Effect of Rice Cultivar, Type, Form, and Moisture Content on the Angle of Repose

2019 ◽  
Vol 35 (4) ◽  
pp. 361-368
Author(s):  
Hu Shi ◽  
Terry J. Siebenmorgen
Keyword(s):  
Moisture Content ◽  
Hybrid Rice ◽  
Brown Rice ◽  
Rice Cultivar ◽  
The United States ◽  
Angle Of Repose ◽  
Rice Cultivars ◽  
Milled Rice ◽  
Rough Rice ◽  
Rice Samples

Abstract.The angle of repose (AoR) is a primary characteristic determining the flowablity of grains and thus is an important property for designing rice handling and storage facilities. The aim of this study was to evaluate the AoR of contemporary rice cultivars grown in the United States. An apparatus was constructed to measure both the emptying and piling AoR of rice samples. The effect of rice cultivars (pureline and hybrid), rice types (long-, medium-, and short-grain rice), rice forms (rough, brown, head, and broken milled rice), and moisture content on the AoR of rice were evaluated. Results indicated that all of these factors significantly affected the AoR of rice. The piling AoR was significantly less than the emptying AoR. Hybrid rice cultivars tended to have greater AoR than purelines, which was attributed to the pubescence characteristic of their hulls. The emptying AoR and piling AoR of tested long-grain rough rice cultivars at 12% to 21% moisture content were in the range of 32.7° to 39.7° and 29.6° to 36.9°, respectively.Increasing the moisture content of long-grain rough rice led to greater AoR, possibly due to increased cohesion of rice kernels. Long-grain rough rice cultivars had slightly lesser AoR than those of medium- and short-grain rice cultivars. Among all tested rice forms, brown rice had the least AoR. Head and broken milled rice had approximately the same AoR as rough rice. Keywords: Angle of repose, Bridging, Flowablity, Friction, Rice.

scholarly journals NIR Spectroscopy Detects Chlorpyrifos-Methyl Pesticide Residue in Rough, Brown, and Milled Rice

2020 ◽  
Vol 36 (6) ◽  
pp. 983-993
Author(s):  
Fatima S Rodriguez ◽  
Paul R Armstrong ◽  
Elizabeth B Maghirang ◽  
Kevin F Yaptenco ◽  
Erin D Scully ◽  
...  
Keyword(s):  
Pesticide Residue ◽  
Brown Rice ◽  
Nir Spectroscopy ◽  
List Type ◽  
Pesticide Level ◽  
Milled Rice ◽  
Near Infrared Reflectance ◽  
Independent Validation ◽  
Rough Rice ◽  
Rice Samples

HighlightsNIR spectroscopy detects quantitative and qualitative levels of chlorpyrifos-methyl residues in bulk rice.Levels of chlorpyrifos-methyl residues in bulk rice can be differentiated at 78% to 100% correct classification.Important NIR wavelengths for chlorpyrifos-methyl residue detection were identified.NIR spectroscopy can be used to detect maximum residue levels of chlorpyrifos-methyl pesticide in rice.Abstract. A rapid technique that uses near-infrared reflectance (NIR) spectroscopy for simultaneous qualitative and quantitative determination of the presence of varying concentrations of chlorpyrifos-methyl in bulk samples of rough, brown, and milled rice was established. Five rice varieties, free of pesticides, obtained from RiceTec Inc. and USDA-ARS Arkansas experimental field were used as rough rice samples and also processed to obtain corresponding brown and milled rice. Rice samples were treated with StorcideTM II containing varying levels of the active ingredient, chlorpyrifos-methyl: 0, 1.5, 3, 6, 9, and 12 ppm for rough rice, 0, 0.75, 1.5, 3, 4.5, and 6 ppm for brown rice, and 0, 0.1, 0.2, 0.4, 0.6, and 0.8 ppm for milled rice. Concentrations of chlorpyrifos-methyl were verified using gas chromatography-mass spectrometry analyses. A commercial NIR spectrometer (950-1650 nm wavelength range) was used to obtain spectra of bulk samples. Using partial least squares analysis for quantitative analysis, independent validation showed that chlorpyrifos-methyl residues in rough, brown, and milled rice are predictable with R2 ranging from 0.702 to 0.839 and standard error of prediction (SEP) of 1.763 to 2.374 for rough rice, R2 ranging from 0.722 to 0.800 and SEP of 0.953 to 1.168 for brown rice, and R2 ranging from 0.693 to 0.789 and SEP of 0.131 to 0.164 for milled rice. For qualitative analysis obtained using discriminant analysis, rough rice samples with concentrations of 0, 1.5, and 3 ppm pooled as low pesticide level (LPL) is distinguishable to 6, 9, and 12 ppm which were pooled as high pesticide level (HPL). Similarly, for brown and milled rice, the lower three concentrations pooled as LPL is distinguishable from the higher three concentrations pooled as HPL. Independent validation showed overall correct classifications ranging from 77.8% to 92.6% for rough rice, 79.6% to 88.9% for brown rice, and 94.4% to 100% for milled rice. Keywords: Food safety, Grain quality, NIR spectroscopy, Pesticide residue, Rice.

