JP5885168B2 - Method and apparatus for analyzing soil geological traits - Google Patents
Method and apparatus for analyzing soil geological traits Download PDFInfo
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本発明は、土壌に含まれる可給態窒素、可給態リン酸、全炭素、全窒素等の土壌地力形質の分析方法及び土壌地力形質の分析装置に関する。 The present invention relates to a method for analyzing soil geological traits such as available nitrogen, available phosphoric acid, total carbon, and total nitrogen contained in soil, and an apparatus for analyzing soil geological traits.
植物の生育に寄与する土壌成分として最も重要な成分は窒素分である。植物に最初に吸収される窒素分は土壌に含まれている無機態の窒素成分であるが、この無機態の窒素成分は植物の生長に寄与する窒素成分のうちの一部に過ぎず、植物の生長に最も重要な窒素成分は有機態の窒素成分（可給態窒素）であることが知られている（非特許文献１）。有機態の窒素成分（可給態窒素）は、いわゆる地力と称されるものであり、微生物等の分解作用により徐々に有機態から無機化し植物の生長に寄与する。 The most important component as a soil component contributing to plant growth is nitrogen. The nitrogen content that is first absorbed by the plant is the inorganic nitrogen component contained in the soil, but this inorganic nitrogen component is only a part of the nitrogen component that contributes to the growth of the plant. It is known that the most important nitrogen component for the growth of organic compounds is an organic nitrogen component (available nitrogen) (Non-patent Document 1). The organic nitrogen component (available nitrogen) is called so-called geopower, and gradually becomes inorganic from the organic state by the decomposition action of microorganisms and the like and contributes to the growth of plants.
可給態窒素の量を分析する方法として、最も基本的な方法は培養法である。培養法では、測定しようとする土壌を風乾させた試料（風乾土壌）を検査用の容器に入れ、水分量を60%に調節しながら、30℃、４週間、保温静置して培養し、全窒素量から培養土壌の窒素量を差し引くことにより可給態窒素量を求める。この分析方法は、実際に一定期間の培養期間を設けて検出する方法であり、測定法としては最も信頼性は高いが、測定に時間がかかり、滴定等の煩雑な操作を行わなければならないことから、実験室レベルでは可能であっても、実際の土壌分析の用途には適さない。
このため、可給態窒素の量を簡便に分析する方法として、リン酸緩衝液を用いて土壌の有機酸を抽出した抽出液を可視吸光分光あるいは紫外吸光分光する方法、近赤外反射光分光を利用する方法等が提案されてきた（特許文献１、２、３）。
The most basic method for analyzing the amount of available nitrogen is the culture method. In the culture method, a sample (air-dried soil) obtained by air-drying the soil to be measured is placed in a container for inspection, and the moisture content is adjusted to 60%, and the sample is incubated at 30 ° C. for 4 weeks. The amount of available nitrogen is determined by subtracting the nitrogen content of the cultured soil from the total nitrogen content. This analysis method is a method of detection by setting a culture period of a certain period, and it is the most reliable as a measurement method, but it takes a long time to measure and requires complicated operations such as titration. Therefore, even if possible at the laboratory level, it is not suitable for practical soil analysis applications.
For this reason, methods for simple analysis of the amount of available nitrogen include visible absorption spectroscopy or ultraviolet absorption spectroscopy of extracts obtained by extracting organic acids from soil using a phosphate buffer solution, near infrared reflectance spectroscopy. There have been proposed methods for using the above (Patent Documents 1, 2, and 3).
土壌中に含まれる可給態窒素量を簡便に検出する方法は、長年の懸案事項であり、従来も、簡便に検出する方法がいくつか提案されている。しかしながら、いずれの分析方法も、分析操作を行う上での簡便さ、あるいは測定精度の点で、必ずしも満足できるものとなっていない。
なお、土壌には窒素分の他にさまざまな有機成分、無機成分が含まれており、これらの成分もまた土壌の地力を反映している。たとえば、窒素肥沃度と関係の深い全窒素、腐植度や窒素の有機化に寄与する全炭素、可給態リン酸の含量、全炭素と全窒素の比（CN比）等が地力に関わる。本明細書においては、これらの土壌地力に関わる形質を土壌地力形質ということにする。
A simple method for detecting the amount of available nitrogen contained in soil has been a long-standing concern, and several methods have been proposed for simple detection. However, none of the analysis methods is always satisfactory in terms of simplicity in performing an analysis operation or measurement accuracy.
In addition to nitrogen, the soil contains various organic and inorganic components, and these components also reflect the soil's geopower. For example, total nitrogen closely related to nitrogen fertility, total carbon that contributes to humus and nitrogen organics, the content of available phosphoric acid, the ratio of total carbon to total nitrogen (CN ratio), etc. are related to geopower. In this specification, these traits related to soil geology are referred to as soil geology traits.
本発明は、非破壊分析方法により被検体である土壌に含まれる可給態窒素、可給態リン酸、全窒素、全炭素といった土壌地力形質を簡便な操作によって分析、推定することを可能にし、土壌分析に基づく施肥設計などを容易に行うことを可能にする土壌地力形質の分析方法及び分析装置を提供することを目的とする。 The present invention makes it possible to analyze and estimate soil geological traits such as available nitrogen, available phosphoric acid, total nitrogen, and total carbon contained in soil as a specimen by a simple operation by a nondestructive analysis method. An object of the present invention is to provide a soil geological trait analysis method and an analysis apparatus that enable easy fertilization design based on soil analysis.
本発明に係る土壌地力形質の分析方法は、風乾土壌を被検体とし、被検体に励起光を照射し、被検体からの蛍光スペクトルを解析することにより被検体の土壌地力形質として可給態窒素、可給態リン酸、全窒素、全炭素、CN比、CECを分析する方法であって、前記蛍光スペクトルの解析結果に基づいて前記土壌地力形質を個別に推定するための検量線を作成する工程として、異なる土壌地力形質を備える複数種の評価用の土壌を定量分析して各々の土壌の前記土壌地力形質の定量値を特定する工程と、前記評価用の土壌に前記励起光を照射して各々の土壌の蛍光スペクトルを取得し、蛍光スペクトルを解析することにより蛍光解析値を算出する工程と、前記土壌地力形質の定量値と前記蛍光解析値との相関関係から、前記各々の土壌地力形質と蛍光解析値との検量線を作成する工程とを備え、前記被検体の土壌地力形質を分析する方法として、前記被検体の蛍光スペクトルを解析して前記土壌地力形質の各々に対応する蛍光解析値を算出する工程と、該蛍光解析値と前記検量線に基づき、当該被検体の土壌地力形質として、可給態窒素、可給態リン酸、全窒素、全炭素、CN比、CECのいずれかを分析することを特徴とする。 The soil geological trait analysis method according to the present invention uses air-dried soil as a subject, irradiates the subject with excitation light, and analyzes the fluorescence spectrum from the subject to provide available nitrogen as the soil geological trait of the subject. , A method for analyzing available phosphoric acid, total nitrogen, total carbon, CN ratio, CEC, and creating a calibration curve for individually estimating the soil geological traits based on the analysis result of the fluorescence spectrum As a process, quantitatively analyzing a plurality of types of soils for evaluation having different soil geological traits to identify quantitative values of the soil geological traits of each soil, and irradiating the soil for evaluation with the excitation light get the fluorescence spectrum of each of the soil Te, calculating a fluorescence analysis value by analyzing the fluorescence spectrum, the correlation between the quantitative value of the soil 壌地 force transformation and the fluorescence analysis value, of the respective and soil 壌地 force transformation And a step of creating a calibration curve of the optical analysis value, said as a method for analyzing soil fertility traits of the subject, before Symbol fluorescence analysis by analyzing the fluorescence spectrum of the subject corresponding to each of the soil fertility trait A step of calculating a value, and based on the fluorescence analysis value and the calibration curve, as soil geological traits of the subject , any of available nitrogen, available phosphoric acid, total nitrogen, total carbon, CN ratio, CEC characterized by analyzing whether.
