Integration of independent component analysis with near infrared spectroscopy for evaluation of rice freshness

The storage time and conditions of rice has an enormous effect on its appearance, flavor, and quality of the nutrients; and the acidity of rice usually increases with prolonged storage. Therefore, evaluation of freshness is an important issue for rice quality. In this study, the NIR (near infrared) spectra combined with independent component analysis (ICA) technique was used to evaluate the rice freshness. A total of 180 white rice samples were collected from 6 crop seasons for the purpose of developing an ICA-NIR based procedure for rice freshness as quantified by pH values. Values of pH were determined by a BTB-MR (bromothymol blue – methyl red) method. The best calibration model of white rice was developed using the smoothed first derivative spectra, five ICs and cross-validation; the results indicated that r² (coefficient of determination) = 0.924, and in units of pH, SEC (standard error of calibration) = 0.145, SEP (standard error of prediction) = 0.146, bias = 0.001, and RPD (residual predictive deviation) = 3.65. Freshness of white rice could be distinguished either visually by a 3-dimensional diagram composed from ICs 2, 3 and 4, or statistically by a calibration model. The results show that ICA with NIR has the potential to be adopted as an effective method for evaluating rice freshness.     

Lignin-like compounds and sporopollenin coleochaete, an algal model for land plant ancestry

Unusual cell wall structure and resistance to microbial degradation led to an investigation of resistant biopolymers in Coleochaete (Chlorophyta, class Charophyceae), a green alga on the evolutionary lineage that led to land plants. In Coleochaete that are undergoing sexual reproduction, vegetative cell walls contain material similar to lignin, a substance generally thought absent from green algae, and the zygote wall includes sporopollenin. Knowledge of chemically resistant compounds in Coleochaete may facilitate interpretation of the fossil record. Placental transfer cells in Coleochaete orbicularis and in the hornwort Anthoceros survive acetolysis and contain lignin-like compounds, implying a close relation between these taxa.     

Predicting Protein Composition,Biochemical Properties,and Dough-Handling Properties of Hard Red Winter Wheat Flour by Near-Infrared Reflectance

Breadmaking quality in wheat is one of several considerations that plant breeders face when developing new cultivars. In routine breeding programs, quality is assessed by small-scale dough-handling and bake tests, and to some extent, by biochemical analysis of gluten proteins. An alternative, not yet fully examined, method for wheat flour quality assessment is near-infrared reflectance (NIR) spectrophotometry. The present study was performed on 30 genotypes of hard red winter wheat grown during two crop years at eight to nine locations in the Great Plains area of the United States. Biochemical testing consisted of measuring protein fractions from size-exclusion HPLC (M _r > 100k, M _r 25–100k, and M _r < 25k designated as glutenin, gliadins, and albumin and globulins, respectively), pentosan content, and SDS sedimentation volume. Dough-handling properties were measured on a mixograph and recorded as the time to peak dough development, the peak resistance, the width of the mixing curve, and the width of the curve at 2 min past peak. Partial least squares analyses on diffuse NIR spectra (1,100–2,498 nm) were developed for each constituent or property. When applied to a separate validation set, NIR models for glutenin content, gliadin content, SDS sedimentation volume, and mixograph peak resistance demonstrated reference vs. predicted correlations ranging from r = 0.87 to r = 0.94. Such models were considered sufficiently accurate for screening purposes in breeding programs. NIR spectra were responsive to each constituent or property at a level higher than expected from a correlation between the constituent or property and protein content (recognizing that protein content is modeled by NIR with high accuracy).     

Protein Content of Bulk Wheat from Near‐Infrared Reflectance of Individual Kernels

Protein content of wheat by near‐infrared (NIR) reflectance of bulk samples is routinely practiced. New instrumentation that permits automated NIR analysis of individual kernels is now available, with the potential for rapid NIR‐based determinations of color, disease, and protein content, all on a single kernel (sk) basis. In the event that the protein content of the bulk sample is needed rather than that of the individual kernels, the present study examines the feasibility of estimating bulk sample protein from sk spectral readings. On the basis of 318 wheat samples of 10 kernels per sample, encompassing five U.S. wheat classes, the study demonstrates that with as few as 300 kernels bulk sample protein content may be estimated by sk NIR reflectance spectra at an accuracy equivalent to conventional bulk kernel NIR instrumentation.     