Isolation and Identification of Lipolytic Microorganisms Found on Rough Rice from Two Growing Areas

1978 ◽  
Vol 41 (1) ◽  
pp. 28-30 ◽  
Author(s):  
ANTHONY J. DeLUCCA ◽  
STEPHEN J. PLATING ◽  
ROBERT L. ORY
Keyword(s):  
Fatty Acids ◽  
Brown Rice ◽  
Plate Count ◽  
Isolation And Identification ◽  
Lipolytic Action ◽  
Rough Rice ◽  
Colony Forming Units ◽  
Rice Samples ◽  
Lipolytic Microorganisms ◽  
Rice Oil

Rice bran and whole brown rice are currently underutilized because free fatty acids are formed from rice oil during storage. Rough rice from two growing areas was tested for presence of lipolytic microorganisms that could release these fatty acids. Approximately 10% of the total bacterial plate count (4 × 106/g for Louisiana and 12 × 106/g for the Arkansas rice samples) were lipolytic. Upon testing, most were classified as nonsaccharolytic, alkali-producing pseudomonads. The average mold plate count for the Louisiana sample was 2 × 103 colony forming units (cfu)/g and 5 × 103 cfu/g for the Arkansas sample. All molds isolated showed various amounts of lipolytic action, as determined by the size of the lipolytic zone. The molds were generally isolated more from the Louisiana than from the Arkansas rice. Alternaria and Helminthosporium species, the most prevalent molds, were found in all samples.

Effect of Storage Moisture Content on Milling Characteristics of Rough Rice

2019 ◽  
Vol 62 (4) ◽  
pp. 1011-1019
Author(s):  
Bhagwati Prakash ◽  
Terry J. Siebenmorgen ◽  
Kristen E. Gibson ◽  
Shweta Kumari
Keyword(s):  
Moisture Content ◽  
Rice Yield ◽  
Surface Lipid ◽  
Milled Rice ◽  
Financial Return ◽  
Head Rice ◽  
Rough Rice ◽  
Head Rice Yield ◽  
Milling Characteristics ◽  
The Mean

Abstract. Rough rice in the Mid-South U.S. is typically stored and milled at a moisture content (MC) between 12% and 13% on a wet basis. Drying harvested rice to lesser MCs requires increasingly greater energy and reduces the overall mass of rice, both of which translate into lesser financial return for the crop. Considering these disadvantages of drying and storing rice at lesser MCs, farmers and grain handlers have been interested in exploring storing rice at slightly greater MCs. The current study was undertaken to evaluate the effect of storing rice at five MCs (11%, 12%, 13%, 14%, and 15%) on milling characteristics, particularly surface lipid content (SLC), milled rice yield (MRY), and head rice yield (HRY); additionally, the effects of storing rice at two storage temperatures (25°C and 35°C) and several storage durations (up to one year) on milling characteristics were investigated. Five long-grain rice lots were harvested in 2016 and 2017 from several locations in Arkansas; rice from each lot was gently dried to the target MCs and then stored in sealed glass jars at selected temperatures. With an increase in storage MC, shorter milling durations were needed to achieve a given SLC, which could potentially reduce the cost of the milling operation. However, rice samples stored at greater MCs were observed to have lesser HRYs, which could reduce the economic value of rice. The mean HRYs of the 15% MC samples were 4.8 to 9.1 percentage points less than the mean HRYs of the 12% MC samples. This study quantifies the milling characteristics of rice when stored for various durations at different MCs and temperatures. Overall, these data will allow the rice industry to make informed decisions related to storage conditions of rice, specifically storage MC. Keywords: Head rice yield, Milling, Moisture content, Rice, Storage.