また、前記蛍光解析値を算出する工程において、蛍光スペクトルの一次微分値を説明変数とし、土壌地力形質を従属変数とするPLS回帰分析法を利用して算出した推定値を蛍光解析値とすることを特徴とする。 Further, in the step of calculating the fluorescence analysis value, an estimated value calculated using a PLS regression analysis method using a first derivative value of the fluorescence spectrum as an explanatory variable and a soil geological trait as a dependent variable is set as the fluorescence analysis value. It is characterized by.
また、前記蛍光解析値を算出する工程において、蛍光スペクトルの波長間の関係を正規化分光指数（NDSI値)として算出し、土壌地力形質の推定に有効に寄与する波長の組み合わせに係るNDSI値を蛍光解析値とすることを特徴とする。Further, in the step of calculating the fluorescence analysis value, the relationship between the wavelengths of the fluorescence spectrum is calculated as a normalized spectral index (NDSI value), and the NDSI value relating to the combination of wavelengths that effectively contributes to estimation of soil geological traits is calculated. The fluorescence analysis value is used.
また、前記蛍光解析値を算出する工程において、蛍光スペクトルを一定波長範囲ごとに区切った波長域ごとの蛍光強度の積分値を、蛍光スペクトル全体の積分値により除した蛍光指数を求め、前記波長域ごとの蛍光指数のうち他の蛍光指数と比較して前記定量値と相関関係の高い波長域の蛍光指数を蛍光解析値とすることを特徴とする。Further, in the step of calculating the fluorescence analysis value, a fluorescence index obtained by dividing the integral value of the fluorescence intensity for each wavelength region obtained by dividing the fluorescence spectrum for each predetermined wavelength range by the integral value of the entire fluorescence spectrum is obtained, The fluorescence index in a wavelength region having a high correlation with the quantitative value is used as the fluorescence analysis value among the fluorescence indices for each of the fluorescence indices.
また、本発明に係る土壌地力形質の分析装置として、風乾土壌を被検体とし、被検体に励起光を照射し、被検体からの蛍光スペクトルを解析することにより被検体の土壌地力形質として可給態窒素、可給態リン酸、全窒素、全炭素、CN比、CECを分析する分析装置であって、被検体である風乾土壌をセットするセット部と、前記被検体に励起光を照射する光照射部と、前記被検体からの蛍光を計測する蛍光測定部と、前記蛍光測定部の測定結果に基づき蛍光データを解析する解析部と、を備え、前記解析部は、前記蛍光スペクトルの解析結果に基づいて前記土壌地力形質を個別に推定するための検量線を作成する手段として、異なる土壌地力形質を備える複数種の評価用の土壌に前記励起光を照射して各々の土壌の蛍光スペクトルを取得し、蛍光スペクトルを解析することにより蛍光解析値を算出する手段と、前記評価用の土壌について特定された定量値と前記蛍光解析値との相関関係から、前記各々の土壌地力形質と蛍光解析値との検量線を作成する手段とを備え、前記被検体の土壌地力形質を分析する手段として、前記被検体の蛍光スペクトルを解析して前記土壌地力形質の各々に対応する蛍光解析値を算出する手段と、該蛍光解析値と前記検量線に基づき、当該被検体の土壌地力形質として、可給態窒素、可給態リン酸、全窒素、全炭素、CN比、CECのいずれかを分析する手段とを備えることを特徴とする。 Further, as the analyzer soil fertility traits according to the present invention, the air-dried soil was the subject is irradiated with excitation light to a subject, soluble as the subject of soil fertility traits by analyzing the fluorescence spectrum from the subject An analyzer that analyzes supplied nitrogen, available phosphoric acid, total nitrogen, total carbon, CN ratio, and CEC, and sets the air-dried soil that is the subject, and irradiates the subject with excitation light a light irradiation section for the comprising a fluorescence measuring unit for measuring the fluorescence from the subject, and an analysis unit for analyzing the fluorescence data based on the measurement result of the fluorescence measurement unit, the analysis unit of the fluorescence spectra As means for creating a calibration curve for individually estimating the soil geological traits based on the analysis results, the excitation light is irradiated to a plurality of types of soils for evaluation having different soil geological traits to fluoresce each soil Acquire the spectrum and firefly From the correlation between the means for calculating the fluorescence analysis value by analyzing the spectrum and the quantitative value specified for the soil for evaluation and the fluorescence analysis value, calibration of each soil geological trait and fluorescence analysis value is performed. Means for creating a line, and as means for analyzing the soil geological traits of the subject, means for analyzing the fluorescence spectrum of the subject and calculating a fluorescence analysis value corresponding to each of the soil geological traits, Based on the fluorescence analysis value and the calibration curve, as a soil geological trait of the subject, means for analyzing any of available nitrogen, available phosphoric acid, total nitrogen, total carbon, CN ratio, CEC , It is characterized by providing.
また、前記蛍光解析値を算出する手段において、蛍光スペクトルの一次微分値を説明変数とし、土壌地力形質を従属変数とするPLS回帰分析法を利用して算出した推定値を蛍光解析値とし、また、蛍光スペクトルの波長間の関係を正規化分光指数（NDSI値)として算出し、土壌地力形質の推定に有効に寄与する波長の組み合わせに係るNDSI値を蛍光解析値とし、また、蛍光スペクトルを一定波長範囲ごとに区切った波長域ごとの蛍光強度の積分値を、蛍光スペクトル全体の積分値により除した蛍光指数を求め、前記波長域ごとの蛍光指数のうち他の蛍光指数と比較して前記定量値と相関関係の高い波長域の蛍光指数を蛍光解析値とすることを特徴とする。
また、前記光照射部として、紫レーザ光源を備えることにより、的確に土壌地力形質を分析することができる。
Further, in the means for calculating the fluorescence analysis value, the first derivative value of the fluorescence spectrum is an explanatory variable, the estimated value calculated using the PLS regression analysis method having the soil geological trait as a dependent variable is the fluorescence analysis value, Calculate the relationship between the wavelengths of the fluorescence spectrum as a normalized spectral index (NDSI value), use the NDSI value for the combination of wavelengths that contributes to the estimation of soil geological characteristics as the fluorescence analysis value, and keep the fluorescence spectrum constant. The fluorescence index obtained by dividing the integral value of the fluorescence intensity for each wavelength range divided for each wavelength range by the integral value of the entire fluorescence spectrum is obtained, and the quantification is performed by comparing with the other fluorescence index among the fluorescence indexes for each wavelength range. A fluorescence index in a wavelength region having a high correlation with the value is used as a fluorescence analysis value.
