Sultan Qaboos University Journal for Scientific Research Agricultural and Marine Sciences, 10(1):13-19 (2005) ©2005 Sultan Qaboos University 13 * Corresponding author Prediction of Composition of Broiler Chicken Excreta Using Near-infrared Reflectance Spectroscopy I. T. Kadim*, W. Al-Marzooqi, O. Mahgoub and K. Annamalai Department of Animal and Veterinary Sciences, College of Agricultural and Marine Sciences, Sultan Qaboos University, PO Box 34, Al-Khod, PC 123, Muscat, Sultanate of Oman التنبؤ بالمكونات الكیمیائیة لفضالت الدواجن بأستخدام جھاز معامل االنعكاس باالشعة تحت الحمراء عصام توفیق كاظم الجافة المادة بمحتوى للتنبؤ المطیاف باستخدام الحمراء تحت باألشعة االنعكاس معامل جھاز معايیر تطوير تم الخالصة: فضالت من عینات في والفوسفات والكالسیوم الكلیة والطاقة والحوامض القواعد في الذائبة واأللیاف والدھون والنیتروجین الدجاج الالحم. ثم تحلیل التكوين الكیمائي لبراز الدجاج الالحم بطرق التحلیل الكیمیائیة التقلیدية بالمختبر ومقارنتھا بنتائج جھاز المطیاف تم تجفیف اثنان وسبعون عینة من برا فضالت الدجاج الالحم بدرجة حرارة 60 درجة مئوية تم تحلیلھا لتحديد مستوى المادة الجافة والنیتروجین والدھون واأللیاف الذائبة في القواعد والحوامض والطاقة الكلیة والكالسیوم والفوسفات وكانت قراءات المتوسط العام ومعامل اإلنحراف القیاسي كاآلتي :للمادة الجافة 31.46±7.65 (المدى: 44.51-19.14) والناتروجین 2.88±5.85 (المدى: 1.99±16.7: الحامضیة المحالیل في الذائبة وااللیاف )1.99-0.88 (المدى: 0.25±1.37 4.85-7.00)والدھون )تامدى 0.99±15.27 الكلیة: والطاقة (30.21±22.03 (المدى: 1.63±26.26 القفاعدية المحالیل في الذائبة االلیاف و (19.97-12.11 ثم .(2.11-1.41 (المدى: 0.15±1.79 الفوسفات: و (3.01-2.16 (المدى: 0.22±2.57 والكالسیوم: (16.11-14.52 (المدى: فحصت العینات باستخدام المطیاف موديل 5000 وحدد الخط الطیفي لكل عینة. طورت معادالت المعايرة وقیم التنبؤ لعینات براز الدجاج الالحم كما تم تطوير أنظمة البرنامج لحساب التراجع التربیعي االقل التي تعتبر اكثر مالئمة للمنتجات الطبیعة. وكانت فحصت العینات باستخدام المطیاف موديل 5000 وحدد الخط الطیفي لكل عینة. طورت معادالت المعايرة وقیم التنبؤ لعینات براز الدجاج الالحم كما تم تطوير أنظمة البرنامج لحساب التراجع التربیعي االقل التي تعتبر اكثر مالئمة للمنتجات الطبیعة. وكانت فحصت العینات باستخدام المطیاف موديل 5000 وحدد الخط الطیفي لكل عینة. طورت معادالت المعايرة وقیم التنبؤ لعینات براز R) والخطأ المعیاري المتوقع لعینات من فضالت دجاج االحم للمادة الجافة 0.97 و 1.27وللناتروجین 0.95 و 0.72 الدجاج الالحم كما تم تطوير أنظمة البرنامج لحساب التراجع التربیعي االقل التي تعتبر اكثر مالئمة للمنتجات الطبیعة. وكانت R) والخطأ المعیاري المتوقع لعینات من فضالت دجاج االحم للمادة الجافة 0.97 و 1.27وللناتروجین 0.95 و 0.72 الدجاج الالحم كما تم تطوير أنظمة البرنامج لحساب التراجع التربیعي االقل التي تعتبر اكثر مالئمة للمنتجات الطبیعة. وكانت 2 معامل التقدير( وللدھون 0.92 و 0.07 و لاللیف الذائبة في الحوامض 0.87 و 0.78 و لاللیاف الذائبة في القواعد 0.88 و 0.72 و للطاقة الكلیة 0.89 و 0.24 و للكاسیوم 0.96 و 0.06 و للفسفور 0.93 و 0.09 باتتابع. أشارت نتائج ھذا البحث إلى امكانیة استخدام معیار المطیاف وللدھون 0.92 و 0.07 و لاللیف الذائبة في الحوامض 0.87 و 0.78 و لاللیاف الذائبة في القواعد 0.88 و 0.72 و للطاقة الكلیة 0.89 و 0.24 و للكاسیوم 0.96 و 0.06 و للفسفور 0.93 و 0.09 باتتابع. أشارت نتائج ھذا البحث إلى امكانیة استخدام معیار المطیاف وللدھون 0.92 و 0.07 و لاللیف الذائبة في الحوامض 0.87 و 0.78 و لاللیاف الذائبة في القواعد 0.88 و 0.72 و للطاقة الكلیة 0.89 للتنبؤ بمكونات فضالت الدجاج الالحم. ABSTRACT: Near-infrared reflectance spectroscopic (NIRS) calibrations were developed for the prediction of the content of dry matter (DM); nitrogen (N), ether extract (EE), neutral detergent fibre (NDF), acid detergent fibre (ADF), gross energy (GE), calcium (Ca) and phosphate (P) in broiler excreta samples. The chemical composition of broiler excreta