新疆沙尔套山天然草地主要混合牧草营养指标近红外光谱分析
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摘要
为了对新疆沙尔套山天然草地主要牧草营养指标进行快速、无损检测,本试验采用近红外光谱技术(Near infrared reflectance spectroscopy,NIRS),进行修正偏最小二乘回归法(Modified partial least squares,MPLS),结合散射处理、导数、平滑等不同的光谱预处理和数学处理方法,建立了32种主要牧草(草粉)的粗蛋白(Crude protein,CP)、中性洗涤纤维(Neutral detergent fiber,NDF)、酸性洗涤纤维(Acid detergent fiber,ADF)、粗灰分(Ash)、钙(Ca)和磷(P)的校正模型。结果表明:CP、NDF、ADF、Ash、Ca和P的交叉检验决定系数(R2)分别为0.82,0.80,0.78,0.50,0.72和0.65,交叉验证标准误差(Standard error of cross validation,SECV)分别为2.36,6.17,3.87,0.85,0.24和0.07,交叉验证相对分析误差(Relative percent deviation of cross validation,RPDCV)分别为2.78,2.26,2.39,1.92,2.39和1.65。最后结合外部验证集对各矫正模型进行验证。试验得出CP、NDF、ADF外部验证相对分析误差分别为2.67,2.20和2.28,相关性分别为0.66,0.73和0.84,其模型精确度和验证准确度还有待提高;利用近红外光谱检测技术不能建立Ash、Ca和P的检测模型。
In order to test main herbage nutrition in natural grassland rapidly and nondestructively,Shaertao mountain,Xinjiang,using near infrared spectroscopy(NIRS)to perform the modified partial least squares(MPLS).In combination with different spectral pretreatments and mathematical treatment methods such as scattering,derivative,smooth and other different spectra pretreatment and mathematical processing methods were used to establish the calibration model of 32 kinds main forage(grass meal)on crude protein(CP),neutral detergent fiber(NDF),acid detergent fiber(ADF)and crude Ash(Ash),calcium(Ca)and phosphorus(P).The results showed that the cross-examination determination coefficient(R2)of CP,NDF,ADF,Ash,Ca and P were 0.82,0.80,0.78,0.50,0.72 and 0.65,the standard error of cross validation(SECV)were 2.36,6.17,3.87,0.85,0.24 and 0.07,and relative percent deviation of cross validation(RPDCV)were 2.78,2.26,2.39,1.92,2.39 and 1.65,respectively.Finally,the correction model is validated by external validation set.The correlation is 0.66,0.73 and 0.84 respectively,and the accuracy of the model is still need to be improved.The detection model of Ash,Ca and P cannot be established by using NIRS.
In order to test main herbage nutrition in natural grassland rapidly and nondestructively,Shaertao mountain,Xinjiang,using near infrared spectroscopy(NIRS)to perform the modified partial least squares(MPLS).In combination with different spectral pretreatments and mathematical treatment methods such as scattering,derivative,smooth and other different spectra pretreatment and mathematical processing methods were used to establish the calibration model of 32 kinds main forage(grass meal)on crude protein(CP),neutral detergent fiber(NDF),acid detergent fiber(ADF)and crude Ash(Ash),calcium(Ca)and phosphorus(P).The results showed that the cross-examination determination coefficient(R2)of CP,NDF,ADF,Ash,Ca and P were 0.82,0.80,0.78,0.50,0.72 and 0.65,the standard error of cross validation(SECV)were 2.36,6.17,3.87,0.85,0.24 and 0.07,and relative percent deviation of cross validation(RPDCV)were 2.78,2.26,2.39,1.92,2.39 and 1.65,respectively.Finally,the correction model is validated by external validation set.The correlation is 0.66,0.73 and 0.84 respectively,and the accuracy of the model is still need to be improved.The detection model of Ash,Ca and P cannot be established by using NIRS.