Moreover, as the pre-Symbol light irradiation unit, by providing the violet laser light source, it is possible to accurately analyze the soil fertility trait.
本発明に係る土壌地力形質の分析方法及び分析装置によれば、被検体の蛍光スペクトルを計測するのみで、可給態窒素、可給態リン酸、全窒素、全炭素といった地力形質を容易に分析することができる。 According to the method and apparatus for analyzing soil geological traits according to the present invention, it is possible to easily perform geological traits such as available nitrogen, available phosphoric acid, total nitrogen, and total carbon only by measuring the fluorescence spectrum of the subject. Can be analyzed.
（分析装置）
図１は、土壌の地力形質の分析に利用した分析装置の構成を示す。この分析装置は、分析対象である土壌試料にレーザ光を照射し、試料からの蛍光を観察することにより、可給態窒素量、可給態リン酸、全炭素、全窒素等の土壌の地力に関わる形質を検出するものである。分析装置は、暗箱１２内に、土壌の試料をセットするセット部１０と、試料にレーザ光を照射するレーザヘッド１３と、試料から放射される蛍光を受ける受光ヘッド１６とを配置した構成を備える。
(Analysis equipment)
FIG. 1 shows the configuration of an analysis apparatus used for analysis of soil geological traits. This analyzer irradiates the soil sample to be analyzed with laser light and observes the fluorescence from the sample, so that the soil's ground strength such as available nitrogen amount, available phosphoric acid, total carbon, total nitrogen, etc. It detects the traits related to The analyzer includes a configuration in which a setting unit 10 for setting a soil sample, a laser head 13 for irradiating the sample with laser light, and a light receiving head 16 for receiving fluorescence emitted from the sample are disposed in the dark box 12. .
レーザヘッド１３はケーブル１４を介してレーザ電源１５に接続される。本実施形態においては、レーザヘッド１３として、中心波長405nm（紫色）の連続発振半導体レーザ（SU-62:株式会社オーディオテクニカ製）を使用し、レーザ電源１５としてSUP-60M（株式会社オーディオテクニカ製）を使用した。レーザヘッド１３及びレーザ電源１５が試料に励起光を照射する光照射部を構成する。レーザ光の出力は光パワーメータを用いて測定した。レーザの出力は試料の照射部分で28mW/cm2であった。 The laser head 13 is connected to a laser power source 15 via a cable 14. In this embodiment, a continuous wave semiconductor laser (SU-62: manufactured by Audio Technica Co., Ltd.) having a central wavelength of 405 nm (purple) is used as the laser head 13, and SUP-60M (produced by Audio Technica Co., Ltd.) is used as the laser power source 15. )It was used. The laser head 13 and the laser power source 15 constitute a light irradiation unit that irradiates the sample with excitation light. The output of the laser beam was measured using an optical power meter. The laser output was 28 mW / cm 2 at the irradiated part of the sample.
受光ヘッド１６は光ファイバの端面に蛍光を受光するためのもので、蛍光は石英光ファイバ１７を介して分光器１８に導かれる。受光ヘッド１６の前部に、励起光をカットするフィルタ１６aを配置する。フィルタ１６aには470nm以下の光を遮断する短波長カットフィルタを使用した。分光器１８にはマルチチャンネル分光器（浜松ホトニクス製）を使用し、分光器１８の出力を解析部（PC)２０に入力する。受光ヘッド１６、フィルタ１６a、石英光ファイバ１７、分光器１８が蛍光測定部に相当する。
本実施形態の分析装置では、光強度の強い紫レーザ光を励起光としたことにより、蛍光スペクトル分析が容易になり、暗箱１２から分光器１８に蛍光を導くといった引き回し操作に光ファイバが利用できるという利点がある。
The light receiving head 16 is for receiving fluorescence at the end face of the optical fiber, and the fluorescence is guided to the spectroscope 18 through the quartz optical fiber 17. A filter 16 a that cuts excitation light is disposed in front of the light receiving head 16. The filter 16a is a short wavelength cut filter that blocks light of 470 nm or less. A multi-channel spectrometer (manufactured by Hamamatsu Photonics) is used as the spectrometer 18, and the output of the spectrometer 18 is input to an analysis unit (PC) 20. The light receiving head 16, the filter 16a, the quartz optical fiber 17, and the spectroscope 18 correspond to a fluorescence measuring unit.
In the analyzer according to the present embodiment, the violet laser light having a high light intensity is used as the excitation light, so that the fluorescence spectrum analysis is facilitated, and the optical fiber can be used for the routing operation for guiding the fluorescence from the dark box 12 to the spectrometer 18. There is an advantage.
試料はシャーレ内に平らに収納し、レーザヘッド１３から試料の表面に対し４５度の角度でレーザ光を照射し、受光ヘッド１６の光軸を入射光に対して正反射位置とした。レーザヘッド１３の端面と試料の上面の照射位置との離間間隔は1.5ｃｍ、受光ヘッド１６の端面と試料上面のレーザ光の照射位置との離間間隔は４５ｍｍである。
レーザ光の照射光と蛍光の光軸を定める方法として、レーザヘッド１３から放射されるレーザ光を光ファイバに導いて光ファイバの光軸を照射角度に設定し、受光ヘッド１６のかわりに、試料からの蛍光を、光軸を正反射角度に設定した光ファイバに入射させることも可能である。
The sample was stored flat in a petri dish, laser light was irradiated from the laser head 13 to the surface of the sample at an angle of 45 degrees, and the optical axis of the light receiving head 16 was set to a regular reflection position with respect to incident light. The distance between the end face of the laser head 13 and the irradiation position of the upper surface of the sample is 1.5 cm, and the distance between the end face of the light receiving head 16 and the irradiation position of the laser light on the upper surface of the sample is 45 mm.
As a method for determining the optical axis of the laser light irradiation light and fluorescence, the laser light emitted from the laser head 13 is guided to the optical fiber, the optical axis of the optical fiber is set to the irradiation angle, and the sample is used instead of the light receiving head 16. It is also possible to make the fluorescence from the light incident on an optical fiber whose optical axis is set to a regular reflection angle.
（蛍光強度を用いる分析方法：蛍光NDSI法）
長野県内の畑から採取した土壌（黒ボク土）２４点を土壌試料とし、蛍光NDSIを利用して土壌地力形質を推定する方法について検討した。土壌試料にレーザ光を照射して得られる蛍光には土壌中の有機物に由来するものの他に、鉱物等を由来とするものが含まれている可能性がある。本調査においては、土壌試料の蛍光と可給態窒素、全窒素、全炭素、可給態リン酸、CN比等の土壌地力形質との相関関係を調べ、その解析結果に基づいて、土壌の蛍光スペクトルから土壌地力形質（可給態窒素、全窒素、全炭素、可給態リン酸、CN比等）を推定することが可能であるか否か研究した。
(Analysis method using fluorescence intensity: fluorescence NDSI method)
Using 24 samples of soil (Kuroboku soil) collected from fields in Nagano Prefecture as a soil sample, we investigated a method for estimating soil geological traits using fluorescent NDSI. The fluorescence obtained by irradiating a soil sample with laser light may contain minerals or the like in addition to those derived from organic matter in the soil. In this study, we investigated the correlation between soil sample fluorescence and soil geological traits such as available nitrogen, total nitrogen, total carbon, available phosphoric acid and CN ratio, and based on the analysis results, We investigated whether it was possible to estimate soil geological traits (available nitrogen, total nitrogen, total carbon, available phosphoric acid, CN ratio, etc.) from the fluorescence spectrum.