was determined by the conventional chemical analysis methods in the laboratory and compared with NIRS. Excreta samples (n = 72) were oven dried (60 oC) and analyzed for DM, N, EE, NDF, ADF, GE, Ca and P. The determined values (mean ± SD) were as follows: DM: 31.46 ± 7.65 (range:19.14 - 44.51), N: 5.85 ± 2.88 (range: 4.85 -7.00), EE: 1.37 ± 0.25 (range: 0.88-1.99), ADF: 16.71 ± 1.99 (range: 12.11-19.97), NDF: 26.26 ± 1.63 (range: 22.03-30.21), GE: 15.27 ± 0.33 (range: 14.52-16.11), Ca: 2.57 ± 0.22 (range: 2.16-3.01), P: 1.79 ± 0.15 (range: 1.41-2.11). The samples were then scanned in a NIRS model 5000 analyzer and the spectra obtained for each sample. Calibration equations and prediction values were developed for broiler excreta samples. The software used modified partial least square regression statistic, as it is most suitable for natural products. For broiler excreta samples, the coefficient of determination (R2) and the standard error of prediction (SEP) was DM = 0.97, 1.27, N = 0.95, 0.72, EE = 0.92, 0.07, ADF = 0.87, 0.78, NDF = 0.88, 0.72, GE = 0.89; 0.24, Ca = 0.96, 0.06, P = 0.93, 0.09, respectively. The results indicate that it is possible to calibrate NIRS to predict major constituents in broiler excreta samples. Keywords: Spectroscopy, broiler, excreta, calibration, Oman. Introduction Poultry manure, which is a pollutant in soil and water, is produced in large quantities by the poultry industry. An accurate and fast analytical procedure to detect poultry manure components is becoming more critical in areas with intensive poultry production (Reeves, 2001). In some countries, restrictive manure management guidelines have been adopted, which Kadim et. al. 14 need a quick, easy and reliable method for determining excreta composition to assist those abiding by and enforcing regulations. To manage these pressures, it is necessary to collect as much information as possible on raw materials, which depend on analytical laboratory techniques. Traditionally, chemical reference methods are laborious, time consuming and generate hazardous wastes. Near-infrared reflectance spectroscopy (NIRS) has been widely used as a rapid and accurate method for measuring some constituents of materials without requiring extensive sample preparation (Norris et al., 1976). Components successfully measured include nitrogen, moisture, fibre, starch, individual sugar, amino acids, and fat (Foley et al., 1998; Fontaine et al., 2002; Smith et al., 2001; Valdes and Summers, 1986), The principle of NIRS is the selective absorption of electromagnetic radiation from 800 to 2500 nm in accordance with the characteristic vibration frequencies of functional groups (De Boever et al., 1994). It has the capability to measure CH, NH, OH bonds, which form the functional groups in moisture, protein, amino acids, fibre, sugar and fat in biological samples. Although organic complexes may be detected (Shenk et al., 1992), no absorption bands for minerals exist in the near-infrared region. Every biological substance has a unique NIRS composite spectrum, depending on their characteristic functional groups; the NIRS spectrum of a sample is the composition of all the physical and chemical information of the sample (De Boever et al., 1994; Murray and Williams, 1987). The objectives of the current study were to calibrate NIRS spectrometer equations and to evaluate their accuracy to predict chemical composition, moisture, nitrogen, ether extract, neutral detergent fibre, acid detergent fibre, gross energy, calcium and phosphorus in broiler excreta. Materials and Methods Seventy-two broiler excreta samples (500 g) were randomly