Prediction of Starch Content and Ethanol Yields of Sorghum Grain Using near Infrared Spectroscopy

2015 ◽  
Vol 23 (2) ◽  
pp. 85-92 ◽  
Author(s):  
Junhui Li ◽  
Mary-Grace C. Danao ◽  
Shih-Fang Chen ◽  
Song Li ◽  
Vijay Singh ◽  
...  
Keyword(s):  
Near Infrared ◽  
Ethanol Yield ◽  
Starch Content ◽  
Nir Spectroscopy ◽  
High Ratio ◽  
Fermentation Products ◽  
Number Of Factors ◽  
Ethanol Yields ◽  
Theoretical Ethanol Yield ◽  
Sorghum Grain

A rapid quantification method was developed and validated for non-destructive measurement of starch content, theoretical ethanol yield and actual ethanol yield of 48 cultivars of sorghum grain using Fourier transform near infrared (FT-NIR) spectroscopy in diffuse reflectance mode. Multiplicative scatter correction, Savitzky–Golay derivative smoothing and mean centring were used for processing the spectra of ground sorghum grain. The processed spectra were correlated with starch content, theoretical ethanol yield and ethanol produced through simultaneous saccharification and fermentation using partial least-squares regression (PLSR). The spectral range and number of factors were optimised for the low number of factors, high coefficients of determination for calibration ( R2) and validation ( r2), low root mean square error of prediction ( RMSEP), high ratio of performance to deviation ( RPD) and high ratio of the standard error of prediction to the range ( RER). The best PLSR model for starch content utilised the 4000–6000 cm−1 wavebands and had the following values: R2 = r2 = 0.97, RMSEP = 5.5 g kg−1 grain, RPD = 5.9 and RER = 15. Likewise, the model for theoretical ethanol yield utilised the 4000–8000 cm−1 wavebands and had R2 and r2 values of >0.90, RMSEP = 4.9 g kg−1 grain, RPD = 4.47 and RER = 12.8. It was more difficult to predict actual ethanol yield using FT-NIR spectroscopy given the small data set, and spectra were collected prior to the fermentation step. Resulting PLSR models had R2 and r2 values of <0.60, RMSEP = 11.2–21.4 g kg−1, RPD < 3 and RER < 6. These results demonstrated that FT-NIR spectroscopy may be a practical method for rough screening of sorghum cultivars for desirable starch content and theoretical ethanol yield. The models may be improved by including more cultivars in the model and additional compositional information, such as tannin and free amino nitrogen contents, in the chemometric analysis and using FT-NIR scans of the fermentation products to predict actual ethanol yields.

scholarly journals POTENCIAL DE CLONES EXPERIMENTAIS DE BATATA-DOCE PARA PRODUÇÃO DE ETANOL

Nativa ◽  
2018 ◽  
Vol 6 (4) ◽  
pp. 352
Author(s):  
Adriano Mendes Lourenço ◽  
Aline Torquato Tavares ◽  
Tiago Alves Ferreira ◽  
Danilo Alves da Silva Porto Lopes ◽  
João Victor Gonçalves Carline ◽  
...  
Keyword(s):  
Ethanol Production ◽  
Sweet Potato ◽  
Ipomoea Batatas ◽  
Ethanol Yield ◽  
Starch Content ◽  
Great Ability ◽  
Ethanol Yields ◽  
Root Starch ◽  
Breeding Selection ◽  
Starch Yield