土壌地力形質の定量：
採取した土壌（２４点）を風乾した後、乳鉢を用いて粉砕したもの（風乾粉砕土）を土壌試料とした。各々の土壌試料の地力形質を定量する方法としては、一般的な土壌分析方法を利用した。土壌の可給態窒素量については、培養の後に無機態窒素(NH4-N)をケルダール法などの滴定法で定量し、全窒素量と全炭素量は乾式燃焼法、可給態リン酸はトルオーグ法を用いて定量した。CN比は全炭素と全窒素の定量値から算出した。
表１に、上記分析方法により測定した各々の土壌試料について、可給態窒素、可給態リン酸、全炭素、全窒素、CN比を定量した結果を示す。
Quantification of soil geological traits:
The collected soil (24 points) was air-dried and then pulverized with a mortar (air-dried pulverized soil) as a soil sample. As a method for quantifying the geological traits of each soil sample, a general soil analysis method was used. Regarding the amount of available nitrogen in the soil, after culturing, inorganic nitrogen (NH4-N) was quantified by a titration method such as Kjeldahl, and the total nitrogen and total carbon were determined by the dry combustion method. Quantification was performed using the Toruog method. The CN ratio was calculated from the quantitative values of total carbon and total nitrogen.
Table 1 shows the results of quantifying available nitrogen, available phosphoric acid, total carbon, total nitrogen, and CN ratio for each soil sample measured by the above analytical method.
蛍光スペクトルの解析：
図１に示した分析装置を用いて、２４点の土壌試料について蛍光計測を行った。計測は、１回の照射時間を500msecとし、１つのサンプルについて２０回繰り返し計測を行い、２０個のスペクトルの平均を各々のサンプルから得られたスペクトルとした。実際には、分光器１８の検出データを２nm間隔に変換し、２nm間隔のスペクトルの隣り合う５波長の移動平均をとってスムージングし、これを１サンプルから得られる蛍光スペクトルとした。
図２に、紫レーザ光（405nm）励起による蛍光スペクトルの例を示す。470nmから800nmに後半にかけて広い範囲の蛍光が見られ、520nmと570nm付近にピークが見られる。
Analysis of fluorescence spectrum:
Fluorescence measurement was performed on 24 soil samples using the analyzer shown in FIG. In the measurement, one irradiation time was set to 500 msec, measurement was repeated 20 times for one sample, and an average of 20 spectra was obtained as a spectrum obtained from each sample. Actually, the detection data of the spectroscope 18 was converted into 2 nm intervals, and a moving average of 5 wavelengths adjacent to each other at 2 nm intervals was smoothed to obtain a fluorescence spectrum obtained from one sample.
FIG. 2 shows an example of a fluorescence spectrum by violet laser beam (405 nm) excitation. A wide range of fluorescence is observed from 470 nm to 800 nm in the latter half, and peaks are observed around 520 nm and 570 nm.
蛍光NDSIを用いる分析方法は、蛍光スペクトルの正規化分光指数（NDSI:Normalized
Difference Spectral Index)を利用して、正規化分光指数と土壌地力形質の実測値（定量値）との相関関係を解析する手法である。
正規化分光指数（NDSI)は、図３に示すように、任意の２波長（ｉ、ｊ）間の蛍光強度差の関係を数値化したものであり、波長ｉのスペクトル強度をLi、波長ｊのスペクトル強度をLｊとして、次式によって定義される。
NDSI＝（Li−Lｊ）／（Li＋Lｊ） ただし、−１≦NDSI≦１
The analysis method using fluorescence NDSI is the normalized spectral index (NDSI) of the fluorescence spectrum.
This is a technique for analyzing the correlation between the normalized spectral index and the measured values (quantitative values) of soil geological traits using the Difference Spectral Index.
Normalized spectral index (NDSI), as shown in FIG. 3, is obtained by digitizing a relationship fluorescence intensity difference between any two wavelengths (i, j), the spectral intensity of the wavelength i L i, wavelength The spectral intensity of j is defined as L j by the following equation.
NDSI = (L i −L j ) / (L i + L j ) where −1 ≦ NDSI ≦ 1
各土壌試料の定量結果と蛍光スペクトルのNDSIと測定項目との相関行列（符号をはずすために二乗してR2行列とした）を求めることにより、土壌中の可給態窒素、全窒素、全炭素、可給態リン酸の含量とCN比の推定に寄与している波長の組み合わせを求めることができる。本実施形態では、図４に示すように、R2行列を2nm刻みのマトリクスの図とし、R2行列を可視化するため、推定力（R2)の高低を明暗によって表示するR2分布図を作成して評価した。 By determining the correlation matrix of the NDSI and measurement items of quantitative results and the fluorescence spectrum of each soil sample (squaring to remove the sign was R 2 matrix), Yes supplying nitrogen in the soil, total nitrogen, total The combination of wavelengths contributing to the estimation of the content of carbon and available phosphoric acid and the CN ratio can be obtained. In the present embodiment, as shown in FIG. 4, the R 2 matrix is displayed as a matrix diagram in increments of 2 nm, and in order to visualize the R 2 matrix, the R 2 distribution diagram that displays the level of the estimated force (R 2 ) in terms of light and dark Created and evaluated.
図５は可給態窒素について、実測値と蛍光スペクトルとの相関関係を示すR2分布図である。同図で、明るく表れている部分は暗く表れているい部分よりも推定力が高い波長の組み合わせである個所（ホットスポット）であり、NDSI値と実測値との相関における決定係数R2が高い個所を示す。この可給態窒素と実測値との相関関係については、660〜680nm付近の近接した２波長の組み合わせのNDSI値と可給態窒素との間に負の相関がみられ、決定係数は約0.4であった。本解析方法ではホットスポットでのNDSI値が蛍光解析値に相当する。 FIG. 5 is an R 2 distribution diagram showing the correlation between the actually measured value and the fluorescence spectrum for available nitrogen. In the figure, the part that appears bright is the part (hot spot) that is a combination of wavelengths that has a higher estimation power than the part that appears dark, and the part that has a high coefficient of determination R 2 in the correlation between the NDSI value and the measured value. Indicates. As for the correlation between the available nitrogen and the measured value, a negative correlation is observed between the NDSI value of the combination of two adjacent wavelengths near 660 to 680 nm and the available nitrogen, and the coefficient of determination is about 0.4. Met. In this analysis method, the NDSI value at the hot spot corresponds to the fluorescence analysis value.
図６は可給態リン酸についての実測値と蛍光スペクトルとの相関関係を示すR2分布図である。この例では、500〜550nm付近の近接した２波長の組み合わせのNDSI値と可給態リン酸との間に正の相関がみられ、決定係数は0.4以上であった。 FIG. 6 is an R 2 distribution diagram showing the correlation between the actual measurement value of the available phosphoric acid and the fluorescence spectrum. In this example, a positive correlation was found between the NDSI value of the combination of two adjacent wavelengths near 500 to 550 nm and the available phosphoric acid, and the determination coefficient was 0.4 or more.
