近红外光谱技术分析高羊茅干草营养成分含量
English
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参考文献
[1] 陈昌荣, 阮晓贵, 黄琦, 刘琼波, 李文霞, 李飞艳. 野生牧草种质资源保护与开发. 畜牧兽医科学(电子版), 2020(17): 146-147. CHEN C R, RUAN X G, HUANG Q, LIU Q B, LI W X, LI F Y. Conservation and development of wild herbage germolasm resources. Graziery Veterinary Sciences (Electronic Version), 2020(17): 146-147.
[2] 马宏义. 野生牧草种质资源在生态环境中的地位和保护措施. 当代畜牧, 2020(10): 44-45. MA H Y. Status and protection measures of wild forage germplasm resources in ecological environment. Contemporary Animal Husbandry, 2020(10): 44-45.
[3] 吴佳海, 牟琼, 唐成斌, 尚以顺, 莫本田, 瓦庆荣. 牧草新品种黔草1号高羊茅的选育. 贵州农业科学, 2006(4): 75-79. doi: 10.3969/j.issn.1001-3601.2006.04.027 WU J H, MOU Q, TANG C B, SHANG Y S, MO B T, WA Q R. Breeding of qiancao 1, a new festuca arundinacea variety. Guizhou Agricultural Sciences, 2006(4): 75-79. doi: 10.3969/j.issn.1001-3601.2006.04.027
[4] 乔玉梅. 禾本科牧草与大豆秸秆饲用产量和营养品质的研究. 沈阳: 沈阳农业大学博士学位论文, 2008. QIAO Y M. Yield and quality of soybean straw and gramineal forage. PhD Thesis. Shenyang: Shenyang Agricultural University, 2008.
[5] 伍文丹, 雷雄, 赵文达, 杨晓鹏, 熊毅, 熊艳丽, 张新全, 马啸. 饲草型高羊茅引进品种的表型变异分析. 草业科学, 2019, 36(10): 2622-2630. doi: 10.11829/j.issn.1001-0629.2018-0680 WU W D, LEI X, ZHAO W D, YANG X P, XIONG Y, XIONG Y L, ZHANG X Q, MA X. Analysis of phenotypic variation of introduced cultivars of tall fescue. Pratacultural Science, 2019, 36(10): 2622-2630. doi: 10.11829/j.issn.1001-0629.2018-0680
[6] 彭艳, 马素洁, 南吉, 索朗德吉, 魏学红. 西藏林芝地区阿尔冈金紫花苜蓿与高羊茅混播效果研究. 黑龙江畜牧兽医, 2019(16): 129-132. PENG Y, MA S J, NAN J, Suolangdeji, WEI X H. Study on the mixed sowing effect of Algonquin alfalfa and tall fescue in Linzhi, Tibet. Heilongjiang Animal Science and Veterinary Medicine, 2019(16): 129-132.
[7] 陈志敏, 张姝, 王征南, 乌远征. 我国东北、西北地区秸秆牧草类饲料资源常规概略养分含量调查报告. 中国奶牛, 2020(4): 59-62. CHEN Z M, ZHANG S, WANG Z N, WU Y Z. Investigation report on nutrient content of straw and forage feed resources in northeast and northwest China. China Dairy Cattle, 2020(4): 59-62.
[8] ANDERSON J V, WITTENBERG A, LI H, BERTI M T. High throughput phenotyping of Camelina sativa seeds for crude protein, total oil, and fatty acids profile by near infrared spectroscopy. Industrial Crops and Products, 2019, 137: 501-507. doi: 10.1016/j.indcrop.2019.04.075
[9] IKOYI A Y, YOUNGE B A. Influence of forage particle size and residual moisture on near infrared reflectance spectroscopy (NIRS) calibration accuracy for macro-mineral determination. Animal Feed Science and Technology, 2020, 270: 114675.
[10] 李磊, 陈丰. 红外光谱分析技术在化工生产中的应用. 化工设计通讯, 2020, 46(4): 150-156. LI L, CHEN F. Application of infrared spectrum analysis technology in chemical production. Chemical Engineering Design Communications, 2020, 46(4): 150-156.
