Analysis of dry matter and protein contents in fresh yam bean tubers by near‐infrared reflectance spectroscopy

Abstract

Fast screening methods are needed for plant breeding. The objective of this research was to evaluate the potential of near‐infrared reflectance spectroscopy (NIRS) for the simultaneous analysis of dry matter and protein contents in intact discs of fresh yam bean (Pachyrhizus spp.) tubers. Discs from 210 tubers were extracted with a punch few hours after harvesting and scanned by NIRS using a specially designed adapter. External validation revealed a close relationship between NIRS and reference methods for dry matter content (r²=0.94; standard error of performance, SEP=1.2%) and protein content (r²=0.87; SEP=1.94%). The calibration for protein content was compared with another one developed using dried‐ground tuber samples (r²=0.97; SEP=0.97%). These results suggested that NIRS can be used to determine dry matter and protein contents in fresh tuber samples of yam beans with acceptable accuracy. Further research will have to determine if additional traits can be incorporated into this scheme.     

Effect of Storage Temperature for Paddy on Consumer Perception of Cooked Rice

Effect of storage temperature (ST) (5, 15, and 25°C) for paddy on the consumer perception of cooked rice (CR) was investigated with six major rice cultivars in Korea (Ilmibyeo, Chucheongbyeo, Ilpumbyeo, Hwayeongbyeo, Nampyeongbyeo, and Odaebyeo) after 12 months of storage. Germination rate (GR) of the paddy, grading characteristics (percentages of head rice, broken kernels, damaged kernels, colored kernels and chalky kernels) of milled rice (MR) kernels, texture profile analysis (hardness, springiness, cohesiveness, adhesiveness, and chewiness) and color (L*, a*, and b*) of CR were measured. Also, consumer testing on CR was done with 108 consumers. Consumers evaluated acceptability for odor, appearance, taste, texture, and overall purchase intent, and willingness to pay (WTP) of CR. After 12 months of storage, physicochemical characteristics of MR and CR were significantly different depending on ST. The significant difference among three ST of paddy was noted for GR, color b* value, fat acidity of MR, and overall consumer acceptability of CR. The GR was constant during 12 months of storage at 5°C, whereas a significant decrease of GR was noted for all six cultivars within 12 months of storage at 25°C. The average WTP for rice stored at 5°C for 12 months was $U.S. 45.68/20 kg, whereas WTP for rice stored at 15°C and 25°C were $U.S. 44.19/20 kg and $U.S. 41.87/20 kg, respectively, implying the importance of ST on grain quality and product value by consumers. Overall consumer acceptability had high correlation coefficient with WTP (r = 0.985). Overall consumer acceptability had highest correlation with GR of paddy (r = 0.861), followed by b* value of CR (r = –0.826), fat acidity (r = –0.768), cohesiveness (r = 0.733), and hardness (r = –0.650) of CR by TA, implying GR of paddy and b* value of CR could be used as indicators for eating quality of rice.     

Protein and Apparent Amylose Contents of Milled Rice by NIR‐FT/Raman Spectroscopy

The chemometric calibration of near‐infrared Fourier‐transform Raman (NIR‐FT/Raman) spectroscopy was investigated for the purpose of providing a rigorous spectroscopic technique to analyze rice flour for protein and apparent amylose content. Ninety rice samples from a 1996 collection of short, medium, and long grain rice grown in four states of the United States, as well as Taiwan, Korea, and Australia were investigated. Milled rice flour samples were scanned in rotating cups with a 1,064 nm (NIR) excitation laser using 500 mW of power. Raman scatter was collected using a liquid N₂ cooled Ge detector over the Raman shift range of 175–3,600 cm^‐1. The spectral data was preprocessed using baseline correction with and without derivatives or with derivatives alone and normalization. Nearly equivalent results were obtained using all of the preprocessing methods with partial least squares (PLS) models. However, models using baseline correction and normalization of the entire spectrum, without derivatives, showed slightly better performance based on the criteria of highest r² and the lowest SEP with low bias. Calibration samples (n = 57) and validation samples (n = 33) were chosen to have similar respective distributions for protein and apparent amylose. The best model for protein was obtained using six factors giving r² = 0.992, SEP = 0.138%, and bias = ‐0.009%. The best model for apparent amylose was obtained using eight factors giving r² = 0.985, SEP = 1.05%, and bias = ‐0.006%.     