scholarly journals A Combined Method of Image Processing and Artificial Neural Network for the Identification of 13 Iranian Rice Cultivars

Agronomy ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 117 ◽  
Author(s):  
Yousef Abbaspour-Gilandeh ◽  
Amir Molaee ◽  
Sajad Sabzi ◽  
Narjes Nabipur ◽  
Shahaboddin Shamshirband ◽  
...  
Keyword(s):  
Neural Network ◽  
Image Processing ◽  
Brown Rice ◽  
Principal Component ◽  
Rice Cultivar ◽  
Rice Cultivars ◽  
Texture Properties ◽  
Effective Components ◽  
Significant Difference ◽  
Artificial Neural

Due to the importance of identifying crop cultivars, the advancement of accurate assessment of cultivars is considered essential. The existing methods for identifying rice cultivars are mainly time-consuming, costly, and destructive. Therefore, the development of novel methods is highly beneficial. The aim of the present research is to classify common rice cultivars in Iran based on color, morphologic, and texture properties using artificial intelligence (AI) methods. In doing so, digital images of 13 rice cultivars in Iran in three forms of paddy, brown, and white are analyzed through pre-processing and segmentation of using MATLAB. Ninety-two specificities, including 60 color, 14 morphologic, and 18 texture properties, were identified for each rice cultivar. In the next step, the normal distribution of data was evaluated, and the possibility of observing a significant difference between all specificities of cultivars was studied using variance analysis. In addition, the least significant difference (LSD) test was performed to obtain a more accurate comparison between cultivars. To reduce data dimensions and focus on the most effective components, principal component analysis (PCA) was employed. Accordingly, the accuracy of rice cultivar separations was calculated for paddy, brown rice, and white rice using discriminant analysis (DA), which was 89.2%, 87.7%, and 83.1%, respectively. To identify and classify the desired cultivars, a multilayered perceptron neural network was implemented based on the most effective components. The results showed 100% accuracy of the network in identifying and classifying all mentioned rice cultivars. Hence, it is concluded that the integrated method of image processing and pattern recognition methods, such as statistical classification and artificial neural networks, can be used for identifying and classification of rice cultivars.

Artificial Neural Network Approach for Impingement Drying of Germinated Brown Rice Soaking with Turmeric Solution

2013 ◽  
Vol 372 ◽  
pp. 463-466
Author(s):  
Kiattisak Suntaro ◽  
Khwanruedi Sangchum ◽  
Supawan Tirawanichakul ◽  
Yutthana Tirawanichakul
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Moisture Content ◽  
Brown Rice ◽  
Measured Data ◽  
Drying Kinetics ◽  
Drying Time ◽  
Rice Samples ◽  
Artificial Neural ◽  
Drying Conditions

The objectives of this research are to determine the evolution of moisture transfer for germinated Thai jasmine Khao Dawk Mali 105 (KDML105) brown rice variety using impingement drying by eight commonly empirical drying modeling and artificial neural network (ANN) method. The experiments were carried out with drying temperatures of 80-100°C, initial moisture content of KDML105 rice samples soaking with turmeric solution was of 54-55% dry-basis and the desired final moisture content for each drying conditions was fixed at 14-16% dry-basis. The air flow rate was fixed at 7.0 m/s. The measured data in each drying conditions were simulated for getting drying equation by non-linear regression analysis. The results showed that the rice soaking with herb turmeric solution had no effect to drying kinetics and the simulated data using empirical drying equation of Henderson model had the best fitting to all measured data (R2of 0.9978-0.9995 and RMSE of 0.0001441-0.000414). For applying ANN modeling approach, the drying temperature and drying time were considered as the input variables for the topology of neural network while the moisture ratio was the output layer. The simulation results concluded that the simulated values of the ANN model, which was not concerned with any complicated physical properties of grain rice kernels, could be used for prediction drying kinetics and was relatively high accuracy compared to those predicted results of empirical models. So the ANN method without any complicated properties related of rice samples can approach for good prediction their drying kinetics as well as the complicated drying simulations method.

