植物营养与肥料学报
植物營養與肥料學報
식물영양여비료학보
PLANT NUTRITION AND FERTILIZER SCIENCE
2009年
4期
750-755
,共6页
林芬芳%陈祝炉%邓劲松%王珂
林芬芳%陳祝爐%鄧勁鬆%王珂
림분방%진축로%산경송%왕가
水稻%氮%傅立叶变换中红外光谱(vrm)%siPLS
水稻%氮%傅立葉變換中紅外光譜(vrm)%siPLS
수도%담%부립협변환중홍외광보(vrm)%siPLS
rice%nitrogen%FTIR%siPLS
通过不同氮素水平的水稻田间试验,在分析测定了水稻叶片叶绿素、氮素等农学参数后,采用傅立叶中红外光谱仪测定了水稻孕穗期叶片干样的透射光谱,利用协同偏最小二乘算法(siPLS)分析选取了傅立叶变换红外光谱估测水稻氮素含量的敏感波段及其组合.结果表明,其最优主成分数是9个,最佳估测建模的波段组合分别为1350.89~1586.57,1587.53~1822.40和3709.41~3943.72 cm-1;建立的水稻氮素预测模型的精度较高,交互验证均方根误差(RMSECV)和预测均方根误差(RMSEP)分别为0.1538和0.1933,预测值与化学分析获得的叶片总氮浓度之间的交互相关系数和独立检验相关系数分别为0.9393和0.6649,高于中红外光谱指数NFS和NFSA的预测精度.说明利用傅立叶红外光谱作为水稻氮含量的诊断技术是可能的,值得进一步验证和完善.
通過不同氮素水平的水稻田間試驗,在分析測定瞭水稻葉片葉綠素、氮素等農學參數後,採用傅立葉中紅外光譜儀測定瞭水稻孕穗期葉片榦樣的透射光譜,利用協同偏最小二乘算法(siPLS)分析選取瞭傅立葉變換紅外光譜估測水稻氮素含量的敏感波段及其組閤.結果錶明,其最優主成分數是9箇,最佳估測建模的波段組閤分彆為1350.89~1586.57,1587.53~1822.40和3709.41~3943.72 cm-1;建立的水稻氮素預測模型的精度較高,交互驗證均方根誤差(RMSECV)和預測均方根誤差(RMSEP)分彆為0.1538和0.1933,預測值與化學分析穫得的葉片總氮濃度之間的交互相關繫數和獨立檢驗相關繫數分彆為0.9393和0.6649,高于中紅外光譜指數NFS和NFSA的預測精度.說明利用傅立葉紅外光譜作為水稻氮含量的診斷技術是可能的,值得進一步驗證和完善.
통과불동담소수평적수도전간시험,재분석측정료수도협편협록소、담소등농학삼수후,채용부립협중홍외광보의측정료수도잉수기협편간양적투사광보,이용협동편최소이승산법(siPLS)분석선취료부립협변환홍외광보고측수도담소함량적민감파단급기조합.결과표명,기최우주성분수시9개,최가고측건모적파단조합분별위1350.89~1586.57,1587.53~1822.40화3709.41~3943.72 cm-1;건립적수도담소예측모형적정도교고,교호험증균방근오차(RMSECV)화예측균방근오차(RMSEP)분별위0.1538화0.1933,예측치여화학분석획득적협편총담농도지간적교호상관계수화독립검험상관계수분별위0.9393화0.6649,고우중홍외광보지수NFS화NFSA적예측정도.설명이용부립협홍외광보작위수도담함량적진단기술시가능적,치득진일보험증화완선.
The time and quantity of N fertilization is considered as a key technique for high yield and quality in crop pro-duction. Based on the rice field experiment with different N rates, the mid-IR transmittance spectra of the dried and ground leaf samples were determined by Fourier transform infrared (FTIR) spectroscopy, and then the estimation model for leaf nitrogen content was built with the obtained mid-IR transmittance spectra and synergy interval partial least square algorithm (siPLS). The optimal siPLS model was obtained with 100 intervals and 9 PLS components. The best combina-tions of spectral regions selected were 1350.89-1586.57, 1587.53-1822.40 and 3709.41-3943.72 cm-1. The value of RMSECV (root mean square error of cross-validation) is 0. 1538, and correlation coefficient (r) was 0.9393 in calibration set, and the RMSEP (root mean square error of prediction) was 0. 1933 and correlation coefficient (r) was 0.6649 for test data set. Furthermore, compared with spectral indices NFS and NFSA, this modal was more reliable and representative. It was suggested that FTIR spectroscopy may be considered as a diagnosis technology for leaf nitrogen content in rice.