Poor growth of summer crops due to phosphate deficiency after rice cultivation—No involvement of soil-borne plant pathogens

Aerated steam treatment of drained rice soils at 60°, 80° and 100°C for 30 min had no significant effect on the dry matter production of maize seedlings indicating that soil-borne root disease micro-organisms are not involved in the poor growth of maize in these soils. No evidence of Mn or Fe toxicity was apparent in plant tissue analyses. The 100°C steam treatment significantly depressed the amount of phosphorus fertilizer required to provide an equilibrium P concentration in soil solutions of 0.13 μg ml^?1 (P_req) in both rice bank and bay soils. In bay soils this effect was also observed in 60° and 80°C treatments. Differences in concentrations of P_REQ between bank and bay soils were detected in untreated and 60°C treated soils. These differences were no longer apparent at the two higher temperatures. The effect of increasing heat treatment on the P_REQ of these soils was not reflected in the less sensitive Shukla single-value method for determining P sorptivity.Incorporation of sufficient P fertilizer to provide a minimum P concentration of 0.13 μg ml^?1 in both rice bank and rice bay soils eliminated differences in seedling growth of maize in these soils. Poor phosphate availability was therefore confirmed as the major constraint on the growth of maize seedlings growing in drained rice soils.     

ROOT ZONE TEMPERATURE INFLUENCES ZINC REQUIREMENT OF MAIZE CULTIVARS ON A CALCAREOUS LOAM SOIL

The zinc (Zn) requirement of a maize (Zea mays L.) hybrid (‘FHY-396’) and an indigenous variety (‘EV-7004’) was measured at low (22.4 ± 5°C) and high (28.8 ± 5°C) root-zone temperatures (RZT). Four Zn rates (0, 3, 9 and 27 mg kg^?1 soil) were applied to a calcareous loam soil in pots for the glasshouse study. Shoot and root dry matter yields were significantly more at the higher RZT. Regardless the RZT, maximum relative shoot dry matter yield in hybrid and variety was produced, respectively, at 9 and 3 mg Zn kg^?1 soil. Zinc concentration in roots and shoots of both the cultivars increased with Zn rates and it was significantly more at the higher RZT. Cultivars differed in critical Zn concentration (C_ZnC) required for maximum shoot dry matter yield. The C_ZnC ranged from 25 to 39 μg Zn g^?1 plant tissue for optimum growth of both the cultivars at low and high RZT.     

Infrared Drying Characteristics of Long‐Grain Hybrid,Long‐Grain Pureline,and Medium‐Grain Rice Cultivars