図７は全炭素についての実測値と蛍光スペクトルとの相関関係を示すR2分布図である。図８は全窒素についての実測値と蛍光スペクトルとの相関関係を示すR2分布図である。図７と図８は、同様の明暗の傾向を示し、750〜800nm付近の近接した２波長の組み合わせのNDSI値と全炭素、全窒素との間に正の相関がみられ、決定係数は0.4以上を示した。また、600nm付近と800nm付近の離れた２波長の組み合わせについて、NDSI値と全炭素、全窒素との間に負の相関がみられ、決定係数は0.3以上を示した。 FIG. 7 is an R 2 distribution diagram showing the correlation between the actual measurement value and the fluorescence spectrum for all carbon. FIG. 8 is an R 2 distribution diagram showing the correlation between the actually measured value and the fluorescence spectrum for all nitrogen. 7 and 8 show the same light and dark tendency, and there is a positive correlation between the NDSI value of the combination of two adjacent wavelengths near 750 to 800 nm and the total carbon and total nitrogen, and the determination coefficient is 0.4. The above is shown. In addition, a negative correlation was found between the NDSI value and the total carbon and total nitrogen for the combination of two wavelengths separated by about 600 nm and about 800 nm, and the coefficient of determination was 0.3 or more.
図９はCN比と蛍光スペクトルとの相関関係を示すR2分布図である。この例では、750nm付近の近接した２波長の組み合わせのNDSI値とCN比との間に負の相関がみられ、、600nm付近と800nm付近の離れた２波長の組み合わせにおいても弱い負の相関がみられた。 FIG. 9 is an R 2 distribution diagram showing the correlation between the CN ratio and the fluorescence spectrum. In this example, there is a negative correlation between the NDSI value of the combination of two adjacent wavelengths near 750 nm and the CN ratio, and a weak negative correlation is also found in the combination of two wavelengths near 600 nm and 800 nm. It was seen.
図７〜１０に示したR2分布図を見ると、可給態窒素、可給態リン酸、全炭素、全窒素、CN比について、推定力が高い領域（ホットスポット）がそれぞれ異なる分布になっている。この解析結果は、土壌試料に紫レーザ光を照射して得られる蛍光が、可給態窒素、可給態リン酸、全炭素、全窒素、CN比といった土壌地力形質についての情報を含むものであり、これらの情報から可給態窒素、可給態リン酸、全炭素、全窒素、CN比といった土壌地力形質を推定することが可能であることを示唆する。 When the R 2 distribution diagrams shown in FIGS. 7 to 10 are viewed, the regions (hot spots) where the estimated power is high for the available nitrogen, the available phosphoric acid, the total carbon, the total nitrogen, and the CN ratio have different distributions. It has become. This analysis result shows that the fluorescence obtained by irradiating a soil sample with purple laser light includes information on soil geological traits such as available nitrogen, available phosphoric acid, total carbon, total nitrogen, and CN ratio. It is suggested that it is possible to estimate soil geological traits such as available nitrogen, available phosphoric acid, total carbon, total nitrogen, CN ratio from these information.
図１０は、土壌試料の可給態窒素量と蛍光との相関関係を、24個の土壌試料について波長（624nm、632nm）のNDSI値を横軸、可給態窒素の定量値（実測値）を縦軸としてグラフに示したものである。図中に回帰分析によって得られた検量線を示す。
この解析結果は、蛍光スペクトル解析によって得られた蛍光データの指標となるNDSI値と土壌に含まれる可給態窒素量とが良い相関関係にあることを示している。すなわち、この相関関係を利用すれば、検査対象である土壌の蛍光スペクトルのNDSI値を求めることにより、土壌の可給態窒素量を推定することができる。
なお、可給態窒素以外の可給態リン酸、全炭素、全窒素、CN比についても同様に、蛍光スペクトル解析に基づいて検量線を作成し、検査対象である土壌を蛍光測定することによりその土壌の地力形質を推定することができる。
Fig. 10 shows the correlation between the amount of available nitrogen in the soil sample and the fluorescence, the NDSI value of the wavelength (624 nm, 632 nm) for the 24 soil samples on the horizontal axis, and the quantitative value of the available nitrogen (actually measured value). Is plotted on the graph with the vertical axis. The calibration curve obtained by regression analysis is shown in the figure.
This analysis result shows that there is a good correlation between the NDSI value, which is an indicator of fluorescence data obtained by fluorescence spectrum analysis, and the amount of available nitrogen contained in the soil. That is, by utilizing this correlation, the amount of available nitrogen in the soil can be estimated by obtaining the NDSI value of the fluorescence spectrum of the soil to be examined.
Similarly, for the available phosphoric acid other than available nitrogen, total carbon, total nitrogen, and CN ratio, a calibration curve is created based on fluorescence spectrum analysis, and the soil to be examined is measured by fluorescence measurement. The geological traits of the soil can be estimated.
（蛍光強度の積分値を用いる分析方法：蛍光NDSI法）
図５〜９に示す可給態窒素、可給態リン酸、全炭素、全窒素、CN比についてのR2分布図を見ると、可給態窒素や可給態リン酸のように、10nm以下の近接した波長間での蛍光NDSIと定量値との相関係数が高くなるもの、すなわちホットスポットが狭い領域にあるものと、全炭素や全窒素、CN比のようにホットスポットが比較的広い領域にあるものとがある。ホットスポットが比較的狭い領域にあるものは、狭い波長域に情報が集中していると考えられ、比較的広い領域にあるものは広い波長域に情報が存在していると考えられる。
図５〜９に示すNDSIマトリクス表に基づく分析方法は、蛍光強度と定量値との相関関係を解析する方法によるものであるが、蛍光スペクトルに存在する情報の波長域を考えると、蛍光強度の積分値あるいは微分値を考慮することによって、土壌地力形質の情報をさらに的確に把握することができる可能性が示唆される。
(Analysis method using the integrated value of fluorescence intensity: fluorescence NDSI method)
When the R 2 distribution diagrams for the available nitrogen, available phosphoric acid, total carbon, total nitrogen, and CN ratio shown in FIGS. 5 to 9 are 10 nm, as in the case of available nitrogen and available phosphoric acid, When the correlation coefficient between the fluorescence NDSI and the quantitative value between the adjacent wavelengths below is high, that is, the hot spot is in a narrow region, the hot spot is relatively low, such as the total carbon, total nitrogen, and CN ratio. Some are in a wide area. When the hot spot is in a relatively narrow region, it is considered that information is concentrated in a narrow wavelength region, and when the hot spot is in a relatively wide region, information is considered to exist in a wide wavelength region.
The analysis method based on the NDSI matrix table shown in FIGS. 5 to 9 is based on a method of analyzing the correlation between the fluorescence intensity and the quantitative value, but considering the wavelength range of information existing in the fluorescence spectrum, the fluorescence intensity By considering the integral value or the differential value, it is suggested that the information on soil geological characteristics can be grasped more accurately.
