/ha) were also noted in treatment-9 (RNR-15048 + ZnSo4 - 0.4%).

Enrichment of Heavy Metals by Different Varieties of Rice

Pot experiment was carried out to compare the difference of Cr accumulation and distribution in different organs of 3 rice cultivars under different treatment of Cr. The results showed that the average values of Cr concentration in root, stem, leaf, chaff and grain of all cultivars were 7.63~141.09, 2.29~8.58, 14.01~39.93, 3.65~5.21 and 0.46~0.92 mg•kg-1, respectivly. Compared with the control, the accumulation and translocation of Cr in rice was significantly affected by the stress of exogenous Cr. At control treament, most of Cr was distributed in leafs, but the proportion of Cr in roots was significantly increased under the stress of exogenous Cr. At the same Cr application rate level, the distribution of Cr in II You-838 and Yixiangyou-10 followed the pattern: root &gt; leaf &gt; chaff &gt; stem &gt; grain, while it showed root &gt; leaf &gt; stem &gt; chaff &gt; grain in Jinfuyou-270. The distribution of Cr in different parts of rice was very uneven for three rice cultivars. With increasing Cr treatment levels, the proportion of Cr in roots was increasing, while a decrease was observed in aerial parts, and their bioconcentration factors (BCF) and translocation factors (TF) of Cr also declined. The transport ability of Cr from root to leaf was stronger, but weak ability in translocating Cr from root to stem, chaff and grain. There were different in Cr accumulation and distribution in organs of 3 rice cultivars. The falling sequence of accumulation and translocation ability of Cr in rice was Jinfuyou-270 &gt; Yixiangyou-10 &gt; II You-838. The Cr concentration in the grain of Jinfuyou-270 was 0.70~0.92 mg•kg-1, which was quite close to the national food heavy metal limits hygienic standard.

Пирикуляриоз риса и методы борьбы

Поражения риса, вызываемые Magnaporthe grisea, являются основной болезнью, наносящей ущерб почти во всех странах, выращивающих рис. Экономическая значимость риса огромная, для более по-ловины населения мира рис служит как основной источник калорий. В годы эпифитотий пирикуляри-оз может нанести разрушительное влияние на производство риса в мире. На данный момент этот па-тоген превратился в новаторскую модельную систему для исследования взаимодействия «хозяин–патоген». Вспышка заболевания зависит от климатических условий различных регионов. Возникнов е-ние болезни и симптомы варьируются от страны к стране. Восприимчивые сорта несут огромные по-тери урожая риса. Основной причиной нарушения устойчивости риса к пирикуляриозу является высокая способность патогена к изменчивости. Вирулентные патотипы вызывают тяжелую форму заболеваемости. При исследовании патогенности возбудителя можно определить патотипы, используя коллекцию различных сортов риса, которые обычно отличаются друг от друга, неся различные гены устойчивости. В настоящее время селекционерами мира широко практикуется полигенная (пирамидирование генов) устойчивость вместо традиционной моногенной. Выращивание сортов, полученных путем скрещивания устойчивых сортов с восприимчивыми, с использованием молекулярного контроля перехода генов на каждом этапе, может служить высокоэффективным методом борьбы с пирикуляриозом. Генетическая гетерогенность M. grisea должна учитываться при скрининге устойчивых к пирикуляриозу генотипов риса с помощью морфологического, фитопатологического анализов и молекулярной характеристики.