scholarly journals STUDY OF MILLING PROCESS AND ITS EFFECT ON VITAMIN B1 AND FOLIC ACID CONTENTS ON LOWLAND RICE PROMISING LINES

2015 ◽  
Vol 15 (2) ◽  
pp. 79
Author(s):  
Siti Dewi Indrasari ◽  
Shinta Dewi Ardhiyanti ◽  
Buang Abdullah
Keyword(s):  
Folic Acid ◽  
Vitamin B1 ◽  
Brown Rice ◽  
Milling Process ◽  
Lowland Rice ◽  
Rice Cultivars ◽  
Cultivated Rice ◽  
Uv Detector ◽  
Milled Rice ◽  
Fluorescence Detector

Rice is an important source of vitamin B1 and folic acid, but cultivated rice cultivars contain low of these nutrient. Breeding program had been conducted and several advanced lines with a high vitamin B and folic acid contents were found. This research aimed to study the contents of vitamin B1 and folic acid in the brown rice and milled rice of fifteen promising lowland rice lines. Dried paddy (14% moisture content) were husked in the mini husker (Satake THU 35A) to obtain brown rice and milled rice by using abrasive-type mini polisher (Satake TM-05, 1,450 RPM for 2 minutes). Vitamin B1 and folic acid in the brown rice and milled rice were determined by using HPLC equipped with fluorescence detector for vitamin B1 and UV detector for folic acid. Four out of fifteen rice lines studied showed a unique characteristic of vitamin B1 content in the brown rice and milled rice. Rice lines which have highest vitamin B1 in the brown rice were B10267-4-PN-6-2-3-2-2-2-3-3-2 (3.03 mg 100 g-1), B10876H-MR-2 (2.13 mg 100 g-1), B10531E-KN-1-2-PN-1-4-2 (1.33 mg 100 g-1) and B12411E-RS*-1-2-1 (1.21 mg 100 g-1). However after milling, 43-92% of their vitamin B1 were lost; the least loss was observed in B12411E-RS*-1-2-1 (1.21 mg 100 g-1) which was only  4%. Three out of fifteen rice lines studied has highest folic acid in brown rice, i.e. BP400G-PN-12-3-6 (158.5 µg 100 g-1), B10876H-MR-2 (152.0 µg 100 g-1), and B11742-RS*-2-3-MR-5-5-1-Si-1-3 (100.0 µg 100 g-1). After milling the line B10876H-MR-2 had the highest folic acid content (52.0 µg 100 g-1), much higher than that of Ciherang variety as a control. This study indicates the importance of having a suitable milling instrument to minimize loss of vitamin B1 and folic acid. The study also suggests the importance of creating new rice cultivars that have high nutrient and resistant to milling process.

scholarly journals STUDY OF MILLING PROCESS AND ITS EFFECT ON VITAMIN B1 AND FOLIC ACID CONTENTS ON LOWLAND RICE PROMISING LINES

2015 ◽  
Vol 15 (2) ◽  
pp. 79
Author(s):  
Siti Dewi Indrasari ◽  
Shinta Dewi Ardhiyanti ◽  
Buang Abdullah
Keyword(s):  
Folic Acid ◽  
Vitamin B1 ◽  
Brown Rice ◽  
Milling Process ◽  
Lowland Rice ◽  
Rice Cultivars ◽  
Cultivated Rice ◽  
Uv Detector ◽  
Milled Rice ◽  
Fluorescence Detector