以下では、まず、蛍光強度の積分値と土壌の定量値との相関関係について検討する。蛍光強度の積分値を利用する場合は、各土壌から得られる蛍光強度そのものにばらつきがあるから、蛍光スペクトルの蛍光強度の積分値をそのまま利用することは適当でない。そこで、本実施形態では、土壌試料から得られた蛍光スペクトルを10nmごとに区切り、区切った波長域の積分値を蛍光スペクトル全体の積分値により除して規格化した蛍光指数をもとに解析した。 In the following, first, the correlation between the integrated value of fluorescence intensity and the quantitative value of soil will be examined. When the integrated value of the fluorescence intensity is used, it is not appropriate to use the integrated value of the fluorescence intensity of the fluorescence spectrum as it is because the fluorescence intensity itself obtained from each soil varies. Therefore, in this embodiment, the fluorescence spectrum obtained from the soil sample is divided every 10 nm, and the integrated value of the divided wavelength region is divided by the integrated value of the entire fluorescence spectrum, and the analysis is performed based on the normalized fluorescence index. .
土壌試料の定量：
実験で使用した土壌試料は、前述した24点の土壌試料の他に、６点の畑作土壌（黒ボク土）を加えた30点である。土壌試料は、風乾後、乳鉢を用いて粉砕した。各々の土壌試料について、前述した方法と同様に、可給態窒素量については、培養の後に滴定法、全窒素量と全炭素量は乾式燃焼法、可給態リン酸はトルオーグ法を用いて分析して定量した。CN比は全炭素と全窒素の定量値から算出した。
表２に、上記分析方法により各々の土壌試料について、可給態窒素、可給態リン酸、全炭素、全窒素、CN比を定量した結果を示す。
Quantification of soil samples:
The soil samples used in the experiment are 30 points including the above-mentioned 24 soil samples and 6 field crops (black soil). The soil sample was air-dried and then ground using a mortar. For each soil sample, using the titration method after cultivation, the total nitrogen and total carbon content using the dry combustion method, and the available phosphoric acid using the Torugue method, as in the method described above. Analyzed and quantified. The CN ratio was calculated from the quantitative values of total carbon and total nitrogen.
Table 2 shows the results of quantifying available nitrogen, available phosphoric acid, total carbon, total nitrogen, and CN ratio for each soil sample by the above analysis method.
蛍光スペクトルの解析：
図１に示した分析装置を用いて、２４点の土壌試料について蛍光計測を行った。計測は、１サンプルについて20回繰り返して行い、得られた20個のスペクトルの平均を１つのサンプルから得られるスペクトルとし、30サンプル分のスペクトルを取得した。
分光器１８の検出データを２nm間隔に変換し、２nm間隔のスペクトルの隣り合う５波長の移動平均をとってスムージングし、これを１サンプルから得られる蛍光スペクトルとした。
Analysis of fluorescence spectrum:
Fluorescence measurement was performed on 24 soil samples using the analyzer shown in FIG. The measurement was repeated 20 times for one sample, and the average of the obtained 20 spectra was taken as a spectrum obtained from one sample, and spectra for 30 samples were obtained.
The detection data of the spectroscope 18 was converted to a 2 nm interval, and a moving average of 5 wavelengths adjacent to each other at a 2 nm interval was smoothed to obtain a fluorescence spectrum obtained from one sample.
図１１は、前述した蛍光指数の算出方法を示す。取得した蛍光スペクトルの470nmn〜900nmの蛍光強度の積分値をAとし、470nmn〜900nmの波長域を10nmごとに区切った波長域ごとの蛍光強度の積分値をBとすると、BをAで除した値を蛍光指数とする。本実施形態では、土壌試料の定量値と蛍光指数との相関関係について検討する。なお、以下では、たとえば470nm〜480nmの波長域の蛍光指数をB470−480/Aと記述する。本解析方法では蛍光スペクトルを解析して得られる蛍光指数が蛍光解析値に相当する。 FIG. 11 shows a method for calculating the fluorescence index described above. The integral value of the fluorescence intensity of 470 nmn to 900 nm of the acquired fluorescence spectrum is A, and the integral value of the fluorescence intensity for each wavelength region obtained by dividing the wavelength region of 470 nmn to 900 nm every 10 nm is B, and B is divided by A. The value is taken as the fluorescence index. In this embodiment, the correlation between the quantitative value of the soil sample and the fluorescence index is examined. Hereinafter, for example, the fluorescence index in the wavelength region of 470 nm to 480 nm is described as B470-480 / A. In this analysis method, the fluorescence index obtained by analyzing the fluorescence spectrum corresponds to the fluorescence analysis value.
図１２に蛍光スペクトルから算出した蛍光指数と、可給態窒素、可給態リン酸、全炭素、全窒素の定量値と定量値から求めたCN比との相関関係を示す。
可給態窒素については、B610−620/A以下の蛍光指数と定量値との間に負の相関がみられ、B620−630/A以上では、蛍光指数と定量値との間に正の相関が見られる。蛍光指数と定量値との相関関係が高いのはB670−680/A付近である。
図１３は、30個の土壌試料について、可給態窒素の定量値とB670−680/Aの相関関係をグラフ化し、検量線を作成した結果を示す。決定係数はB670−680/Aのときに最も高くなり、決定係数は0.2程度である。
FIG. 12 shows the correlation between the fluorescence index calculated from the fluorescence spectrum, the quantitative values of available nitrogen, available phosphoric acid, total carbon, and total nitrogen, and the CN ratio determined from the quantitative values.
For available nitrogen, there is a negative correlation between the fluorescence index below B610-620 / A and the quantitative value, and at B620-630 / A and above, there is a positive correlation between the fluorescence index and the quantitative value. Is seen. The correlation between the fluorescence index and the quantitative value is high in the vicinity of B670-680 / A.
FIG. 13 is a graph showing the correlation between the quantitative value of available nitrogen and B670-680 / A for 30 soil samples, and shows the results of creating a calibration curve. The determination coefficient is highest when B670-680 / A, and the determination coefficient is about 0.2.
図１２から、可給態リン酸については、B550−560/A以下の蛍光指数と定量値との間に正の相関がみられ、B600−610/A周辺において負の相関が見られる。蛍光指数と定量値との相関関係が高いのはB600−610/A付近である。
図１４は、各々の土壌試料について、可給態リン酸の定量値とB600−610/Aの相関関係をグラフ化したものである。決定係数はB600−610/Aのときに最も高くなり、決定係数は0.4程度である。
From FIG. 12, for available phosphoric acid, a positive correlation is observed between the fluorescence index below B550-560 / A and the quantitative value, and a negative correlation is observed around B600-610 / A. The correlation between the fluorescence index and the quantitative value is high near B600-610 / A.
FIG. 14 is a graph showing the correlation between the quantitative value of available phosphoric acid and B600-610 / A for each soil sample. The determination coefficient is highest when B600-610 / A, and the determination coefficient is about 0.4.
