The Ability of Visible and near Infrared Reflectance Spectroscopy to Predict the Chemical Composition of Ground Chicken Carcasses and to Discriminate between Carcasses from Different Genotypes

2005 ◽  
Vol 13 (3) ◽  
pp. 109-117 ◽  
Author(s):  
R.M. McDevitt ◽  
A.J. Gavin ◽  
S. Andrés ◽  
I. Murray
Keyword(s):  
Crude Protein ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Dietary Treatment ◽  
Fat Content ◽  
Ash Content ◽  
Carcass Composition ◽  
Near Infrared Reflectance ◽  
Fast Growing ◽  
Slow Growing

The potential of visible and near infrared (NIR) spectroscopy to predict the fat, crude protein (CP) and ash content (g kg−1 DM) in dry ground chicken carcasses was evaluated. In addition, NIR spectroscopy was used to discriminate between ground carcasses from three different chicken genotypes: fast-growing broiler, slow-growing broiler and a layer-type chicken. When corrected for age and body mass (BM), the fast-growing broiler had the highest fat content and the lowest CP and ash content of the three genotypes. In contrast, the layer genotype had the highest CP and ash content and the lowest fat content. The fat, ash and CP content were intermediate in the slow-growing broilers. Spectra could explain a high proportion of the variability in carcass composition with respect to fat ( R2 = 0.93) and CP ( R2 = 0.86) content but less so for the ash content ( R2 = 0.71). Carcasses could be accurately classified according to chicken genotype or dietary treatment using NIR. However discrimination between male and female birds was not so clear, probably because all the birds used in the study were sexually immature.

Use of near infrared reflectance spectroscopy to predict and compare the composition of carcass samples from young steers

1997 ◽  
Vol 65 (1) ◽  
pp. 45-54 ◽  
Author(s):  
R. Sanderson ◽  
S. J. Lister ◽  
M. S. Dhanoa ◽  
R. J. Barnes ◽  
C. Thomas
Keyword(s):  
Crude Protein ◽  
Protein Concentration ◽  
Near Infrared ◽  
Fish Meal ◽  
Carcass Composition ◽  
Standard Errors ◽  
Near Infrared Reflectance ◽  
Wet Chemical ◽  
Four Levels ◽  
Different Levels

AbstractThe aim of the current study was to investigate the effects of level of feeding and level offish-meal supplementation on the carcass composition of young steers and in doing so, to assess the potential for employing near infrared reflectance spectroscopy (NIRS) in such studies. In addition to wet chemical techniques, NIRS was used to examine carcass samples from animals offered silage-based diets at one of four levels of feeding ranging from near maintenance to ad libitum and with one of four levels offish meal (0, 50,100 or 150 g/kg silage dry matter).Wet chemical data indicated an increase in fat concentration (P < 0·001) and decrease in crude protein concentration (P < 0·05) in the fresh carcass in response to increasing level of feeding but no statistically significant effect of level of fish meal. Ash concentration was not affected significantly by either level of feeding or level of fish-meal supplementation. Ground, freeze-dried samples were scanned in the wavelength range 1100 to 2498 nm. Calibration equations for ash, fat and crude protein concentration (g/kg carcass) were derived using a modified partial least-squares regression technique. Equations were found to be superior for fat compared with those for crude protein and ash. Standard errors of calibration (g/kg carcass) and multiple correlation coefficients of 6·96 and 0·42, 6·61 and 0·95 and 4·36 and 0·61 were obtained for ash, fat and crude protein respectively with corresponding standard errors of cross validation of 7·71, 7·82 and 4·96 g/kg carcass respectively. Qualitative analysis of spectral information using multivariate techniques and difference spectra clearly showed differences in carcass composition resulting from the different levels of feeding and less so the different levels offish-meal supplementation.It is shown, that NIRS can be used both quantitatively and qualitatively to study the effects of nutrition on carcass composition.

Prediction of Dry Matter and Crude Protein Content in Fresh Grass Silage by Near Infrared Spectroscopy

2005 ◽  
Vol 1 (1) ◽  
pp. 57-75 ◽  
Author(s):  
Marina Vranić ◽  
Mladen Knežević ◽  
Zsolt Seregély ◽  
Krešimir Bošnjak ◽  
Josip Leto ◽  
...  
Keyword(s):  
Protein Content ◽  
Crude Protein ◽  
Dry Matter ◽  
Near Infrared ◽  
Chemical Constituents ◽  
Nir Spectroscopy ◽  
Meat Production ◽  
Crude Protein Content ◽  
Near Infrared Reflectance ◽  
Grass Silage