Rice is an important source of vitamin B1 and folic acid, but cultivated rice cultivars contain low of these nutrient. Breeding program had been conducted and several advanced lines with a high vitamin B and folic acid contents were found. This research aimed to study the contents of vitamin B1 and folic acid in the brown rice and milled rice of fifteen promising lowland rice lines. Dried paddy (14% moisture content) were husked in the mini husker (Satake THU 35A) to obtain brown rice and milled rice by using abrasive-type mini polisher (Satake TM-05, 1,450 RPM for 2 minutes). Vitamin B1 and folic acid in the brown rice and milled rice were determined by using HPLC equipped with fluorescence detector for vitamin B1 and UV detector for folic acid. Four out of fifteen rice lines studied showed a unique characteristic of vitamin B1 content in the brown rice and milled rice. Rice lines which have highest vitamin B1 in the brown rice were B10267-4-PN-6-2-3-2-2-2-3-3-2 (3.03 mg 100 g-1), B10876H-MR-2 (2.13 mg 100 g-1), B10531E-KN-1-2-PN-1-4-2 (1.33 mg 100 g-1) and B12411E-RS*-1-2-1 (1.21 mg 100 g-1). However after milling, 43-92% of their vitamin B1 were lost; the least loss was observed in B12411E-RS*-1-2-1 (1.21 mg 100 g-1) which was only  4%. Three out of fifteen rice lines studied has highest folic acid in brown rice, i.e. BP400G-PN-12-3-6 (158.5 µg 100 g-1), B10876H-MR-2 (152.0 µg 100 g-1), and B11742-RS*-2-3-MR-5-5-1-Si-1-3 (100.0 µg 100 g-1). After milling the line B10876H-MR-2 had the highest folic acid content (52.0 µg 100 g-1), much higher than that of Ciherang variety as a control. This study indicates the importance of having a suitable milling instrument to minimize loss of vitamin B1 and folic acid. The study also suggests the importance of creating new rice cultivars that have high nutrient and resistant to milling process.

Prediction of Rice Milling Yield and Quality Attributes during Storage Using Regression Analyses

2019 ◽  
Vol 62 (5) ◽  
pp. 1259-1268
Author(s):  
Soraya Shafiekhani ◽  
Jung Ae Lee ◽  
Griffiths G. Atungulu
Keyword(s):  
Hybrid Rice ◽  
Storage Temperature ◽  
Rice Yield ◽  
Storage Conditions ◽  
Milled Rice ◽  
Yield And Quality ◽  
Head Rice ◽  
Rough Rice ◽  
Milling Yield

Abstract. Regression analyses were performed to determine the storage conditions that exhibited the best outcomes for long-grain, hybrid milled rice yield and quality. This study evaluated mold population on rough rice, milled rice discoloration, and head rice yield (HRY) after storage of rough rice in airtight conditions at moisture contents (MCs) of 12.5%, 16%, 19%, and 21% wet basis and temperatures of 10°C, 15°C, 20°C, 27°C, and 40°C at two-week intervals for 12 weeks. The experiment used a popular long-grain hybrid rice cultivar (XL745). Rice lots were procured from fields with and without conventional treatment of the field with fungicide for plant disease management. Field treatment and no field treatment were considered as a block, and a Mann-Whitney test was conducted to determine effect. The response surface method, an extension of second-order polynomial regression, was used to examine optimal treatment conditions. Mold population and milled rice discoloration from a combination of storage conditions were predicted using regression models. The first-order and second-order terms of temperature indicated a nonlinear relationship between temperature and ln(discoloration). The MC was positively associated with ln(discoloration), but the degree of impact may change with temperature because the interaction term was significant. From the model evaluation (R2 and lack-of-fit test), the discoloration level is expected to be 57% (49% to 66% confidence interval) under conditions of 20% MC, 40°C, and nine weeks of storage for samples procured from fungicide-treated rice fields. This discoloration change is substantial compared to the initial discoloration of 9%. At high temperature (40°C) and MC (21%), discoloration started immediately after two weeks of storage. Anaerobic storage conditions impeded mold growth, especially at high storage temperature (40°C). Low mold populations were observed in rice stored at low MC (16%). According to the regression model, the critical storage temperature that may lead to discoloration is between 27°C and 40°C. Pre-harvest fungicide treatment of rice in the field for disease control significantly improved the HRY but had no significant influence on mold population or discoloration. This study suggests a range of storage conditions to prevent losses in milling yield and quality of rice. In addition, the studied storage conditions mimicked the typical conditions for on-farm, in-bin drying and storage in the U.S. Mid-South, especially for the top layers of rice inside the bin, and therefore provide an important reference for growers and rice processors using in-bin structures to manage the quality of long-grain hybrid rice. Keywords: Discoloration, Head rice yield, Mold population, Regression analysis, Rice quality, Rice storage.