図１２から、全炭素、全窒素については、蛍光指数と定量値との相関関係が同様の傾向を示すことがわかる。全炭素と全窒素については、B610−620/A以下の蛍光指数と定量値との間に負の相関が見られ、B620−630/A以上では正の相関が見られる。蛍光指数と定量値との相関関係が高いのはB840−850/A付近である。
図１５は、全炭素の定量値とB840−850/Aの相関関係をグラフ化したものである。決定係数は0.4程度を示した。図１６は、全窒素の定量値とB840−850/Aの相関関係をグラフ化したものである。決定係数は0.4程度である。
FIG. 12 shows that the correlation between the fluorescence index and the quantitative value shows the same tendency for all carbon and all nitrogen. For total carbon and total nitrogen, a negative correlation is observed between the fluorescence index of B610-620 / A and lower and the quantitative value, and a positive correlation is observed for B620-630 / A and higher. The correlation between the fluorescence index and the quantitative value is high in the vicinity of B840-850 / A.
FIG. 15 is a graph showing the correlation between the quantitative value of total carbon and B840-850 / A. The coefficient of determination was about 0.4. FIG. 16 is a graph showing the correlation between the quantitative value of total nitrogen and B840-850 / A. The coefficient of determination is about 0.4.
図１２から、CN比については、B560−570/A以上の広い範囲の蛍光指数と定量値との間に正の相関が見られる。蛍光指数と定量値との相関関係はB800−810/A以上において比較的高い相関関係を示し、最も高くなるのはB880−890/A付近である。
図１７は、CN比とB880−890/Aの相関関係をグラフ化したものである。決定係数は0.3程度を示した。
From FIG. 12, regarding the CN ratio, a positive correlation is observed between the fluorescence index in a wide range of B560-570 / A or more and the quantitative value. The correlation between the fluorescence index and the quantitative value shows a relatively high correlation at B800-810 / A or higher, and the highest is around B880-890 / A.
FIG. 17 is a graph showing the correlation between the CN ratio and B880-890 / A. The coefficient of determination was about 0.3.
上記実験結果から、可給態窒素、全炭素、全窒素については、620nm以上の波長域において正の相関を示すことがわかる。このことから、有機物由来の蛍光は620nm以上の波長域に存在することが示唆される。
可給態窒素、全炭素、全窒素については正の相関を示す波長域が広いことに対し、可給態リン酸については600nm付近の積分値を用いたときに負の相関が認められた。このことは、600nm付近の波長域に可給態リン酸由来の情報が含まれていることを示唆する。リン酸は土壌中の鉄やアルミニウムの金属によって固定されることが知られている。すなわち、土壌中の金属量によって可給態リン酸量は増減すると考えられる。したがって、600nm周辺の蛍光には土壌中に含まれる鉄やアルミニウム等の金属に関する情報が含まれていることが考えられる。紫レーザ光によって金属が励起されることは考えにくいため、この実験結果は、金属を吸着した有機物由来の情報を反映したものであると考えられる。
From the above experimental results, it can be seen that available nitrogen, total carbon, and total nitrogen show a positive correlation in the wavelength region of 620 nm or more. This suggests that organic-derived fluorescence exists in a wavelength region of 620 nm or more.
For available nitrogen, total carbon, and total nitrogen, the wavelength range showing a positive correlation was wide, whereas for available phosphoric acid, a negative correlation was observed when an integral value near 600 nm was used. This suggests that information derived from available phosphoric acid is contained in the wavelength region near 600 nm. It is known that phosphoric acid is fixed by iron or aluminum metal in the soil. That is, the amount of available phosphoric acid is considered to increase or decrease depending on the amount of metal in the soil. Therefore, it is considered that the fluorescence around 600 nm contains information on metals such as iron and aluminum contained in the soil. Since it is unlikely that the metal is excited by the violet laser light, this experimental result is considered to reflect information derived from an organic substance that has adsorbed the metal.
図１３〜１７に示すように、土壌試料に紫レーザ光を照射して得られる蛍光強度の積分値と、土壌試料の可給態窒素、可給態リン酸、全炭素、全窒素、CN比等の土壌地力形質との間には一定程度の相関関係が認められる。したがって、蛍光強度（蛍光指数）と定量値との相関関係についての検量線をあらかじめ作成しておけば、土壌の蛍光測定を行うことによって、検査対象の土壌の土壌地力形質（可給態窒素、可給態リン酸等）を推定することができる。
しかしながら、図１３〜１７に示すように、蛍光強度の積分値と土壌地力形質の定量値との相関関係における決定係数は、可給態リン酸が最も高く、全炭素、全窒素、CN比、可給態窒素の順に低くなり、可給態リン酸の決定係数も0.4程度であり、必ずしも十分に高いとはいえず、むしろ、図１０に示す、可給態窒素についてNDSI値を利用した相関関係に基づくものの方が高い決定係数が得られている。
As shown in FIGS. 13 to 17, the integrated value of the fluorescence intensity obtained by irradiating the soil sample with purple laser light, the available nitrogen, available phosphoric acid, total carbon, total nitrogen, and CN ratio of the soil sample. There is a certain degree of correlation with soil geological traits such as Therefore, if a calibration curve for the correlation between the fluorescence intensity (fluorescence index) and the quantitative value is created in advance, the soil geological traits (available nitrogen, Available phosphoric acid etc.).
However, as shown in FIGS. 13 to 17, the coefficient of determination in the correlation between the integrated value of fluorescence intensity and the quantitative value of soil geological traits is the highest in available phosphoric acid, total carbon, total nitrogen, CN ratio, The determinant of available phosphoric acid is about 0.4, which is lower in the order of available nitrogen, and is not necessarily high enough. Rather, the correlation using available NDSI values for available nitrogen is shown in FIG. A higher coefficient of determination is obtained based on the relationship.
（蛍光強度の微分値を用いる分析方法：PLS回帰分析法）
本実験においては、蛍光測定によって得られる蛍光スペクトルを一次微分スペクトルに変換し、PLS回帰分析（Partial Least Squares Regressions）法を利用して検量線を作成し、紫レーザ光励起による蛍光と土壌地力形質との相関関係について検討した。PLS回帰分析法は、変数同士に相関がある場合でも、それらを潜在変数と呼ばれる中間変数に集約したうえで分析を行うため、多重共線性がある場合でも安定したモデルが得られるという特徴がある。
(Analysis method using differential value of fluorescence intensity: PLS regression analysis method)
In this experiment, the fluorescence spectrum obtained by fluorescence measurement is converted into a first derivative spectrum, and a calibration curve is created using the PLS regression analysis (Partial Least Squares Regressions) method. The correlation was examined. The PLS regression analysis method is characterized in that even if there is a correlation between variables, the analysis is performed after the variables are aggregated into an intermediate variable called a latent variable, so that a stable model can be obtained even when there is multicollinearity. .
使用した土壌試料は、蛍光強度の積分値を用いる分析方法において使用した30点の試料と同一のものである。蛍光測定も図１に示した分析装置を使用し、１サンプルについて20回繰り返して蛍光測定し、得られた20個のスペクトルの平均を１つのサンプルから得られるスペクトルとし、30サンプル分のスペクトルを取得した。 The used soil samples are the same as the 30 samples used in the analysis method using the integrated value of fluorescence intensity. Fluorescence measurement is also performed using the analyzer shown in FIG. 1, and the fluorescence measurement is repeated 20 times for one sample. The average of the 20 spectra obtained is taken as the spectrum obtained from one sample, and the spectra for 30 samples are obtained. I got it.