collected from a broiler feed evaluation project. The excreta samples were dried in a forced air oven at 60 oC until no decrease in weight occurred. All samples were then left on the laboratory bench for over 48 h to equilibrate with atmospheric moisture. The samples were ground in a Cyclotech 1093 sample mill with a 0.5-mm screen and were stored in plastic bags until analysis. Laboratory analysis Excreta samples were analysed for dry matter (DM) by drying in an oven at 60 oC until no decrease in weight occurred, and for organic matter (OM) and ash by ashing dry samples at 450 oC for 12 h in a muffle furnace (AOAC, 1990). Triplicate samples of approximately 2 g each were freeze-dried for 4 days for ether extraction (EE) by petroleum ether in a Soxhlet apparatus. Nitrogen (N) was determined by the Kjeldahl method. Neutral detergent fibre (NDF) was determined by using sodium sulphite and sodium lauryl sulphate as a neutral detergent extracting solution as described by Van Soest et al. (1991). Acid detergent fibre (ADF) was determined using Table 1. Values for chemical analysis in 72 broiler excreta samples used for the near-infrared reflectance equation .and validation. Variable Mean SD Range SEC SECV R2 1-VR Dry matter (%) 31.46 7.65 19.14-44.51 1.18 1.27 0.97 0.97 Nitrogen (%) 5.85 2.88 4.85-7.00 0.64 0.72 0.95 0.93 Ether extract (%) 1.38 0.25 0.88-1.99 0.07 0.07 0.92 0.91 Acid detergent fibre (%) 16.72 1.99 12.11-19.97 0.71 0.78 0.87 0.85 Neutral detergent fibre (%) 26.26 1.63 22.03-30.21 0.55 0.72 0.88 0.81 Gross energy (MJ/kg) 15.27 0.33 14.52-16.11 0.22 0.24 0.89 0.47 Calcium (%) 2.57 0.22 2.16-3.01 0.04 0.06 0.96 0.92 Phosphorous (%) 1.79 0.15 1.41-2.11 0.08 0.09 0.93 0.61 SD: Standard Deviation, SEC: Standard Error of Calibration, SECV: Standard Error of Cross Validation, R2: coefficient of determination, 1-VR: 1- Variance Ratio. Prediction of composition of broiler chicken excreta using near-IR reflectance spectroscopy 15 cetyl trimethyl ammonium bromide and 1N H2SO4 as described by Roberston and Van Soest (1981). Calcium (Ca) and phosphorus (P) were measured with an atomic absorption spectrophotometer (PHILIPS model PU9100, single beam) according the procedures of AOAC (1990). Gross energy (GE) was measured using a bomb calorimeter. Analysis for all items was done in triplicate on a dry matter basis. Near-infrared reflectance spectroscopy analysis Samples were divided into calibration and prediction sets, which consisted of 72 and 40 samples, respectively. Prediction samples were randomly selected from the calibration samples. All calibration samples were analysed by conventional chemical methods in the laboratory and then scanned in the NIRS for comparison. A feed and Forage Foss NIRS systems Model 5000 Reflectance Transport Model Analyzer was used for scanning samples and collecting spectra. The software used was WinISI II version 1.50. Interpretation of NIRS spectra was done by calibrating with reference values obtained from laboratory analysis of the sample and correlating them to NIRS measurements of these samples. The reference laboratory data and the sample spectra were used to develop predictive equations. Samples were uniformly mixed and loaded in the NIRS sample cups. About 5-6 g of ground sample were placed in sample cup to about 8 mm depth, then covered to be processed on the holder gently. Consistency in sample preparation and packing is important for accuracy. The NIR spectrum for each sample was recorded as log 1/R (reflectance) for each wavelength in the NIRS range. Calibration The mathematical relationship between chemical reference values and the NIRS spectral