The objective for this study was to investigate the effectiveness of scaled‐up infrared (IR) heating followed by tempering steps to dry freshly harvested rough rice. An industrial‐type, pilot‐scale, IR heating system designed to dry rough rice was used in this study. The heating zone of the equipment had catalytic IR emitters that provided heat energy to the sample as it was conveyed on a vibrating belt. The sample comprised freshly harvested rough rice of long‐grain pureline (Cheniere), long‐grain hybrid (6XP 756), and medium‐grain (CL 271) cultivars at initial moisture contents of 23, 23.5, and 24% wb, respectively. Samples at a loading rate of 1.61 kg/m² were heated with IR of radiation intensity 5.55 kW/m² for 30, 50, 90, and 180 s followed by tempering at 60°C for 4 h, at a product‐to‐emitter‐gap size of 450 mm, in one‐ and two‐pass drying operations. Control samples were gently natural air dried in an equilibrium moisture content chamber set at relative humidity of 65% and temperature of 26°C to moisture content of 12.5% wb. The effects of IR treatments followed by tempering on percentage points of moisture removed, head rice yield, energy use, rice color, and pasting characteristics were evaluated. For all cultivars, percentage point moisture removed increased with increase in IR drying duration. For all rice cultivars, one‐pass IR treatments for 180 s resulted in head rice yield significantly lower than that of rice dried with natural air in the controlled‐environment conditions (P < 0.05). Energy required to dry rice increased with increase in drying duration. Viscosity values of all the experimental samples were significantly greater (P value < 0.05) than that of the control samples for all the cultivars, except those treated with IR for 180 s. There was a significant difference (P < 0.05) in the color index (ΔE ) of treated milled samples and the controls. In conclusion, the study provided information crucial to understanding the effects of scaled‐up radiant heating and tempering of rough rice on drying rates and rice quality for long‐grain pureline, long‐grain hybrid, and medium‐grain rice cultivars.     

Development of a Near‐Infrared Imaging System for Determination of Rice Moisture

The objective of this study was to develop a near‐infrared (NIR) imaging system to determine rice moisture content. The NIR imaging system fitted with 15 band‐pass filters (wavelengths of 870–1,014 nm) was used to capture the spectral image. In this work, calibration methods including multiple linear regression (MLR), partial least squares regression (PLSR), and artificial neural network (ANN) were used in both near‐infrared spectrometry (NIRS) and the NIR imaging system to determine the moisture content of rice. Comprehensive performance comparison among MLR, PLSR, and ANN approaches has been conducted. To reduce repetition and redundancy in the input data and obtain a more accurate network, six significant wavelengths selected by the MLR model, which had high correlation with the moisture content of rice, were used as the input data of the ANN. The performance of the developed system was evaluated through experimental tests for rice moisture content. This study adopted the coefficient of determination (r_val²), the standard error of prediction (SEP), and the relative performance determinant (RPD) as the performance indices of the NIR imaging system with respect to the tests of rice moisture content. Utilizing these three models, the analysis results of r_val², SEP, and RPD for the validation set were within 0.942–0.952, 0.435–0.479%, and 4.2–4.6, respectively. From experimental results, the performance of NIR imaging system was almost the same as that of NIRS. Using the developed NIR imaging system, all of the three different calibration methods (MLR, PLSR, and ANN) provided a high prediction capacity for the determination of moisture in rice samples. These results indicated that the NIR imaging system developed in this study can be used as a device for the measurement of rice moisture content.     

Predicting pasture root density from soil spectral reflectance: field measurement

This paper reports the development and evaluation of a field technique for in situ measurement of root density using a portable spectroradiometer. The technique was evaluated at two sites in permanent pasture on contrasting soils (an Allophanic and a Fluvial Recent soil) in the Manawatu region, New Zealand. Using a modified soil probe, reflectance spectra (350–2500 nm) were acquired from horizontal surfaces at three depths (15, 30 and 60 mm) of an 80‐mm diameter soil core, totalling 108 samples for both soils. After scanning, 3‐mm soil slices were taken at each depth for root density measurement and soil carbon (C) and nitrogen (N) analysis. The two soils exhibited a wide range of root densities from 1.53 to 37.03 mg dry root g⁻¹ soil. The average root density in the Fluvial soil (13.21 mg g⁻¹) was twice that in the Allophanic soil (6.88 mg g⁻¹). Calibration models, developed using partial least squares regression (PLSR) of the first derivative spectra and reference data, were able to predict root density on unknown samples using a leave‐one‐out cross‐validation procedure. The root density predictions were more accurate when the samples from the two soil types were separated (rather than grouped) to give sub‐populations (n = 54) of spectral data with more similar attributes. A better prediction of root density was achieved in the Allophanic soil (r² = 0.83, ratio prediction to deviation (RPD ) = 2.44, root mean square error of cross‐validation (RMSECV ) = 1.96 mg g ⁻¹) than in the Fluvial soil (r² = 0.75, RPD = 1.98, RMSECV = 5.11 mg g ⁻¹). It is concluded that pasture root density can be predicted from soil reflectance spectra acquired from field soil cores. Improved PLSR models for predicting field root density can be produced by selecting calibration data from field data sources with similar spectral attributes to the validation set. Root density and soil C content can be predicted independently, which could be particularly useful in studies examining potential rates of soil organic matter change.     