A batata-doce (Ipomoea batatas (L.) Lam.) tem sido reportada como uma das espécies de planta com grande capacidade de converter biomassa em matéria prima para produção de etanol. O objetivo do trabalho foi avaliar o potencial de clones de batata-doce para produção de etanol. Foram avaliados 60 clones de batata-doce para produtividade de raízes, teor de amido nas raízes, produtividade de amido, coloração da casca e da polpa e o rendimento de etanol. O clone BDTO#122,32 e as cultivares Ana Clara e Carolina Vitória com média de 46,77; 42,75 e 41,25 t ha-¹, respectivamente, foram os que mais conseguiram acumular biomassa na forma de raiz. Os clones que apresentam as maiores médias de produtividade de amido por hectare foram BDTO#144.22 e BDTO#100.23, com valores de 15,46 e 14,16% t ha-1, com rendimentos de etanol de 8,33 e 7,63 m³ ha-¹. Os clones BDTO#144.22 e BDTO#100.23 apresentaram as maiores médias de produtividade de amido por hectare e rendimento de etanol, sendo, portanto, os mais promissores para a produção de etanol.Palavras-chave: Ipomoea batatas (L.) Lam, melhoramento genético, seleção, biocombustível. POTENTIAL OF EXPERIMENTAL CLONES OF SWEET POTATO FOR ETHANOL PRODUCTION ABSTRACT:Sweet potato (Ipomoea batatas (L.) Lam.) Has been reported as one of the plant species with great ability to convert biomass into feedstock for ethanol production. The objective of this work was to evaluate the potential of sweet potato clones for ethanol production. Twenty-six sweet potato clones were evaluated for root productivity, root starch content, starch yield, bark and pulp color, and ethanol yield. Clone BDTO # 122.32 and cultivars Ana Clara and Carolina Vitória averaging 46.77; 42.75 and 41.25 t ha-1, respectively, were the ones that were able to accumulate biomass in the root form. The clones presenting the highest starch productivity per hectare were BDTO # 144.22 and BDTO # 100.23, with values of 15.46 and 14.16% t ha-1, with ethanol yields of 8.33 and 7.63 m³ ha-¹. The clones BDTO # 144.22 and BDTO # 100.23 showed the highest averages of starch productivity per hectare and yield of ethanol, thus being the most promising for the production of ethanol.Keywords: Ipomoea potatoes (L.) Lam, breeding, selection, biofuel.

scholarly journals Assessing Ethanol Yield from Fermented Juice of Local and Exotic Sweet Sorghum Varieties Grown in Sudan

2021 ◽  
Vol 12 ◽  
pp. 11-17
Author(s):  
Salma I. Abdalbagi ◽  
Maarouf I. Mohammed
Keyword(s):  
Regression Analysis ◽  
Sweet Sorghum ◽  
Cultural Practices ◽  
Ethanol Yield ◽  
Correlation And Regression Analysis ◽  
Juice Yield ◽  
Ethanol Yields ◽  
Significant Regression ◽  
Theoretical Ethanol Yield ◽  
Fermented Juice

An experiment was conducted in 2017 at Alwaha Project, Khartoum State to study the potential of ethanol yield from fermented juice of local and exotic sweet sorghums. 40 genotypes were arranged in RCB design. Juice yield, ethanol yield as percentage of fermented juice, actual and theoretical ethanol yields were studied. The Baker’s yeast (Saccharomyces cerevisiae) was used in the fermentation process. ANOVA tests, correlation and regression analysis of actual vs theoretical ethanol yield were performed. Significant differences were detected among genotypes for ethanol yields. High ethanol yields as percentage from fermented juice were obtained, but ethanol yield per hectare was relatively low due to low juice yields. The genotypes BlueRibbon and KensasCollies from exotic materials; 5AbjSG51 and S.154 Ab70 from local materials were identified as promising for ethanol production. Correlation between actual ethanol yield and Juice yield was positive and highly significant. Regression analysis indicated that theoretical ethanol yield was little bit overestimated. It was concluded that juice yield is more crucial than ethanol concentration in maximizing ethanol yield of sweet sorghum. More efforts are needed to develop high juice-yielding genotypes. Juice maximization can also be achieved by using efficient milling devices and optimizing cultural practices.