[11] 张梦璐, 张国权. 红外光谱技术在食品检测中的应用. 中国食品, 2021(7): 95. doi: 10.3969/j.issn.1000-1085.2021.07.054 ZHANG M L, ZHANG G Q. Application of infrared spectroscopy in food detection. China Food, 2021(7): 95. doi: 10.3969/j.issn.1000-1085.2021.07.054
[12] 王娅宁, 薛旭东. 近红外光谱在制药过程控制中的应用分析. 中国卫生产业, 2016, 13(33): 50-52. WANG Y N, XUE X D. Application of near infrared spectroscopy in pharmaceutical process control. China Health Industry, 2016, 13(33): 50-52.
[13] 孙克强, 王京力, 廖佳, 赵珍玉. 近红外光谱技术在纺织产品检测中的应用. 轻纺工业与技术, 2019, 48(8): 189-191. doi: 10.3969/j.issn.2095-0101.2019.08.084 SUN K Q, WANG J L, LIAO J, ZHAO Z Y. Application of near infrared spectroscopy in textile products detection. Light and Textile Industry and Technology, 2019, 48(8): 189-191. doi: 10.3969/j.issn.2095-0101.2019.08.084
[14] 欧宇. 浅谈红外光谱技术在环境科学中的应用与展望. 江西化工, 2021, 37(1): 94-96. doi: 10.3969/j.issn.1008-3103.2021.01.027 OU Y. Application and prospect of infrared spectroscopy in environmental science. Jiangxi Chemical Industry, 2021, 37(1): 94-96. doi: 10.3969/j.issn.1008-3103.2021.01.027
[15] 毛建雄, 肖东, 罗燕, 张翅, 王秀良. 近红外光谱技术在测定新生儿坏死性小肠结肠炎脑血氧饱和度和判定肠坏死程度的探讨. 岭南现代临床外科, 2020, 20(5): 562-566, 572. MAO J X, XIAO D, LUO Y, ZHANG C, WANG X L. Determination of cerebral oxygen saturation and determination of intestinal necrosis in neonatal necrotizing enterocolitis by near infrared spectroscopy. Lingnan Modern Clinics in Surgery, 2020, 20(5): 562-566, 572.
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图 4 营养成分含量的预测值与化学测定值的相关性
Figure 4. Correlation between predicted value and chemical measured value of nutrition component
表 1 高羊茅干草7种营养成分湿化学分析结果(干物质基础)
Table 1 Results of wet chemical analysis of seven nutrients in tall fescue hay (DM basis)
营养成分
Nutrient样本数量
Sample number最小值
Minimum/%最大值
Maximum/%平均值
Mean/%标准差
SD变异系数
CV/%干物质 DM 101 93.71 96.72 95.29 0.55 0.57 粗蛋白 CP 101 11.28 29.71 17.53 3.83 21.86 有机物 OM 101 77.43 98.93 88.95 3.68 4.14 中性洗涤纤维 NDF 101 30.27 58.32 46.26 5.00 10.81 酸性洗涤纤维 ADF 101 14.12 34.01 24.86 3.15 12.69 粗脂肪 EE 101 1.76 5.79 3.56 0.71 19.84 粗灰分 Ash 101 1.07 22.57 11.05 3.68 33.33 DM: dry matter; CP: crude protein; OM: organic matter; NDF: neutral detergent fiber; ADF: acid detergent fiber; EE: ether extract; Ash: crude ash; this is applicable for the following tables as well. 