The effect of preplant nitrogen and soil temperature on yield and nitrogen accumulation of alfalfa 1

Abstract

Recommendations for the use of preplant N in alfalfa establishment are controversial. Growth chamber experiments were conducted to examine the effect of preplant N and soil temperature on yield and N accumulation of alfalfa (Medicago sativa L.). Alfalfa was grown in river sand at three day/night soil temperatures (18/12°C, 24/16°C, and 27/21°C), and at five levels of preplant N (0, 10, 20, 40, 80 kg ha^?1). At 18/12°C, 40 kg ha^?1 preplant N resulted in a 69% increase in shoot dry matter yield. Dry matter and N accumulation rates were greatest at 40 and 80 kg ha^?1. Preplant N effects on dry matter and N accumulation at 18/12°C were expressed primarily between the early bud and early flowering stages. Assessment of soil temperature and soil N availability is necessary to determine the potential for a yield response of alfalfa to preplant N.     

Screening of Wheat for Flour Swelling Volume by Near-Infrared Spectroscopy

Selection for starch quality is an important consideration in the breeding of wheat for Asian noodles, particularly Japanese udon, and the flour swelling volume (FSV) test was developed for this purpose. Near-infrared reflectance spectroscopy (NIRS) analysis has also been a key tool in recent years in wheat quality selection. The development and validation of NIRS calibrations for the prediction of FSV on whole grain involved 22 cultivars and breeding lines grown at four locations in two seasons. Eight calibrations were developed, each based on samples from seven trials, with the eighth trial used for validation. Over the eight calibrations, r² between predicted and actual values was 0.56–0.86 (mean 0.74) and the standard error of prediction (SEP) was 0.77–1.65 (mean 1.14) mL/g of dry meal. Separate calibrations were also developed for hard (n = 461), soft (n = 150), and soft+hard grain (n = 616), with standard errors of cross-validation (SECV) of 1.03, 1.39, and 1.21 mL/g of dry meal, respectively. Corresponding r² between predicted and actual values were 0.76, 0.78, and 0.76, respectively. Thus, NIRS offers good potential for the screening of early-generation lines to identify those with high or low FSV.     

Use of near‐infrared reflectance spectroscopy to assess nitrogen concentration in different plant tissues of rapeseed

Abstract

An evaluation of the performance of near‐infrared reflectance spectroscopy (NIRS) in the analysis of nitrogen (N) concentration in different rapeseed (Brassica napus L.) tissues was made. A total of 228 samples from an N‐efficiency study corresponding to leaves and stems at flowering, fallen leaves, mature stems, and mature pod walls were oven dried, ground, and then analyzed by NIRS. The N concentration was determined by Dumas combustion. Two different calibration strategies were followed: (i) separate calibration equations were developed for each type of tissue, resulting in r² above 0.95 in crossvalidation for all tissues with the ratio of the standard error of crossvalidation (SECV) to the standard deviation of the population (SD) ranging from 0.10 to 0.22, and (ii) a NIRS calibration equation was developed from a set integrating 149 samples from the five groups of tissues. External . validation with a set containing 79 further samples from all the groups resulted in an r² of 0.99 and a ratio of the standard error of performance (SEP) to the SD of 0.08. External validation for each group separately resulted in r² from 0.91 to 0.99 and SEP/SD from 0.10 to 0.27. It was concluded that a universal NIRS calibration equation integrating samples from all the types of tissues is an adequate approach for the accurate analysis of N concentration in rapeseed. Based on our results, the NIRS technique can reliably replace the Kjeldahl or Dumas methods to determine the N concentration in investigations of the N efficiency in rapeseed.     