Changes in ethanol production potential due to species, cultivar and location on the Canadian prairie

2010 ◽  
Vol 90 (2) ◽  
pp. 163-171 ◽  
Author(s):  
J G McLeod ◽  
W E May ◽  
D F Salmon ◽  
K. Sosulski ◽  
J B Thomas ◽  
...  
Keyword(s):  
Ethanol Production ◽  
Ethanol Yield ◽  
Starch Content ◽  
Species Selection ◽  
Western Canada ◽  
Canadian Prairie ◽  
Spring Triticale ◽  
Ethanol Yields ◽  
Small Grains ◽  
Selection Of

In recent years there has been a rapid growth in the fuel ethanol industry, increasing the need for a consistent supply of feedstock. This study was conducted to evaluate the potential of small grains in western Canada to supply feedstock to the ethanol industry. Thirty-one lines and cultivars of Canadian small grains were evaluated: eleven cultivars comprising five classes spring wheat, six cultivars of two and six row barley of feed, malting and hulless classes, eight cultivars of spring triticale and six cultivars of oat were grown at seven locations in western Canada and evaluated as feedstock for ethanol production. Starch concentrations and, for certain grains, β-glucan and pentosans were determined and used to estimate ethanol yields in L t-1 and L ha-1. On average, ethanol yield in L t-1 was wheat > triticale > barley > oat; however, for yield in L ha-1, only oat was inferior. This ranking was consistent across all locations tested. Estimates of ethanol yields indicated that certain cultivars within classes of grains were superior, such as CDC Buck, SWS 109, HY 617 and Pronghorn in the hulless barley, CWSWS, CPS-R and Triticale classes, respectively. Locations that produced the highest level of ethanol in one species tended to produce grain with the highest ethanol yields in the other species. Selection of cultivars with greater starch content, different starch quality and reduced pentosans as well as the advancements in and adoption of new fermentation technologies may lead to greater estimates of ethanol yields of small grain cereals in the future.Key words: Cereal grains, starch, pentosans, β-glucans, ethanol yield

scholarly journals The principles, practices and some future applications of near infrared spectroscopy for predicting the nutritive value of foods for animals and humans

1997 ◽  
Vol 10 (1) ◽  
pp. 83-114 ◽  
Author(s):  
D. I. Givens ◽  
J. L. De Boever ◽  
E. R. Deaville
Keyword(s):  
Egg Production ◽  
Nutritive Value ◽  
Near Infrared ◽  
Starch Content ◽  
Animal Health ◽  
Nir Spectroscopy ◽  
Vital Role ◽  
Future Application ◽  
Current Application ◽  
The Future

AbstractThe current application and future potential of near infrared (NIR) spectroscopy in the evaluation of foods for domesticated animals and humans is enormous. Where used, NIR spectroscopy has revolutionized the analysis and nutritional evaluation of animal feeds and human foods by providing a rapid means of examination. The availability of accurate and rapid methods of evaluation is becoming increasingly important to meet the nutritional requirements of animals for meat, milk, wool and egg production. This is essential for efficient and economic animal production, to maintain animal health and to minimize environmental impact. Accurate evaluation methods are also needed in relation to national and international legislation that regulates the circulation, trade and inspection of foods and feeds, aids effective functioning of the market and guards the safety of animals and humans. The aim of this review is to outline the theory and principles of NIR spectroscopy and to focus primarily on its application in the field of animal nutrition. The vital role NIR spectroscopy is playing in the prediction of biologically meaningful feed characteristics, including data derived in vivo, is demonstrated particularly through its application to forage evaluation, but also in the examination of raw materials and compound feeds. While the applications of NIR spectroscopy to different foods and drinks are extensive, this review gives an overview only of selected reported applications including its use for predicting nutritive value (mainly water, protein, fat, sucrose and starch content), monitoring food processing and for food authentication. The review provides clear evidence that the future application of NIR spectroscopy will undoubtedly increase, playing a vital role in the authentication of the quality and origin of foods and feeds and enabling the complex methods of feed evaluation required in the future to be put into widespread use.

scholarly journals Evaluation of the physicochemical content and solid-state fermentation stage of Zhenjiang aromatic vinegar using near-infrared spectroscopy

2020 ◽  
Vol 16 (12) ◽  
Author(s):  
Suwan Fan ◽  
Tianhong Pan ◽  
Guoquan Li
Keyword(s):  
Solid State ◽  
Solid State Fermentation ◽  
Near Infrared ◽  
Evaluation Method ◽  
Nir Spectroscopy ◽  
Least Squares Regression ◽  
Total Acid ◽  
Fermentation Products ◽  
Fermentation Stage