Intensive livestock feeding requires constant monitoring of diet composition to ensure a consistent level of milk or meat production. A rapid analysis of fresh grass silage samples for dry matter (DM) and crude protein (CP) content would provide basic, rapid information what would permit decision to be made regarding the need to supplement the diet. The aim of the present study was to determine dry matter (DM) and crude protein (CP) content in fresh grass silage samples by NIR spectroscopy. Crude protein content can be expressed as g per kg dry matter (g kg-1 DM) or as per cent of fresh weight (% FW). Near-infrared reflectance spectra were recorded for 103 fresh grass silage samples. Laboratory analysis of DM and CP were determined for these samples. MLR, PCR and PLS techniques were used for data modelling to determine the optimum models for predicting each of the chemical constituents. It was concluded that the PLS method was superior to the PCR and MLR methods for DM and CP prediction in fresh grass silage samples, while MLR showed a promising possibility to determine the CP content using only two spectral values measured at two “characteristic”wavelengths.

Comparative study of the carcass characteristics and nutrient composition of three species of giant African land snail

2020 ◽  
Vol 47 (3) ◽  
pp. 155-161
Author(s):  
O. A. Ekine ◽  
D. N. Onunkwo
Keyword(s):  
Comparative Study ◽  
Crude Protein ◽  
Dry Matter ◽  
Moringa Oleifera ◽  
Live Weight ◽  
Dietary Treatment ◽  
Fat Content ◽  
Carcass Composition ◽  
Southeastern Nigeria ◽  
Nutrient Compositions

A comparative study was carried out on three breeds of snails in southeastern Nigeria to assess their carcass characteristic and carcass nutrient compositions. The three breeds used were Achatina fulica, Achatina achatina and Archachatina marginata. Four experimental diets were formulated to contain concentrate + pawpaw (Diet I), concentrate + Moringa oleifera (Diet II), concentrate + Moringa oleifera+ African spinach + Amaranthus hybridus (Diet III) and concentrate + Moringa oleifera+Amaranthus spinosus (Diet IV). Fifteen 6-month old growing snails of each breed was assigned per dietary treatment and each dietary treatment was replicated three times to contain five snails per replicate, given a total of one hundred and eighty snails. The experiment involved a 3 x 4 factorial experiment in a completely randomized design (CRD). Feed and water were given ad libitum throughout the duration of the experiment which lasted (56 days). At the end of the experiment, a total of seventy-two (72) snails were starved and slaughtered for carcass evaluation. Carcass nutrient compositions were measured including dry matter, moisture content, ash, crude fibre, crude protein, fat and nitrogen free extract. The results showed that the highest foot weight (57.50%) was observed in snails fed diet I, associated with relatively high live weight and highly reduced offal weight, which makes it comparatively better in improving carcass. The A. fulica, A achatina and A. marginata obtained best carcass composition respectively on diets I, III and II due to interaction effect of breed x diet. The A. achatina and A. marginata had higher dry matter (91.64 and 92.07 respectively) than the A fulica (90.09). The A. marginata carcass had the higher (p<0.05) crude protein (32.78%), highest ash (9.17%) and a moderate fat content (1.59%). Based on overall interaction effects, diet I is recommended for A. fulica, while diet III for A. marginata and diet II for A. marginata. The A. marginata performed better than the A. achatina and A. fulica in highest crude protein, highest ash and a moderate fat content and is thus recommended.

scholarly journals MODEL PENDUGAAN KANDUNGAN AIR, LEMAK DAN ASAM LEMAK BEBAS PADA TIGA PROVENAN BIJI JARAK PAGAR (Jatropha curcas L.) MENGGUNAKAN SPEKTROSKOPI INFRAMERAH DEKAT DENGAN METODE PARTIAL LEAST SQUARE (PLS)

2020 ◽  
Vol 19 (4) ◽  
pp. 203
Author(s):  
LADY C. E. CH. LENGKEY ◽  
I WAYAN BUDIASTRA ◽  
KUDANG B. SEMINAR ◽  
BAMBANG S. PURWOKO
Keyword(s):  
Moisture Content ◽  
Standard Error ◽  
Near Infrared ◽  
Seed Quality ◽  
Nir Spectroscopy ◽  
Fat Content ◽  
Partial Least Square ◽  
Least Square ◽  
Physic Nut ◽  
Near Infrared Reflectance