Functional and Digestive Characteristics of Extruded Rice Flour

Waxy (short grain), long grain, and parboiled (long grain) rice flours were extruded using three different temperatures and five different water feed rates. The water absorption and water solubility index of the extrudates was 0.67–5.86 and 86.45–10.03%, respectively. The fat absorption index was similar to that of unextruded flours with an average value of 0.96 g/g ± 0.12. Bulk density decreased with an increase in moisture, except waxy rice, which had a quadratic relationship. The viscosity profiles for long grain and parboiled rice were similar. Both initially increased in viscosity (>130 RVU), then decreased to ≈40 RVU. The final viscosity was ≈60 RVU. Waxy rice viscosity remained low (<20 RVU), then doubled upon cooling. The main difference in the digestion profiles was due to temperature. The flours extruded at 100°C digested significantly slower than those extruded at 125 and 150°C. Significant differences were not detected for a given temperature and moisture (P > 0.05) except for long grain and parboiled rice extruded at 100°C and 15% added moisture (F = 4.48, P = 0.03) and 150°C and 20% added moisture (F = 3.72, P = 0.05). Moisture appeared to have little effect for a given temperature, except when parboiled rice was extruded at 150°C. The digestion rate for 11 and 25% added moisture was significantly less than that for 20% (P ≤ 0.05).     

Effects of Silver Nanoparticles on Soil Ammonia-Oxidizing Microorganisms Under Temperatures of 25 and 5℃

The excellent bactericidal performance of silver nanoparticles (Ag NPs) has led to their wide applications, resulting in increasing concerns about their potential environmental impacts. This study evaluated the influences of different concentrations of Ag NPs (0, 1, 10, and 100 μg g^-1 dry soil) on the ammonia-oxidizing microorganisms in soil at cultivation temperatures of 25 and 5℃ for 37 d. The results showed that 1 μg g^-1 dry soil of Ag NPs had no acute effects on the ammonia-oxidizing microorganisms. However, 10 and 100 μg g^-1 dry soil of Ag NPs levels were found to significantly inhibit the activities of soil nitrification, with a decrease of 69.89% and 94.55%, respectively, at 25℃ and 61.65% and 83.79%, respectively, at 5℃ compared to the control (0 μg g^-1 dry soil of Ag NPs). These levels of Ag NPs also obviously decreased soil urease activity from about 380.47 ±0.07 (at 5℃) and 529.76 ±13.44 (at 25℃) mg N g^-1 dry soil d^-1 to 61.70 ±2.97 and 68.29 ±8.22 mg N g^-1 dry soil d^-1, respectively, after 37 d of cultivation. Quantitative polymerase chain reaction showed the abundance of ammonia-oxidizing archaea and bacteria. For the same exposure time, the effects of Ag NPs on the activities of ammonia-oxidizing microorganisms and urease decreased with decreasing temperature. The threshold concentration of Ag NPs that induced negative effects on ammonia-oxidizing microorganisms was higher at 5℃ than at 25℃. Therefore, the temperature has a major impact on the toxicity of Ag NPs to ammonia-oxidizing microorganisms and on the urease activity, with toxicity being reduced with decreasing temperature.     

Production and carrying capacity for the earthworm Lumbricus terrestris in culture

Approximately 8 h were required at 25°C for food to pass from mouth to anus in the earthworm Lumbricus terrestris. Gut load per unit transit appeared inversely related to nitrogen content; values of about 2 and 44 mg dry castings per 100mg dry worm were obtained with activated sludge and mineral soil, respectively. Production of biomass was greater in a substrate of activated sludge and loam relative to activated sludge and cellulose, despite higher concentrations of nitrogen in the latter. Optimum population density was about 8 earthworms (31 g live wt) in 1000cm³ 2:1 sludge:soil. Growth occurred at a maximum rate between 15 and 25°C. A yield of approximately 4% biomass (dry wt) was obtained on a mixture of activated sludge and loam, based on the content of organic matter present.     