AbstractAs one of the most famous traditional Chinese vinegars, the grains physicochemical content of Zhenjiang aromatic vinegar during solid-state fermentation (SSF) reflects the growth status of microorganisms and the quality of fermentation products. In addition, the time for grain-turning has a significant effect on the quality of fermentation products. In this study, a new evaluation method combined near-infrared (NIR) spectroscopy with partial least squares regression (PLSR) was proposed to predict the physicochemical content of grains and the fermentation stage. The performance of the PLSR models for the total acid and the nonvolatile acid were RMSEP = 0.0371, Rp2 = 0.9760, and RMSEP = 0.0216, Rp2 = 0.9646, respectively. The accuracy ratio of SSF stage judgment was 100%. Experimental results indicate that the proposed method can be used to guide on-site grain-turning and improve the quality of fermentation products.

Changes in Carbohydrate Content during Wheat Maturation—What is Measured by near Infrared Spectroscopy?

2005 ◽  
Vol 13 (1) ◽  
pp. 9-17 ◽  
Author(s):  
Szilveszter Gergely ◽  
András Salgó
Keyword(s):  
Near Infrared ◽  
Starch Content ◽  
Nir Spectroscopy ◽  
Water Soluble ◽  
Starch Accumulation ◽  
Soluble Carbohydrates ◽  
Spectroscopic Techniques ◽  
Absorption Bands ◽  
Physiological Processes ◽  
Water Soluble Carbohydrates

The role of bread, pasta and related products produced from milled wheat seeds is important to the human diet, so monitoring changes of starch content in developing grain is essential. Immature wheat grains are also used as a functional food, particularly as a source of water-soluble carbohydrates. The amount and variation in content of different carbohydrates changes considerably during maturation and these changes were non-destructively monitored in developing grain using near infrared (NIR) spectroscopy. Characteristic changes in three carbohydrate absorption bands [1585–1595 nm (Carbohydrate I), 2270–2280 nm (Carbohydrate II) and 2325–2335 nm (Carbohydrate III)] were identified and it was concluded that the different dynamics of carbohydrates (starch accumulation as well as synthesis/decomposition of water-soluble carbohydrates) could be followed sensitively by monitoring these three different regions of NIR spectra. Carbohydrate I represents the effect of starch accumulation during maturation based on the vibrations of intermolecular hydrogen bonded O–H groups in polysaccharides. Carbohydrate II is the manifestation of O–H stretching and C–C stretching vibrations existing unengaged in water-soluble carbohydrates while Carbohydrate III describes the changes in C–H stretching and deformation band of poly- and mono-oligosaccharides. NIR spectroscopic techniques are shown to be effective in monitoring plant physiological processes and the spectra have hidden information for predicting the stage of growth in wheat seed.

scholarly journals Sorghum Grains Grading for Food, Feed, and Fuel Using NIR Spectroscopy

2021 ◽  
Vol 12 ◽  
Author(s):  
Irsa Ejaz ◽  
Siyang He ◽  
Wei Li ◽  
Naiyue Hu ◽  
Chaochen Tang ◽  
...  
Keyword(s):  
Near Infrared ◽  
Prediction Models ◽  
Low Cost ◽  
Nir Spectroscopy ◽  
Grain Morphology ◽  
Whole Grains ◽  
Least Squares Regression ◽  
Sorghum Grains ◽  
Sorghum Grain ◽  
Non Destructive

Near-infrared spectroscopy (NIR) is a non-destructive, fast, and low-cost method to measure the grain quality of different cereals. However, the feasibility for determining the critical biochemicals, related to the classifications for food, feed, and fuel products are not adequately investigated. Fourier-transform (FT) NIR was applied in this study to determine the eight biochemicals in four types of sorghum samples: hulled grain flours, hull-less grain flours, whole grains, and grain flours. A total of 20 hybrids of sorghum grains were selected from the two locations in China. Followed by FT-NIR spectral and wet-chemically measured biochemical data, partial least squares regression (PLSR) was used to construct the prediction models. The results showed that sorghum grain morphology and sample format affected the prediction of biochemicals. Using NIR data of grain flours generally improved the prediction compared with the use of NIR data of whole grains. In addition, using the spectra of whole grains enabled comparable predictions, which are recommended when a non-destructive and rapid analysis is required. Compared with the hulled grain flours, hull-less grain flours allowed for improved predictions for tannin, cellulose, and hemicellulose using NIR data. This study aimed to provide a reference for the evaluation of sorghum grain biochemicals for food, feed, and fuel without destruction and complex chemical analysis.

