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.

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.

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 Rice Chilling on Drying, Milling, and Quality Characteristics

2020 ◽  
Vol 36 (5) ◽  
pp. 767-776
Author(s):  
Soraya Shafiekhani ◽  
Griffiths G Atungulu
Keyword(s):  
High Temperature ◽  
Cold Storage ◽  
Storage Temperature ◽  
Rice Yield ◽  
Quality Characteristics ◽  
List Type ◽  
Milled Rice ◽  
Heated Air ◽  
Rough Rice

HighlightsThis study experimentally simulated drying of rough rice subjected to various cold storage/chilling conditions.The rice was dried using slightly-heated air and high temperature air with procedures set to mimic those practiced by commercial systems.The moisture removal, drying rate constant, material state transition, milling and quality characteristics of rice upon drying conditions was investigated.The study provides important reference information for growers and rice processors using the relatively new rice cooling technology.Abstract. High temperature (field heat) and moisture content of freshly harvested rough rice promote excessive respiration and microbial growth. Therefore, the rice risks significant deterioration of quality due to delayed drying at peak harvest time when drying capacity becomes limited. The U.S. rice industry has identified that cooling/chilling the rice prior to drying to remove the excess heat, immediately after harvest, significantly preserves the quality of milled rice. This study experimentally simulated drying of rough rice after cold storage/chilling. The rice was dried using slightly-heated air and high temperature air with procedures set to mimic those practiced by commercial systems. Rough rice at moisture contents (MCs) of 16%, 19%, and 21% (wet basis) were stored at storage temperature (Ts) of 10°C, 15°C, and 20°C for up to 4 months. Following retrieval, the samples were dried at drying temperature (Td) of 35°C, 45°C, and 60°C and relative humidity (RH) of 20%. Each drying run comprised of two 20-min drying passes with the rice tempered at the drying Td for a duration of 4 h following every drying pass. Following the drying, the rice was conditioned in an equilibrium MC chamber (T=26°C, RH=56%) to 12.5% MC and then milled to evaluate milled rice yield and quality characteristics. The highest percentage points of MC removal (6.77% points) occurred following drying at air temperature of 60°C for samples with initial MC at 21% and stored at 20°C. Drying with air at 60°C decreased head rice yield (HRY) especially for samples with initial MC at 21% and stored at 10°C (HRY=51.4% versus those at 45°C and 35°C, HRY=55.95% and HRY=58.8%, respectively). Drying air temperatures studied (35°C, 45°C, 60°C) had no significant effect of causing discoloration of samples within the range of the studied initial MCs and storage temperatures. Peak and final viscosities of samples with different initial MCs (16%, 19%, and 21%) stored at 20°C followed by high temperature air drying (60°C) were significantly different from those of samples stored at 10°C and 15°C. The results provided insight into the drying, milling, and quality characteristics of rice after cold storage/chilling. The information provide foundation for development of new recommendations to improve quality of milled rice. Keywords: Conventional drying, Cooling/chilling, Milling quality, Rough rice, Storage.

scholarly journals Color-Induced Aroma Illusion: Color Cues Can Modulate Consumer Perception, Acceptance, and Emotional Responses toward Cooked Rice

Foods ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 1845
Author(s):  
Shady Afrin Jeesan ◽  
Han-Seok Seo
Keyword(s):  
Emotional Responses ◽  
Brown Rice ◽  
Consumer Perception ◽  
Cultural Backgrounds ◽  
Milled Rice ◽  
Cooked Rice ◽  
Yellow Orange ◽  
Rice Consumption ◽  
Rice Samples ◽  
Color Cues

Since rice is often cooked in many countries with different types of ingredients or seasonings, the surface colors of traditional rice meal items vary across cultural backgrounds. This study aimed to determine whether consumer perception, acceptance, willingness to eat, and emotional responses toward cooked rice samples could differ with their surface color cues. Milled rice was cooked with one of three food colorants: yellow, orange, and green, with milled (white) and un-milled (brown) rice cooked without colorants used as respective test and filler samples. Using a check-all-that-apply method, 98 rice consumers checked all aroma attributes they perceived by sniffing each of the four cooked-rice samples (white, yellow, orange, and green). They also rated the four samples with respect to attribute intensity, liking, emotional responses, and willingness to eat. The results showed that participants associated colored rice with specific ingredient-related aroma attributes (e.g., green color elicited sweet peas or spinach aromas). Color cues also affected ratings of attribute intensity, liking, willingness to eat, and emotional responses to cooked rice samples. In conclusion, this study provides empirical evidence that in the context of cooked rice consumption, color cues can elicit associated aromas and modulate consumer perception, acceptance, and evoked emotions to cooked rice.

scholarly journals Prediction of wheat milling characteristics by near-infrared reflectance spectroscopy

2011 ◽  
Vol 23 (No. 4) ◽  
pp. 145-151 ◽  
Author(s):  
J. Blažek ◽  
O. Jirsa ◽  
M. Hrušková
Keyword(s):  
Near Infrared ◽  
Prediction Models ◽  
Nir Spectroscopy ◽  
Milling Process ◽  
Near Infrared Reflectance ◽  
Independent Validation ◽  
Milling Characteristics ◽  
Predicted Values ◽  
Calibration Equations