Modeling of the fine‐scale temperature response of arylsulfatase activity in soil

Fine‐scale (1.0–2.2 °C) temperature dependence of soil arylsulfatase activity (arylsulfate sulfohydrolase, EC 3.1.6.1) was measured at 0 to 75 °C in a Danish sandy, arable soil. Assays were done with field‐moist soil samples in the absence of toluene as plasmolytic agent – a procedure that primarily measures the extracellular enzymes. The aim was to evaluate the use of temperature models to describe the temperature response of soil arylsulfatase activity. In addition, we searched for increases in activity at high temperatures (e.g., 50–60 °C), which might be associated with unmasking (exposure) of intracellular enzymes. Arylsulfatase activities ranged from 1.1 to 60.3 μg p‐nitrophenol (g dry weight soil)^–1 h^–1, with an optimum temperature at 58.1 °C. The temperature response below 58.1 °C could be described by the Arrhenius equation (r² = 0.978, n = 83) and the simple Ratkowsky equation (r² = 0.977, n = 83). The expanded Ratkowsky equation, which covered the entire temperature range (0–75 °C), was less satisfactory (r² = 0.958, n = 90) because the model underestimated the reaction rates near the optimum temperature. The activation energy (E_a) calculated from the Arrhenius equation was 42.2 kJ mol^–1. This was higher than previously found for other soils (16.5–34.7 kJ mol^–1), possibly due to the use of toluene in these studies. Further analysis of the temperature response showed that no increase in activity occurred due to potential unmasking of intracellular enzymes by disintegration of bacterial cell membranes at high temperatures. Thus, the use of high incubation temperatures did not facilitate the differentiation between intra‐ and extracellular enzyme activity.     

Quantitative Analysis of Fat Content in Rice by Near‐Infrared Spectroscopy Technique

Fat content in rice is one of the most important nutritional quality properties. But the chemical analysis of fat content is time‐consuming and costly and could result in poor reproduction between replicates. Near‐infrared spectroscopy (NIRS) can solve those problems by providing a rapid, nondestructive, and quantitative analysis. Based on the NIRS technique and partial least squares (PLS) algorithm, four calibration models were established to quantitatively analyze fat content in brown rice grain and flour and milled rice grain and flour with 248 representative samples. The determination coefficients (R²) of these calibration models were 0.79, 0.84, 0.89, and 0.91, respectively, with the corresponding root mean square errors 0.16, 0.14, 0.09, and 0.08%. The R² were 0.73, 0.81, 0.81, and 0.89 with the corresponding root mean square errors 0.17, 0.15, 0.12, and 0.09%, respectively, in cross validation. The R² were 0.62, 0.80, 0.81, and 0.87, respectively, with the root mean square errors 0.25, 0.31, 0.28, and 0.30% in external validation. These results indicate that the method of NIRS has relatively high accuracy in the prediction of rice fat content. The four calibration models established in the present study should be useful for nutrient quality improvement in rice breeding.     

Genotypic Differences in Potassium Nutrition in Lowland Rice Hybrids

China imports most of its potassium (K) requirements for crop production. The objective of this study was to evaluate indica rice hybrids for K‐use efficiency. Twenty‐eight indica rice hybrids were evaluated in nutrient solution. The K influx rate was greatest in genotype Weiyou 64 (684.9 nmol K⁺ plant^?1 h^?1) and least in genotype Xie A/909 (457.2 nmol K⁺ plant^?1 h^?1). The K‐use efficiency was greatest in genotype ShanA/909 [81.8 mg dry matter (DM) produced per mg K taken up] and least in genotype Shanyou 64 (55.9 mg mg^?1). The maximum biomass was produced by genotype Shan A/4663‐5 (100.8 mg DM per plant), and the least biomass was produced by genotype Xie A/4663‐4 (59.1 mg DM per plant). These results suggest that K shortage for rice production can be alleviated by using K‐efficient rice genotypes.     