scholarly journals Natural Occurrence of Fumonisins in Rice with Fusarium Sheath Rot Disease

Plant Disease ◽  
1998 ◽  
Vol 82 (1) ◽  
pp. 22-25 ◽  
Author(s):  
H. K. Abbas ◽  
R. D. Cartwright ◽  
W. T. Shier ◽  
M. M. Abouzied ◽  
C. B. Bird ◽  
...  
Keyword(s):  
High Performance ◽  
Brown Rice ◽  
The United States ◽  
Enzyme Linked Immunosorbent Assay ◽  
Natural Occurrence ◽  
White Rice ◽  
Rough Rice ◽  
Rot Disease ◽  
Sheath Rot ◽  
Good Agreement

Twenty samples of rough rice (Oryza sativa) (unpolished kernels) collected during the 1995 harvest season from Arkansas (seven samples) and Texas (13 samples) were obtained from rice fields known to include plants with symptoms of Fusarium sheath rot putatively caused by Fusarium proliferatum. Samples were analyzed for fumonisin B1 (FB1) at three laboratories using three different extracting solvents by high-performance liquid chromatography (HPLC) or enzyme-linked immunosorbent assay (ELISA) methods. Forty percent of the samples were positive for FB1 at levels ≤4.3 μg/g by HPLC. The same samples contained FB1 at ≤3.6 μg/g when measured by an ELISA method. Most samples that were positive for FB1 were positive for fumonisin B2 (FB2) and fumonisin B3 (FB3) by HPLC at levels ≤1.2 μg/g. Very good agreement was obtained among the two laboratories using HPLC methods and the third using ELISA. Shelling of the unpolished rice results in hull and brown rice fractions. In a sample that contained 4.3 μg/g in whole kernels, the fumonisin level was very high in hulls (≤16.8 μg/g) and low in brown rice (≤0.9 μg/g). Milling of brown rice results in bran and white rice fractions. Fumonisins were found in bran at a level of ≤3.7 μg/g but were below the level of detection by HPLC in white rice. The presence of fumonisins (FB1, FB2, and FB3) was confirmed by fast atom bombardment/mass spectrometry. This is the first report of fumonisins in naturally contaminated rice in the United States.

Rough Rice Grain Drying (BRSMG CONAI) at Temperatures of 60 and 80°C in Oven

2016 ◽  
Vol 369 ◽  
pp. 148-151
Author(s):  
J.V. Silva ◽  
C.M.R. Franco ◽  
E.M.A. Pereira ◽  
T.H.F. Andrade ◽  
A.G. Barbosa de Lima
Keyword(s):  
Moisture Content ◽  
Oryza Sativa L ◽  
Brown Rice ◽  
Practical Method ◽  
Rice Grain ◽  
Rice Grains ◽  
Mass Transfer Processes ◽  
Rough Rice ◽  
Grain Drying ◽  
Drying Conditions

Rice (Oryza sativa L.) is a greatly important socio-economic crop. Immediate threshing and drying of wet harvested grains, to reach 18–19% (w.b) moisture content, is a practical method used by individual farmers to slow deterioration and increase selling prices. However, rough rice grain is different from other grains because it has an outer cover shell (palea and lemma) and a bran layer. Thus, the heat and mass transfer processes that take place during grain drying are different from those of other cereal grains, so understanding the effect of different treatments, drying temperature, moisture content and the gradients in rice grains is essential to optimize the drying conditions. In this sense, the current study aims to analyze the moisture removal and its effects on the stress cracking and the number of brown rice grains (BRSMG CONAI variety) at the temperatures of 60 and 80°C.

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