data was analysed by linear regression. Calibrations were made using reference values on a dry matter basis, so the NIRS predicted results are also expressed on a dry matter basis. Spectra of 72 broiler excreta samples were collected in the NIRS region (800-2800 nm). Calibration equations were computed for DM, N, EE, ADF, NDF, GE, Ca and P using modified partial least squares regression using the WinISI II software. The program calculates the mathematical relationship between the spectral data from the scanned sample and its reference values obtained by standard chemical procedures. The program then calculates the cross validation errors for each component, and the modified partial least square statistics was determined. The program repeats this process for each component and upon completion, the NIRS equation was developed to predict the constituents in the product. Statistically, the equation was evaluated using the monitor results program, which performs a statistical comparison between chemical reference values and NIRS predicted values for the data set. It also provided tabular and graphical comparison of the two values. Model performance was reported as the coefficient of determination (R2), standard error of prediction (SEP), and linear regression of components reference method against predicted values (slope) (Hurschka, 1987). Results and Discussion The descriptive statistics for the different constituents of broiler excreta are summarized in Tables 1 and 2. There was a considerable variation in the composition, Table 2. Near-infrared transmission calibration and validation statistics for broiler excreta. Variable Mean SD Range SEP Bias R2 Slope Dry matter (%) 31.20 7.44 20.93-42.81 1.56 0.188 0.96 1.01 Nitrogen (%) 5.97 2.59 5.22-6.80 0.77 0.125 0.93 1.04 Ether extract (%) 1.38 0.27 0.86-1.91 0.10 0 0.88 1.01 Acid detergent fibre (%) 17.20 1.41 14.06-19.32 1.07 0.053 0.65 1.05 Neutral detergent fibre (%) 26.50 1.47 22.37-29.51 0.83 0.048 0.73 0.94 Gross energy (MJ/kg) 15.20 0.22 14.77-15.63 0.31 0.043 0.85 0.99 Calcium (%) 2.57 0.19 2.22-2.97 0.07 0.004 0.89 0.97 Phosphorous (%) 1.79 0.11 1.52-2.01 0.11 0.023 0.91 0.82 SEP: Standard Error of Prediction. Kadim et. al. 16 Figure 1. The relationship between near-infrared reflectance spectroscopy (NIRS) predictions and determined percentage dry matter values of 72 broiler excreta samples. Figure 2. The relationship between near-infrared reflectance spectroscopy (NIRS) predictions and determined nitrogen values (%) of 72 broiler excreta samples. as shown by the wide range of values. It is essential for any calibration procedure to ensure that a range of spectral variation found in the whole population is represented in the samples selected for calibration development (Foley et al., 1998). Calibration and validation statistics are shown in Tables 1 and 2, respectively. The range of excreta parameters of DM, N, EE, NDF, ADF, GE, Ca and P in the calibration set are similar to the corresponding ranges in the prediction set. Limited studies have been conducted utilizing NIRS to analyse the chemical composition of poultry manure or excreta (Reeves, 2001; Smith et al., 2001). Contradictory conclusions have been reported by these authors on the suitability of the NIRS to estimate the mineral contents. The findings of Reeves (2001) indicated that NIRS was not suitable for the determination of minerals (P, Ca, etc.) in poultry manure. This may be attributed to the nature of the samples being used. However, Smith et al. (2001) attempted to calibrate an NIRS to predict the Ca and P contents of chicken excreta. They obtained an R2 of 