Rapid Prediction of Rice Quality Characteristics by Near‐Infrared Reflectance Spectroscopy for Breeding Programs

Breeding of high‐quality rice requires quick methods to evaluate the quality characteristics such as milling, grain appearance, nutritional, eating, and cooking qualities. Because routine measurements of these quality traits are time consuming and expensive, a rapid predictive method based on near‐infrared spectroscopy (NIRS) can be applied to measure these quality parameters. In this study, calibration models for measurement of grain quality were developed using a total of 570 brown and milled rice samples. The results indicated that the models developed from the spectra of brown rice for all the quality traits had the coefficient of determination for external validation (R²) larger than 0.64 except for gel consistency. The best model was developed for the protein content, with R² of 0.94 for external validation. The model for the total score of physicochemical characteristics (TSPC), a comprehensive index reflecting all other traits, had R² of 0.70 and SD/SEP of 1.70, which indicates that high or low TSPC for a given rice could be discriminated by NIRS. The models developed from brown rice were as accurate as those from milled rice. Results suggest that NIRS‐based predictions for rice quality traits may be used as indicator traits to improve rice quality in breeding programs.     

Quality Compost Production from Municipality Biowaste in Mix with Rice Straw,Cow Dung,and Earthworm Eisenia fetida

The biodegradable portion of city waste is a potential source of plant nutrients, and appropriate techniques of composting can convert it to quality compost with higher nutrient content and lower levels of pathogenic microorganisms. An amount of 68.19 tons of waste is generated in Imphal City, Manipur, India, of which 24.84 tons were biodegradable. Of the total biodegradable municipality waste (MW), 20.7 tons were produced in households and the vegetable markets of the city. The MW were found to contain pathogenic bacteria (PB), namely, Salmonella spp., Shigella spp., Micrococcus spp., and Enterobacter spp. in the range of 6.35–9.28 (log cfu/g dry biomass), and agriculturally beneficial bacteria (BB), namely, phosphate solubilizers, Azospirillum spp., Azotobacter spp., and cellulose degraders in the range of 6.25–8.83 log cfu/g dry biomass. Pre-treatment of the MW by exposure at temperatures of 27°C–50°C in a greenhouse for 5 days could not reduce the level of PB and BB, but by heating at 100°C for 8 h followed by 30°C for 16 h of a day for three consecutive days, the PB (except Micrococcus spp.) could be eliminated. Aerobic composting of the mixture of MW with cow dung (CD) and rice straw (RS) and by inoculation with epigeic earthworm Eisenia fetida, produced high quality manure as evident from more finer particle (56.6%), higher nutrient (2.19% N) content, higher population of BB (7.03–9.19 log cfu/g dry biomass), and reduced level of PB (6.87–8.09 log cfu/g dry biomass).     

Authentication of Rice Using Near‐Infrared Reflectance Spectroscopy

The authentication of rice (Korean domestic rice vs. foreign rice) has been attempted using near‐infrared spectroscopy (NIRS). Two sample sets (n₁ = 280 and n₂ = 200) were used to obtain calibration equations and the spectral regions used for this study were 500–600 nm, 700–900nm, and 980–2,498 nm. Modified partial least square (MPLS) regression was used to develop the prediction model. The standard error of cross validation (SECV) and the r² were 0.165 and 0.91 respectively for 1st calibration set and 0.165 and 0.93 for 2nd calibration set respectively. The results of the independent validation (n₃ = 80) showed that all of 80 samples were identified correctly. Even though authentication of rice was performed successfully using NIRS, the calibration statistics in this study showed that further effort is needed for implementation of NIRS for authentication of rice for industry purposes.