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表 2 高羊茅干草定标集和验证集各营养成分含量(干物质基础)
Table 2 Nutrient content in the calibration set and validation set of tall fescue hay (DM basis)
样品类别
Sample sort营养成分
Nutrient样本数量
Sample number最小值
Minimum/%最大值
Maximum/%平均值
Mean/%标准差
SD变异系数
CV/%定标集
Calibration set干物质 DM 81 93.71 96.72 95.30 0.55 0.58 粗蛋白 CP 81 11.28 29.71 17.61 3.89 22.09 有机物 OM 81 77.43 98.93 89.03 3.69 4.15 中性洗涤纤维 NDF 81 30.27 58.32 46.38 5.00 10.77 酸性洗涤纤维 ADF 81 14.12 34.01 24.94 3.18 12.76 粗脂肪 EE 81 1.76 5.79 3.57 0.71 20.00 粗灰分 Ash 81 1.07 22.57 11.14 3.75 33.64 验证集
Validation set干物质 DM 20 94.29 96.30 95.25 0.51 0.54 粗蛋白 CP 20 11.40 25.06 17.21 3.58 20.77 有机物 OM 20 79.37 94.78 88.38 3.90 4.41 中性洗涤纤维 NDF 20 31.07 52.74 45.78 4.99 10.89 酸性洗涤纤维 ADF 20 15.90 29.03 24.58 3.02 12.30 粗脂肪 EE 20 1.82 4.89 3.49 0.66 19.03 粗灰分 Ash 20 3.06 18.49 10.70 3.39 31.72
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表 3 高羊茅干草各营养成分最佳定标模型
Table 3 Optimal calibration models of nutrients in tall fescue hay
营养成分
Nutrition component样本数量
Sample number光谱处理
Spectrum treatment参数
Parameter定标标准分析
误差 SEC交叉验证标准
误差 SECV交叉验证相关
系数 1-VR干物质 DM 81 none 1, 4, 4, 1 0.17 0.22 0.85 粗蛋白 CP 81 Derivative, Scale and Offset 2, 4, 4, 1 0.33 0.67 0.97 有机物 OM 81 none 2, 4, 4, 1 1.22 1.42 0.81 中性洗涤纤维 NDF 81 Derivative, Scale and Offset 1, 4, 4, 1 1.40 1.63 0.86 酸性洗涤纤维 ADF 81 Scale and Quadratic 0, 0, 1, 1 0.99 1.09 0.80 粗脂肪 EE 81 Detrend only 1, 4, 4, 1 0.21 0.28 0.84 粗灰分 Ash 81 SNV and Detrend 2, 4, 4, 1 0.99 1.52 0.80
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表 4 高羊茅干草最佳定标模型验证结果
Table 4 Validation results of the optimal calibration model of tall fescue hay
营养指标
Nutrition index化学测定值
Chemical measured value预测值
Predictive value预测决定
系数 RSQ预测标准
误差 SEP外部验证相对
分析误差 RPD干物质 DM 95.29 95.33 0.85 0.21 2.55 粗蛋白 CP 16.80 16.94 0.94 0.83 3.53 有机物 OM 88.80 89.00 0.78 1.58 2.17 中性洗涤纤维 NDF 45.78 46.06 0.78 2.38 2.04 酸性洗涤纤维 ADF 24.86 25.29 0.84 1.21 2.06 粗脂肪 EE 3.42 3.43 0.79 0.28 2.06 粗灰分 Ash 11.10 11.15 0.77 1.47 2.02 RSQ: coefficient of determination for validation; SEP: standard error of prediction; RPD: ratio of performance to deviation for validation.
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[1] 陈昌荣, 阮晓贵, 黄琦, 刘琼波, 李文霞, 李飞艳. 野生牧草种质资源保护与开发. 畜牧兽医科学(电子版), 2020(17): 146-147. CHEN C R, RUAN X G, HUANG Q, LIU Q B, LI W X, LI F Y. Conservation and development of wild herbage germolasm resources. Graziery Veterinary Sciences (Electronic Version), 2020(17): 146-147.
[2] 马宏义. 野生牧草种质资源在生态环境中的地位和保护措施. 当代畜牧, 2020(10): 44-45. MA H Y. Status and protection measures of wild forage germplasm resources in ecological environment. Contemporary Animal Husbandry, 2020(10): 44-45.
[3] 吴佳海, 牟琼, 唐成斌, 尚以顺, 莫本田, 瓦庆荣. 牧草新品种黔草1号高羊茅的选育. 贵州农业科学, 2006(4): 75-79. doi: 10.3969/j.issn.1001-3601.2006.04.027 WU J H, MOU Q, TANG C B, SHANG Y S, MO B T, WA Q R. Breeding of qiancao 1, a new festuca arundinacea variety. Guizhou Agricultural Sciences, 2006(4): 75-79. doi: 10.3969/j.issn.1001-3601.2006.04.027
[4] 乔玉梅. 禾本科牧草与大豆秸秆饲用产量和营养品质的研究. 沈阳: 沈阳农业大学博士学位论文, 2008. QIAO Y M. Yield and quality of soybean straw and gramineal forage. PhD Thesis. Shenyang: Shenyang Agricultural University, 2008.