Single Kernel Near‐Infrared Analysis of Tetraploid (Durum) Wheat for Classification of the Waxy Condition

Plant breeding programs are active worldwide in the development of waxy hexaploid (Triticum aestivum L.) and tetraploid (T. turgidum L. var. durum) wheats. Conventional breeding practices will produce waxy cultivars adapted to their intended geographical region that confer unique end use characteristics. Essential to waxy wheat development, a means to rapidly and, ideally, nondestructively identify the waxy condition is needed for point‐of‐sale use. The study described herein evaluated the effectiveness of near‐infrared (NIR) reflectance single‐kernel spectroscopy for classification of durum wheat into its four possible waxy alleles: wild type, waxy, and the two intermediate states in which a null allele occurs at either of the two homologous genes (Wx‐1A and Wx‐1B) that encodes for the production of the enzyme granule bound starch synthase (GBSS) that controls amylose synthesis. Two years of breeders' samples (2003 and 2004), corresponding to 47 unique lines subdivided about equally into the four GBSS genotypes, were scanned in reflectance (1,000–1,700 nm) on an individual kernel basis. Linear discriminant analysis models were developed using the best set of four wavelengths, best four wavelength differences, and best four principal components. Each model consistently demonstrated the high ability (typically >95% of the time) to classify the fully waxy genotype. However, correct classification among the three other genotypes (wild type, wx‐A1 null, and wx‐B1 null) was generally not possible.     

Influence of Instrument Rigidity and Specimen Geometry on Calculations of Compressive Strength Properties of Wheat Endosperm

Endosperm texture is one of the most important quality features in wheat; it defines milling energy requirements and end‐use suitability. From an engineering perspective, texture can be quantified by measuring the physical property of the resistance force to crushing of precisely machined specimens of endosperm. In such procedures, cylindrical or parallelepiped blocks are crushed under a constant rate of strain, in which values are reported of maximum stress, strain at maximum stress, Young's modulus, and the energy of compression to the point of maximum stress. Generally overlooked, however, is the instrument itself, which can significantly affect the apparent values of the latter three properties. Because no instrument is infinitely rigid, departures between apparent and actual strength properties occur. In this study, the physical principles for compressive strength measurement with respect to corrections for instrument rigidity are developed. Results show that the departures are exacerbated in specimens of small slenderness ratio and elevated hardness. This issue is demonstrated in a small collaborative study involving three laboratories and three instruments with low, intermediate, and high rigidity. Specimens were prepared from wheat kernels from hard and soft near‐isogenic lines derived from the cultivar Alpowa. For strain at maximum stress, the implementation of a correction for instrument rigidity reduced the range across laboratories from 6.03–47.7% (before correction) to 4.49–7.35% (after correction) for the hard genotype, and the corresponding ranges for the soft genotype were 3.29–18.6% and 2.07–6.01%, respectively. For Young's modulus, instrument rigidity correction resulted in a tenfold correction for the hard genotype measured on the least rigid instrument, going from 0.21 GPa (before) to 4.9 GPa (after). Likewise, with this instrument, the imparted energy density to maximum stress was reduced from an average apparent value of 23 MJ/m³ (before) to 3.8 MJ/m³ (after). Because of these large differences between apparent and actual values for these physical‐strength properties, it is recommended that future strength property measurements should account for instrument rigidity by implementation of the correction procedure described herein.     

Repeatability Precision of the Falling Number Procedure Under Standard and Modified Methodologies

The falling number (FN) procedure is used worldwide to assess the integrity of the starch stored within wheat seed. As an indirect measurement of the activity level of α‐amylase, FN relies on a dedicated viscometer that measures the amount of time needed for a metal stirring rod of precise geometry to descend a fixed distance through a column of water–flour or water–meal slurry that undergoes enzyme‐activated starch hydrolysis under controlled mixing and heating conditions. For U.S. wheat, FN values of 300 s and above generally indicate soundness in the condition of the seed starches, whereas values less than 300 s often indicate that some seeds have broken dormancy, which deleteriously affects bread‐, cake‐, and noodle‐making quality of products derived from their flour. Domestic and especially overseas sales contracts will often specify a minimum FN value for consignments, thus making it critical to ensure that the FN procedure be highly precise. The study described herein examined the level of repeatability precision of the FN procedure under strictly controlled laboratory conditions as a means to establish precision levels arising alone from the random nature of the viscous properties of starchy meal undergoing mixing and heating. Six representative samples of Pacific Northwest–grown soft white and club wheat, ranging in FN between 168 and 404 s, were repeatedly measured with the conventional FN procedure and three modifications thereof, with the modifications being increased meal and water amounts (8 g of meal + 30 mL of H₂O instead of 7 g + 25 mL) or the addition of a polysorbate surfactant (0.1% Tween 20) to the mixture water. Based on 16 FN runs for each sample and treatment, estimated variances and coefficients of variation (CV) were determined for each treatment–sample combination. The results indicated that CVs between 1 and 4% were achieved for all treatments and samples. The treatment modification of an augmented test sample size improved precision, whereas incorporating a surfactant had a negligible effect. Precision and treatment (conventional versus augmented) findings were corroborated by two external laboratories with two of the six original samples and by the main laboratory on an independent set of 14 wheat meal samples of commercial origin. Another possible improvement in precision is in the sequencing of water and meal addition to be half the volume of water, then the meal, followed by the remaining volume of water, all at the conventional levels of meal and water. Preliminary experimental results indicate an improvement in precision by using the “sandwich” approach; however, further testing is warranted to substantiate this discovery.