The aim of this study was to explore the use of NIR spectroscopy of laboratory milled flour to predict the milling characteristics of wheat. Quantitative traits of the milling process of wheat were predicted by analyses of NIR spectra of six sets consisting of 94 samples. Reference data were obtained by grinding the samples on the laboratory mill Chopin CD1-auto (France), spectral data were measured on spectrograph NIRSystem 6500. Commercial spectral analysis software WINISI II was used to collect spectra, develop calibration equations and evaluate calibration performance. The quality of prediction was evaluated by coefficients of correlation between the measured and the predicted values from cross and independent validation. MPLS/PLS regression and ANN methods were used. A statistically significant dependence (at the probability level of 99%) was determined for all traits studied in the case of cross-validation. Satisfactory accuracy of the prediction models by independent validation was achieved only for semolina extraction rate, models for other characteristics did not show acceptable precision.  

Fissuring Kinetics of Rough Rice during the Drying Process

2020 ◽  
Vol 36 (5) ◽  
pp. 639-645
Author(s):  
Zephania R. Odek ◽  
Terry J. Siebenmorgen ◽  
Ashok Saxena
Keyword(s):  
Relative Humidity ◽  
Time Interval ◽  
List Type ◽  
Drying Process ◽  
Milled Rice ◽  
X Ray ◽  
Rough Rice ◽  
Drying Conditions ◽  
Subsequent Storage ◽  
Kinetics Of

HighlightsDrying rough rice using harsh air conditions causes fissures to appear instantaneously during active drying.For mild drying air conditions, a time interval is required after the cessation of active drying before fissures appear.The majority of fissures due to active drying in rough rice kernels appear after drying has ceased.Abstract. Fissuring of rough rice kernels leads to breakage during milling, which results in head rice yield reductions. While other studies have addressed the fissuring kinetics of milled rice kernels, rice is normally dried and stored as rough rice. Thus, the objective of this research was to study the fissuring kinetics of rough rice kernels during the drying process and to characterize the configuration of the fissures. Rough rice kernels of cultivar CL XL745 with a bulk moisture content of 17% were dried using air at 40°C, 50°C, and 60°C each at relative humidity (RH) levels of 20%, 40%, and 60%. During the drying process (drying, tempering, and subsequent storage), X-ray images of rice kernels were recorded to enumerate fissures. As the drying air temperature was increased, the percentage of fissured kernels increased for all RHs evaluated. Conversely, as RH was increased, the percentage of fissured kernels decreased. Approximately 90% of fissures appeared after drying had ceased, increasing rapidly in the initial 6 h after drying. Kernels dried at high-temperature, low-RH drying air combinations had fissuring occur and appear instantaneously during active drying. In low-temperature drying conditions, fissures did not appear during active drying. Fissuring under such conditions required a time delay after active drying. This study shows the stages of the drying process when fissures appear in rough rice and the durations after active drying when fissures are expected to appear. Keywords: Glass transition, Post-drying, Relative humidity, Rice drying, Temperature, Tempering, X-ray imaging.

Prediction of Fatty Acid Content in Beef Neck Lean by near Infrared Reflectance Analysis

1998 ◽  
Vol 6 (1) ◽  
pp. 229-234 ◽  
Author(s):  
William R. Windham ◽  
W.H. Morrison
Keyword(s):  
Fatty Acids ◽  
Fatty Acid ◽  
Near Infrared ◽  
Fatty Acid Content ◽  
Reference Method ◽  
Nir Spectroscopy ◽  
Coefficient Of Determination ◽  
Longissimus Dorsi ◽  
Near Infrared Reflectance ◽  
Total Fatty Acids

Near infrared (NIR) spectroscopy in the prediction of individual and total fatty acids of bovine M. Longissimus dorsi neck muscles has been studied. Beef neck lean was collected from meat processing establishments using advanced meat recovery systems and hand-deboning. Samples ( n = 302) were analysed to determine fatty acid (FA) composition and scanned from 400 to 2498 nm. Total saturated and unsaturated FA values ranged from 43.2 to 62.0% and 38.3 to 56.2%, respectively. Results of partial least squares (PLS) modeling shown reasonably accurate models were attained for total saturate content [standard error of performance ( SEP = 1.10%); coefficient of determination on the validation set ( r2 = 0.77)], palmitic ( SEP = 0.94%; r2 = 0.69), unsaturate ( SEP = 1.13%; r2 = 0.77), and oleic ( SEP = 0.97; r2 = 0.78). Prediction of other individual saturated and unsaturated FAs was less accurate with an r2 range of 0.10 to 0.53. However, the sum of individual predicted saturated and unsaturated FA was acceptable compared with the reference method ( SEP = 1.10 and 1.12%, respectively). This study shows that NIR can be used to predict accurately total fatty acids in M. Longissimus dorsi muscle.

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