<p>ABSTRAK<br />Jarak pagar berpotensi sebagai sumber biodiesel karena kandungan<br />lemak yang tinggi (&gt;40%) dan belum ada penggunaan lainnya.<br />Spektroskopi (Near Infrared) NIR adalah metode yang cepat untuk<br />mengukur spektrum sampel dan tidak terdapat limbah kimia. Tujuan<br />penelitian adalah mengembangkan metode pendugaan komposisi kimia<br />beberapa  provenan  jarak  pagar  berdasarkan  spektroskopi  NIR<br />menggunakan kalibrasi PLS. Pengujian dilakukan menggunakan tiga<br />provenan jarak pagar yaitu IP-3A, IP-3M, dan IP-3P masing-masing 85<br />sampel. Spektrum reflektansi diukur menggunakan alat NIRFlex Solids<br />Petri pada panjang gelombang 1000–2500 nm. Sekitar ⅔ jumlah sampel<br />digunakan untuk mengembangkan persamaan kalibrasi dan ⅓ jumlah<br />sampel untuk validasi. Pra perlakuan data spektrum dilakukan dengan<br />normalisasi antara 0-1, turunan pertama Savitzky-Golay 9 titik dan<br />gabungan keduanya. Hasil penelitian menunjukkan spektroskopi NIR<br />dapat menduga kadar air, lemak, dan asam lemak bebas . Koefisien<br />korelasi (r) antara komponen kimia metode acuan dengan dugaan NIR<br />&gt;0,83 menunjukkan ketepatan model cukup baik (r kadar air=0,96, r kadar<br />lemak=0,92, dan r ALB=0,89 ). Konsistensi model kalibrasi kadar<br />air=94,85%, lemak=82,56%, dan ALB=87,80%. Koefisien keragaman<br />dugaan (Prediction Coeficient Variability/PCV) ketiga model &lt;10%<br />menunjukkan model yang dibangun cukup handal. Ratio of standard error<br />prediction to deviation (RPD) menunjukkan metode spektroskopi NIR<br />dapat digunakan untuk menentukan kadar air (RPD=3,30) dan lemak<br />(RPD=2,06). Model-model yang dikembangkan secara umum layak<br />untuk menentukan kadar air dan lemak biji jarak pagar, tetapi belum<br />optimal untuk penentuan kadar ALB biji jarak pagar.<br />Kata kunci: NIR , jarak pagar, kadar air, kadar lemak, kadar asam lemak<br />bebas</p><p>ABSTRACT<br />Physic nut is a potential source of biodiesel. It is high in fat content,<br />above 40% and has not been usesed for other purposes. Moisture, free fatty<br />acid, and fat content are the chemical compounds and determinant factor<br />for physic nut seed quality. The objective of this study was to develop a<br />method to predict chemical composition of physic nut by NIR<br />spectroscopy and PLS calibration. The study was conducted using three<br />provenances of physic nut, i.e. IP-3A, IP-3M, and IP-3P, with 85 samples<br />each. The wavelengths of near infrared reflectance ranged from 1000 to<br />2500 nm, and measured by NIR Flex Solids Petri Apparatus.<br />Approximately ⅔ of total samples were used for developing calibration<br />equation, while ⅓ of total samples for performing validation. Pre-treatment<br />of spectrum data was done by applying normalization, first derivative of<br />Savitzky–Golay 9 points, and as well as their combination. The results<br />showed that NIR spectroscopy performed acceptable prediction for<br />moisture and fat content. Correlation coefficients (r) between the reference<br />method and NIR prediction were 0.96 for moisture content, 0.92 for fat<br />content, and 0.89 for FFA and the consistency of the model were 94.85%<br />for moisture content, 82.56% for fat, and 87.80% for FFA. Prediction of<br />coefficient of variability (PCV) of the three models ≤10 % shows that the<br />models are reliable. Ratio of standard error prediction to deviation (RPD)<br />for moisture content has the potential to be used for screening (RPD=3.30)<br />though the fat content model has rough screening (RPD=2.06).<br />Key words: NIR, physic nut, moisture, fat, free fatty acid contents.</p>

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.

Prediction of crude protein content in field peas using near infrared reflectance spectroscopy

2006 ◽  
Vol 86 (1) ◽  
pp. 157-159 ◽  
Author(s):  
G. C. Arganosa ◽  
T. D. Warkentin ◽  
V. J. Racz ◽  
S. Blade ◽  
C. Phillips ◽  
...  
Keyword(s):  
Crude Protein ◽  
Near Infrared ◽  
Spectroscopic Method ◽  
Correlation Coefficients ◽  
Reflectance Spectroscopy ◽  
Field Pea ◽  
Infrared Reflectance ◽  
Near Infrared Reflectance Spectroscopy ◽  
Near Infrared Reflectance ◽  
Infrared Reflectance Spectroscopy

A rapid, near-infrared spectroscopic method to predict the crude protein contents of 72 field pea lines grown in Saskatchewan, both whole seeds and ground samples, was established. Correlation coefficients between the laboratory and predicted values were 0.938 and 0.952 for whole seed and ground seed, respectively. Both methods developed are adequate to support our field pea breeding programme. Key words: Field pea, near-infrared reflectance spectroscopy, crude protein

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