引文
[1]许鹏.草地资源与调查[M].北京:中国农业出版社,1999:138
[2]聂志东,韩建国,张录达,等.近红外光谱技术(NIRS)在草地生态学研究中的应用[J].光谱学与光谱分析,2007,27(4):691-696
[3]Norris K H,Barnes R F,Moore J E,et al.Prediction forage quality by NIRS[J].Journal of Animal Science,1976,43(4):899-897
[4]Marten G C,Brink G E,Buxton D R,et al.Near infrared reflectance spectroscopy analysis of forage quality in four legume species[J].Crop Science,1984,24(6):1179-1182
[5]刘哲,王玉琴,薛树媛,等.近红外漫反射光谱定量分析天然牧草营养成分[J].草地学报,2018,26(1):249-255
[6]Hansen J L,Viands D R,Steffens J C,et al.Heritability and improvement of protein and nitrogen concentrations in wilted alfalfa forage[J].Crop Science,1992,32(4):879-883
[7]滑荣,韩建国,齐晓,等.近红外漫反射光谱法预测紫花苜蓿草颗粒营养价值[J].光谱学与光谱分析,2008,28(12):2826-2829
[8]尚晨,张月学,李炎,等.紫花苜蓿粗蛋白和粗纤维近红外分析模型的建立[J].光谱学与光谱分析,2009,29(12):3250-3253
[9]严旭,白史且,鄢家俊,等.近红外光谱技术(NIRS)在牧草领域中的应用研究进展[J].光谱学与光谱分析,2012,32(7):1748-1753
[10]Ruano-Ramos A,GarciA-Ciudad A,GarciA-Criado B.Near infrared spectroscopy prediction of mineral content in botanical fractions from semi-arid grasslands[J].Animal Feed Science and Technology,1999,77(3-4):331-343
[11]薛祝林,刘楠,张英俊.近红外光谱法预测紫花苜蓿草捆的营养品质和消化率[J].草地学报,2017,25(1):165-171
[12]张凡凡,于磊,张前兵,等.沙尔套山天然割草场主要豆科牧草营养价值综合评价研究[J].新疆农业科学,2014,51(10):1907-1915
[13]张凡凡,和海秀,于磊,等.天山西部高山区夏季放牧草地4种重要牧草营养品质评价[J].草业学报,2017,26(8):207-215
[14]国家技术监督局.GB/T 14924.9-2001实验动物配合饲料常规营养成分的测定[S].北京:中国标准出版社,2002
[15]Park R S,Agnew R E,Gordon F J,et al.The use of near infrared reflectance spectroscopy(NIRS)on undried samples of grass silage to predict chemical composition and digestibility parameters[J].Animal Feed Science and Technology,1998,72(1-2):155-167
[16]赵环环,胡跃高,赵其波,等.近红外光谱分析技术在黑麦草粉粗蛋白测定中的应用[J].动物营养学报,2001,13(4):40-43
[17]赵秀芳,李卫建,黄伟,等.燕麦干草品质的近红外光谱定量分析[J].光谱学与光谱分析,2008,28(9):2094-2097
[18]石丹,张英俊.近红外光谱法快速测定羊草干草品质的研究[J].光谱学与光谱分析,2011,31(10):2730-2733
[19]Lindgren E.Prediction of energy value and protein content of forages by near infrared reflectance spectroscopy[J].Swedish Journal of Agricultural Research,1988,18(1):21
[20]陆婉珍,袁洪福,徐广通,等.现代近红外光谱分析技术[M].北京:中国石化出版社,2000:208-210
[21]Cozzolino D,Moron A.Exploring the use of near infrared reflectance spectroscopy(NIRS)to predict trace minerals in legumes[J].Animal Feed Science and Technology,2004,111(1-4):161-173
[22]Ruano-Ramos A,García-Ciudad A,García-Criado B.Determination of nitrogen and ash contents in total herbage and botanical components of grassland systems with near infra-red spectroscopy[J].Journal of the Science of Food and Agriculture,1999,79(1):137-143
[23]Cozzolino D,Fassio A,Gimenez A.The use of near-infrared reflectance spectroscopy(NIRS)to predict the composition of whole maize plants[J].Journal of the Science of Food and Agriculture,2001,81(1):142-146
