摘要
运用先进技术实现有机肥高效利用,因地制宜发展区域农业是有机旱作农业发展的重要手段。羊粪施用量的选择与谷子种植用养结合能够有效提高小米品质质量,区别于传统检测手段,高光谱成像对待测样本可以做到检测快速、无损,因而在实现小米粗脂肪、粗蛋白质快速检测中具有巨大潜力。为了为谷子栽培措施的改进及利用高光谱成像对小米营养成分快速检测提供参考和理论支持,试验采集358份小米样本高光谱图像数据并利用传统检测手段进行粗脂肪、粗蛋白质含量测定,同时运用化学计量学方法进行2种成分含量预测。结果表明,连续投影算法结合迭代保留信息变量算法建立的偏最小二乘回归模型在2种成分含量检测上精度最高,其中模型预测粗蛋白质含量相关系数、均方根误差、相对分析误差分别为0.88、0.59、1.99,利用该回归模型进行可视化表达可直观看出不同羊粪施用量下粗脂肪、粗蛋白质的积累规律,并得出每公顷施用90 m^(3)肥料为最佳施用量。
Efficient utilization of organic fertilizer through advanced technology and development of regional agriculture according to local conditions are a crucial method for the development of organic dry farming.Combining sheep manure with millet cultivation can significantly enhance millet quality.Unlike traditional detection methods,hyperspectral imaging offers a rapid,non-destructive means of analyzing samples,therefore,it has great potential in achieving rapid detection of millet crude fat and protein.In order to provide reference and theoretical support for improvement of millet cultivation practices and rapid assessment of nutrient content in millet through hyperspectral imaging,in this study,hyperspectral image data of 358 millet samples were collected,traditional detection methods were used to determine the content of crude fat and crude protein.Simultaneously,chemometrics methods were utilized to predict the content of the two components.The results indicated that the partial least squares regression(PLSR) model established by employing the successive projections algorithm(SPA) and iteratively retaining informative variables(IRIV) had the highest accuracy.The correlation coefficient(R2) predicted by the model for crude protein content was 0.88,with a root mean squared error(RMSE) of 0.59 and a relative percent deviation(RPD) of 1.99.The visualization representations by the regression model vividly illustrated the accumulation patterns of crude fat and protein at various application rates of sheep manure,and it was determined that applying 90 m^(3) of fertilizer per hectare was the optimal application amount.
作者
王国梁
张艾英
王丽霞
赵培悦
刘鑫
成锴
郭二虎
WANG Guoliang;ZHANG Aiying;WANG Lixia;ZHAO Peiyue;LIU Xin;CHENG Kai;GUO Erhu(Institute of Millet,Shanxi Agricultural University/State Key Laboratory of Sustainable Dryland Agriculture(in preparation),Changzhi 046011,China)
出处
《山西农业科学》
2024年第3期1-8,共8页
Journal of Shanxi Agricultural Sciences
基金
山西农业大学省部共建有机旱作农业国家重点实验室自主研发项目(202105D121008-2-5)
山西省现代农业产业技术体系谷子体系(2023CYJSTX04-04)
杂粮种质资源创新与分子育种国家实验室项目(202204010910001-13)
国家现代农业产业技术体系建设专项(CARS-06-14.5-A21)。