0.86, an SEP of 0.14 for Ca and R2 0.93 and an SEP of 0.13 for P. They concluded that NIRS was a good predictor for Ca and total P content of chick excreta. There are no absorption bands for minerals in the near-infrared region, but organic complexes and chelates may still be detected (De Boever et al., 1994). Studies have shown that Ca and P may exist in forms detectable by NIRS, at least in some grasses and legumes (Clark et al., 1987; Saiga et al., 1989). The calibration values obtained for P in forages were Figure 3. The relationship between near-infrared reflectance spectroscopy (NIRS) predictions and determined fat values (%) of 72 broiler excreta samples. Figure 4. The relationship between near-infrared reflectance spectroscopy (NIRS) predictions and determined gross energy values (%) of 72 broiler excreta samples. Prediction of composition of broiler chicken excreta using near-IR reflectance spectroscopy 17 found to be acceptable by Clark et al. (1987) but were not acceptable in similar studies by Vasquez Aldana et al. (1995). De Boever et al. (1994) reported that P of feedstuffs could be predicted by NIRS with an R2 of 0.94 to 0.96 and SEP of 0.08. In grass samples, Dealdana et al. (1995) found that Ca could be predicted with an R2 0.73 to 0.92 and an SEP 0.15 to 0.22. The estimation of mineral elements by NIRS is generally dependent on the occurrence of these elements in organic or hydrated molecules (Clark et al., 1987; Vasquez de Aldana et al., 1995), or mineral levels may simply be correlated to some organic material that the NIRS can easily measure. The findings of the present study confirm previous reports that NIRS is a good predictor for Ca and P with an R2 of 0.89 and 0.91, respectively. Similarly, high coefficients of determination and relatively low SEP were obtained in the present study for DM (R2, 0.96, SEP, 1.56) (Figure 1), N (R2, 0.93, SEP, 0.77) (Figure 2), fat (R2, 0.88, SEP, 0.10) (Figure 3), GE (R2, 0.85, SEP, 0.31) (Figure 4), ADF (R2, 0.65, SEP, 1.07) (Figure 5), NDF (R2, 0.73, SEP, 0.83) (Figure 6), Ca (R2, 0.89, SEP, 0.07) (Figure 7) and P (R2, 0.91, SEP, 0.11) (Figure 8). There have been some studies utilizing NIRS to analyse the moisture and N content of excreta samples. Smith et al. (1999) reported an R2 of 0.97 with an SEP of 0.91 for determining the N content of rooster excreta and an R2 of 0.92 with an SEP of 0.13 for GE determination. Smith et al. (2001) reported an R2 of 0.93 with an SEP of 0.34 for moisture and an R2 Figure 5. The relationship between near-infrared reflectance spectroscopy (NIRS) predictions and determined acid detergent fibre values (%) of 72 broiler excreta samples. Figure 6. The relationship between near-infrared reflectance spectroscopy (NIRS) predictions and determined neutral detergent fibre values (%) of 72 broiler excreta samples. Figure 8. The relationship between near-infrared reflectance spectroscopy (NIRS) predictions and determined phosphorous values (%) of 72 broiler excreta samples. Figure 7. The relationship between near-infrared reflectance spectroscopy (NIRS) predictions and determined calcium values (%) of 72 broiler excreta samples. Kadim et. al. 18 of 0.99 with an SEP of 0.19 for N contents of chicken excreta, thus supporting the findings of the present study. Conclusions The current study has indicated that determination of the composition of broiler excreta by NIRS is feasible with high accuracy. Therefore, NIRS may be routinely used to predict excreta constituents. It may also be useful in monitoring environmental contamination by the poultry industry. 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