[2]聂志东,韩建国,张录达,等.近红外光谱技术(NIRS)在草地生态学研究中的应用[J].光谱学与光谱分析,2007,27(4):691-696
[3]Norris K H,Barnes R F,Moore J E,et al.Prediction forage quality by NIRS[J].Journal of Animal Science,1976,43(4):899-897
[4]Marten G C,Brink G E,Buxton D R,et al.Near infrared reflectance spectroscopy analysis of forage quality in four legume species[J].Crop Science,1984,24(6):1179-1182
[5]刘哲,王玉琴,薛树媛,等.近红外漫反射光谱定量分析天然牧草营养成分[J].草地学报,2018,26(1):249-255
[6]Hansen J L,Viands D R,Steffens J C,et al.Heritability and improvement of protein and nitrogen concentrations in wilted alfalfa forage[J].Crop Science,1992,32(4):879-883
[7]滑荣,韩建国,齐晓,等.近红外漫反射光谱法预测紫花苜蓿草颗粒营养价值[J].光谱学与光谱分析,2008,28(12):2826-2829
[8]尚晨,张月学,李炎,等.紫花苜蓿粗蛋白和粗纤维近红外分析模型的建立[J].光谱学与光谱分析,2009,29(12):3250-3253
[9]严旭,白史且,鄢家俊,等.近红外光谱技术(NIRS)在牧草领域中的应用研究进展[J].光谱学与光谱分析,2012,32(7):1748-1753
[10]Ruano-Ramos A,GarciA-Ciudad A,GarciA-Criado B.Near infrared spectroscopy prediction of mineral content in botanical fractions from semi-arid grasslands[J].Animal Feed Science and Technology,1999,77(3-4):331-343
[11]薛祝林,刘楠,张英俊.近红外光谱法预测紫花苜蓿草捆的营养品质和消化率[J].草地学报,2017,25(1):165-171
[12]张凡凡,于磊,张前兵,等.沙尔套山天然割草场主要豆科牧草营养价值综合评价研究[J].新疆农业科学,2014,51(10):1907-1915
[13]张凡凡,和海秀,于磊,等.天山西部高山区夏季放牧草地4种重要牧草营养品质评价[J].草业学报,2017,26(8):207-215
[14]国家技术监督局.GB/T 14924.9-2001实验动物配合饲料常规营养成分的测定[S].北京:中国标准出版社,2002
[15]Park R S,Agnew R E,Gordon F J,et al.The use of near infrared reflectance spectroscopy(NIRS)on undried samples of grass silage to predict chemical composition and digestibility parameters[J].Animal Feed Science and Technology,1998,72(1-2):155-167
[16]赵环环,胡跃高,赵其波,等.近红外光谱分析技术在黑麦草粉粗蛋白测定中的应用[J].动物营养学报,2001,13(4):40-43
[17]赵秀芳,李卫建,黄伟,等.燕麦干草品质的近红外光谱定量分析[J].光谱学与光谱分析,2008,28(9):2094-2097
[18]石丹,张英俊.近红外光谱法快速测定羊草干草品质的研究[J].光谱学与光谱分析,2011,31(10):2730-2733
[19]Lindgren E.Prediction of energy value and protein content of forages by near infrared reflectance spectroscopy[J].Swedish Journal of Agricultural Research,1988,18(1):21
[20]陆婉珍,袁洪福,徐广通,等.现代近红外光谱分析技术[M].北京:中国石化出版社,2000:208-210
[21]Cozzolino D,Moron A.Exploring the use of near infrared reflectance spectroscopy(NIRS)to predict trace minerals in legumes[J].Animal Feed Science and Technology,2004,111(1-4):161-173
[22]Ruano-Ramos A,García-Ciudad A,García-Criado B.Determination of nitrogen and ash contents in total herbage and botanical components of grassland systems with near infra-red spectroscopy[J].Journal of the Science of Food and Agriculture,1999,79(1):137-143
[23]Cozzolino D,Fassio A,Gimenez A.The use of near-infrared reflectance spectroscopy(NIRS)to predict the composition of whole maize plants[J].Journal of the Science of Food and Agriculture,2001,81(1):142-146