[5] 伍文丹, 雷雄, 赵文达, 杨晓鹏, 熊毅, 熊艳丽, 张新全, 马啸. 饲草型高羊茅引进品种的表型变异分析. 草业科学, 2019, 36(10): 2622-2630. doi: 10.11829/j.issn.1001-0629.2018-0680 WU W D, LEI X, ZHAO W D, YANG X P, XIONG Y, XIONG Y L, ZHANG X Q, MA X. Analysis of phenotypic variation of introduced cultivars of tall fescue. Pratacultural Science, 2019, 36(10): 2622-2630. doi: 10.11829/j.issn.1001-0629.2018-0680
[6] 彭艳, 马素洁, 南吉, 索朗德吉, 魏学红. 西藏林芝地区阿尔冈金紫花苜蓿与高羊茅混播效果研究. 黑龙江畜牧兽医, 2019(16): 129-132. PENG Y, MA S J, NAN J, Suolangdeji, WEI X H. Study on the mixed sowing effect of Algonquin alfalfa and tall fescue in Linzhi, Tibet. Heilongjiang Animal Science and Veterinary Medicine, 2019(16): 129-132.
[7] 陈志敏, 张姝, 王征南, 乌远征. 我国东北、西北地区秸秆牧草类饲料资源常规概略养分含量调查报告. 中国奶牛, 2020(4): 59-62. CHEN Z M, ZHANG S, WANG Z N, WU Y Z. Investigation report on nutrient content of straw and forage feed resources in northeast and northwest China. China Dairy Cattle, 2020(4): 59-62.
[8] ANDERSON J V, WITTENBERG A, LI H, BERTI M T. High throughput phenotyping of Camelina sativa seeds for crude protein, total oil, and fatty acids profile by near infrared spectroscopy. Industrial Crops and Products, 2019, 137: 501-507. doi: 10.1016/j.indcrop.2019.04.075
[9] IKOYI A Y, YOUNGE B A. Influence of forage particle size and residual moisture on near infrared reflectance spectroscopy (NIRS) calibration accuracy for macro-mineral determination. Animal Feed Science and Technology, 2020, 270: 114675.
[10] 李磊, 陈丰. 红外光谱分析技术在化工生产中的应用. 化工设计通讯, 2020, 46(4): 150-156. LI L, CHEN F. Application of infrared spectrum analysis technology in chemical production. Chemical Engineering Design Communications, 2020, 46(4): 150-156.
[11] 张梦璐, 张国权. 红外光谱技术在食品检测中的应用. 中国食品, 2021(7): 95. doi: 10.3969/j.issn.1000-1085.2021.07.054 ZHANG M L, ZHANG G Q. Application of infrared spectroscopy in food detection. China Food, 2021(7): 95. doi: 10.3969/j.issn.1000-1085.2021.07.054
[12] 王娅宁, 薛旭东. 近红外光谱在制药过程控制中的应用分析. 中国卫生产业, 2016, 13(33): 50-52. WANG Y N, XUE X D. Application of near infrared spectroscopy in pharmaceutical process control. China Health Industry, 2016, 13(33): 50-52.
[13] 孙克强, 王京力, 廖佳, 赵珍玉. 近红外光谱技术在纺织产品检测中的应用. 轻纺工业与技术, 2019, 48(8): 189-191. doi: 10.3969/j.issn.2095-0101.2019.08.084 SUN K Q, WANG J L, LIAO J, ZHAO Z Y. Application of near infrared spectroscopy in textile products detection. Light and Textile Industry and Technology, 2019, 48(8): 189-191. doi: 10.3969/j.issn.2095-0101.2019.08.084
[14] 欧宇. 浅谈红外光谱技术在环境科学中的应用与展望. 江西化工, 2021, 37(1): 94-96. doi: 10.3969/j.issn.1008-3103.2021.01.027 OU Y. Application and prospect of infrared spectroscopy in environmental science. Jiangxi Chemical Industry, 2021, 37(1): 94-96. doi: 10.3969/j.issn.1008-3103.2021.01.027
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