Machine Vision Approach for Identification of Four Variant Pakistani Rice Using Multi-Features Dataset

Crops are the most important and beneficial food source in Pakistan. The demand for food has been an increase in Pakistan due to population growth. Pakistan produced 7,410 million tons of rice according to the financial year survey 2020 (FYS-2020). Pakistani rice has been cultivated in 3,304 hectares of the agricultural land zone, and it is also export around the world. Rice is also increased by 0.6% Gross Domestic Product (GDP) of Pakistan (FYS-2020). The old and manual process of rice classification is more expensive and time-consuming. In this study, we describe a machine vision approach for rice identification. We use four different varieties of rice for the experimental process such as Pakei_Kaynat, Kaynat_Kauchei, and Kauchei_Super_Banaspati and Tootaa_Kauchei (P1, P2, P3, and P4). The 100 images dataset have been used for practical work and total calculated of 400 (4 x 100) image of rice. The different process has been deploying on available datasets such as introduction, preprocessing methodology, and result discussion. A quality enhancement technique has been implementing for clarifying between rice color and shape sampling, and it is also converted color image in gray scale level. Every image has been employing six different non-overlapping regions of interest (ROI’s) and calculated a total of 2400 (6 x 400) ROI’s. Binary (B), Histogram (H) and Texture (T) features have been implemented and extract 43 features on each ROI’s and total calculated 103,200 (2400 x 43) machine learning (ML) features. Best First Search (BFS) Algorithm was used for feature optimization. Different ML classifiers are implementing for experimental process namely; Function Multi-Layer-Perception, Function SMO, Random Tree, J48 Tree, Meta Classifier via Regression and Meta Bagging. The Function Multi-Layer-Perception overall accuracy (OA) has describe better accuracy result is 99.8333%.

Candidate Genes Involved in Tolerance to Fenoxaprop-P-Ethyl in Rice Induced by Isoxadifen-Ethyl Hydrolysate

The metabolic resistance of plants to herbicides is similar to the herbicide metabolism process accelerated by safeners. The tolerance to fenoxaprop-P-ethyl (FE) is distinct among different varieties of rice in which phytotoxicity forms easily, resulting in the restricted use of FE in paddy. Safener effectively resolves this issue. This study showed that rice 9311 and Meixiangzhan No. 2 (MXZ) had different tolerance mechanisms to FE. Isoxadifen-ethyl hydrolysate (IH) alleviated FE the inhibition of rice growth. Transcriptome sequencing revealed numerous differentially expressed genes (DEGs) between the two varieties. A total of 31 metabolic enzyme genes related to herbicide detoxification were screened by analyzing the DEGs in different rice varieties or treatments. The results of the quantitative reverse transcription polymerase chain reaction indicated that 12 genes were potential metabolic genes resistant to FE in rice. Additionally, the enhanced expression of GSTU6, DIMBOA UGT BX8, and ABCG39 was confirmed to be induced by safener. Taken together, our results demonstrated that the induced expression of these three genes might be crucial for resistance to herbicide phytotoxicity in crops. These results may help us to understand herbicide metabolism in crops and to develop novel strategies for the safe use of herbicides.

Rapid Classification of Rice Varieties using (ATIR-FTIR) Spectroscopy and Multivariate Chemometrics

Rice is one of the most commonly consumed cereal crops in the world. Rice varieties are difficult to identify, especially when different varieties of rice are mixed (cheap varieties mixed with expensive ones) and packaged for consumers to purchase. Quality control is of great concern in the food industry in that food products are sorted and graded distinctly depending on the quality parameters after harvest. Fourier Transformed Infrared-Attenuated Total Reflectance (FTIR-ATR) Spectroscopy and multivariate chemometrics were applied to classify four rice varieties bought from local shops in the UK for this study. A total of 80 samples were analyzed using Principal component analysis and hierarchical cluster analysis. This method was developed with the aim of Classifying rice varieties as fast as possible without sample alteration. The spectral profile of the rice varieties was obtained at a wave number range of 4000-450 cm-1. Result shows that FTIR-ATR spectroscopy could be used successfully to discriminate rice varieties. When PCA and HCA were used to analyze the spectra data, cluster were identified with few samples of the rice varieties mixed up in the four different clusters identified. Based on this analysis, a suggestion was therefore made that parameters used for this study were not sensitive enough to produce the required outcome and since rice varieties have the same component, this makes it difficult to discriminate them. Although FTIR-ATR has not been widely applied in the discrimination of rice varieties. Multivariate statistical analysis has been successful. The findings of this study therefore pave the way for further research.