scholarly journals Estimation of the Constituent Properties of Red Delicious Apples Using a Hybrid of Artificial Neural Networks and Artificial Bee Colony Algorithm

Agronomy ◽  
2020 ◽  
Vol 10 (2) ◽  
pp. 267 ◽  
Author(s):  
Yousef Abbaspour-Gilandeh ◽  
Sajad Sabzi ◽  
Brahim Benmouna ◽  
Ginés García-Mateos ◽  
José Luis Hernández-Hernández ◽  
...  
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Spectral Range ◽  
Artificial Bee Colony ◽  
Near Infrared ◽  
Effective Properties ◽  
Starch Content ◽  
Nir Spectroscopy ◽  
Bee Colony ◽  
Artificial Neural

Non-destructive estimation of the constituent properties of fruits and vegetables has led to a dramatic change in the agriculture and food industry, allowing accurate and efficient sorting of the products based on their internal properties. Therefore, the present study utilized visible (VIS) and near-infrared (NIR) spectroscopy data in the range from 200 to 1100 nm for the estimation of several properties of Red Delicious apples, namely Brix minus acid (BrimA), firmness, acidity and starch content, using a hybrid of Artificial Neural Networks and Artificial Bee Colony (ANN–ABC) algorithm. Furthermore, the hybrid Artificial Neural Network–Particle Swarm Optimization (ANN–PSO) algorithm was utilized to select the most effective properties to estimate these characteristics. The results indicated that there are different peaks within this spectral range, and the spectral range for each peak gives different results. To ensure the stability of the proposed method, 1000 replications were performed for each estimate. The highest coefficients of determination, R2, for estimating the studied properties among the 1000 replicates were 0.898 for BrimA, 0.8 for firmness, 0.825 for acidity and 0.973 for starch content. The selection of the most effective wavelengths for estimating the properties produced five effective wavelengths for BrimA, nine for firmness, seven for acidity and five for starch content. In this case, the best R2 of the hybrid ANN–ABC among the 1000 iterations were 0.828, 0.738, 0.9 and 0.923, respectively.

scholarly journals AKARI NIR spectroscopy of interstellar ices

2015 ◽  
Vol 11 (A29A) ◽  
pp. 319-320
Author(s):  
Takashi Onaka ◽  
Tamami I. Mori ◽  
Itsuki Sakon ◽  
Fumihiko Usui ◽  
Ronin Wu ◽  
...  
Keyword(s):  
Near Infrared ◽  
Infrared Camera ◽  
Nir Spectroscopy ◽  
High Sensitivity ◽  
Large Magellanic Cloud ◽  
High Ratio ◽  
Young Stellar Objects ◽  
Stellar Objects ◽  
Hii Region ◽  
Low Metallicity

AbstractThe Infrared Camera (IRC) onboard AKARI has a near-infrared (2--5μm) spectroscopic capability with high sensitivity that allows us to study the major ice components in various objects. In particular, H2O and CO2 ice absorption features have been detected towards nearby galaxies, including several young stellar objects (YSOs) in the Large Magellanic Cloud (LMC), as well as a number of HII region-PDR complexes for the first time by IRC spectroscopy. While observations in the LMC show a high ratio (~0.34) of the CO2 to H2O ice column densities, the ratios in Galactic HII-region-PDR complexes are in the range of 0.1--0.2, being compatible with those found in Galactic massive YSOs in previous studies. The good correlation supports concurrent formation of the two ice species on the grain surface and the higher ratio in the low-metallicity LMC suggests possible environmental effects in the formation process.

Sign in / Sign up

Export Citation Format

Share Document