解析には470〜900nmの蛍光スペクトルを利用した。分光器１８の検出データを4nm間隔に変換し、4nm間隔のスペクトルの隣り合う3波長の移動平均をとってスムージングし、スムージングした蛍光スペクトルを一次微分スペクトルに変換した。
472nmから868nmの100個の一次微分値を説明変数とし、可給態窒素、可給態リン酸、全炭素、全窒素の定量値と定量値から求めたCN比を従属変数としてPLS回帰分析を行い、検量線を作成し推定値を求めた。PLS回帰分析には多変数解析ソフトを使用した。最適な潜在変数はクロスバリデーション法を用いて決定した。
For the analysis, a fluorescence spectrum of 470 to 900 nm was used. The detection data of the spectroscope 18 was converted into 4 nm intervals, smoothed by taking a moving average of 3 wavelengths adjacent to each other at 4 nm intervals, and the smoothed fluorescence spectrum was converted into a first derivative spectrum.
PLS regression analysis was performed using 100 primary differential values from 472 nm to 868 nm as explanatory variables, and CN ratio obtained from quantitative values and quantitative values of available nitrogen, available phosphoric acid, total carbon, and total nitrogen as dependent variables. A calibration curve was created to obtain an estimated value. Multivariable analysis software was used for PLS regression analysis. The optimal latent variable was determined using the cross-validation method.
図１８は、取得した蛍光スペクトルの例である。図１９は、この蛍光スペクトルの一次微分スペクトルを示す。
PLS回帰分析による推定値は微分値の偏差に回帰係数を乗じた数値の和に定量値の平均値を加えることで算出する。算出に用いた式は下記の通りである。本解析方法では、蛍光スペクトル解析により求める推定値が蛍光解析値に相当する。
PLS回帰分析は、推定する項目の変動を良く説明する主成分を抽出し、最も適当な主成分を数個用いた回帰式を作るものである。スペクトルデータのように説明変数間に多重共線性がある場合に適しており、また説明変数の数に対してデータ数が少ない場合の推定式の作成に適している。
FIG. 18 is an example of the acquired fluorescence spectrum. FIG. 19 shows the first derivative spectrum of this fluorescence spectrum.
The estimated value by PLS regression analysis is calculated by adding the average value of the quantitative values to the sum of numerical values obtained by multiplying the deviation of the differential value by the regression coefficient. The formula used for the calculation is as follows. In this analysis method, an estimated value obtained by fluorescence spectrum analysis corresponds to a fluorescence analysis value.
PLS regression analysis extracts principal components that explain well the fluctuations of items to be estimated, and creates a regression equation using several of the most appropriate principal components. It is suitable when there is multicollinearity between explanatory variables as in spectral data, and is suitable for creating an estimation formula when the number of data is small relative to the number of explanatory variables.
PLS回帰分析により、可給態窒素について推定値を算出した。可給態窒素を従属変数とし、クロスバリデーション法によりPLS回帰分析に最適な潜在変数を求めたところ潜在変数は５となった。表３に、このときに算出される回帰係数を示す。 Estimates were calculated for available nitrogen by PLS regression analysis. Using available nitrogen as a dependent variable, the optimum variable for PLS regression analysis was obtained by the cross-validation method, and the latent variable was 5. Table 3 shows the regression coefficients calculated at this time.
図２０に、可給態窒素について、PLS回帰分析による推定値と定量値との関係及び検量線を示す。PLS回帰分析による推定値と可給態窒素の定量値との間には強い相関がみられ、決定係数は0.82を示した。 FIG. 20 shows the relationship between the estimated value by the PLS regression analysis and the quantitative value and the calibration curve for the available nitrogen. There was a strong correlation between the estimated value by PLS regression analysis and the quantitative value of available nitrogen, and the coefficient of determination was 0.82.
全炭素を従属変数として、PLS回帰分析に最適な潜在変数を求めたところ、潜在変数は４と求められた。回帰係数についても表３と同様に求めることができる。図２１に、全炭素について、PLS回帰分析により求めた推定値と全炭素の定量値との関係を示す。この推定値と定量値との間には強い相関関係がみられ、決定係数は0.88を示した。 Using the total carbon as a dependent variable, the optimal latent variable for PLS regression analysis was determined, and the latent variable was determined to be 4. The regression coefficient can be obtained in the same manner as in Table 3. FIG. 21 shows the relationship between the estimated value obtained by PLS regression analysis and the quantitative value of all carbon for all carbon. A strong correlation was observed between the estimated value and the quantitative value, and the coefficient of determination was 0.88.
全窒素を従属変数として、PLS回帰分析に最適な潜在変数を求めたところ、潜在変数は４と求められた。回帰係数についても表３に示すと同様に求めることができる。図２２に、全窒素について、PLS回帰分析により求めた推定値と全炭素の定量値との関係を示す。この推定値と定量値との間には強い相関関係がみられ、決定係数は0.86を示した。 Using the total nitrogen as a dependent variable, the optimal latent variable for PLS regression analysis was determined, and the latent variable was determined to be 4. The regression coefficient can be obtained in the same manner as shown in Table 3. FIG. 22 shows the relationship between the estimated value obtained by PLS regression analysis and the quantitative value of total carbon for total nitrogen. There was a strong correlation between the estimated value and the quantitative value, and the coefficient of determination was 0.86.
可給態リン酸を従属変数として、PLS回帰分析に最適な潜在変数を求めたところ潜在変数は３と求められた。回帰係数についても表３に示すと同様に求めることができる。図２３に、可給態リン酸について、PLS回帰分析により求めた推定値と全炭素の定量値との関係を示す。この推定値と定量値との間には相関関係がみられ、決定係数は0.6を示した。 Using available phosphate as a dependent variable, the optimal latent variable for PLS regression analysis was determined, and the latent variable was determined to be 3. The regression coefficient can be obtained in the same manner as shown in Table 3. FIG. 23 shows the relationship between the estimated value obtained by PLS regression analysis and the quantitative value of total carbon for available phosphoric acid. There was a correlation between the estimated value and the quantitative value, and the coefficient of determination was 0.6.
CN比を従属変数としたとき、最適な潜在変数は４と求められた。CN比についても表３と同様な回帰係数を求めることができる。図２４に、CN比について、PLS回帰分析により求めた推定値とCN比の値との関係を示す。この推定値とCN比との間には強い相関関係がみられ、決定係数は0.69を示した。 The optimal latent variable was determined to be 4 when the CN ratio was the dependent variable. For the CN ratio, the same regression coefficient as in Table 3 can be obtained. FIG. 24 shows the relationship between the CN ratio and the estimated value obtained by PLS regression analysis and the CN ratio value. There was a strong correlation between the estimated value and the CN ratio, and the coefficient of determination was 0.69.
上述したPLS回帰分析による推定値と定量値との相関関係を示す決定係数についてみると、全炭素、全窒素、可給態窒素、CN比、可給態リン酸の順に高い数値を示している。可給態窒素、全炭素、全窒素を従属変数としたときは、いずれも決定係数は0.82以上と高い数値を示すことから、土壌試料の蛍光スペクトルの一次微分値に基づきPLS回帰分析方法を利用して可給態窒素、全炭素、全窒素量を推定することにより確度の高い情報を得ることが可能である。また、潜在変数が３〜５といったように少ないことから、PLS回帰分析の成績は良い。 Looking at the coefficient of determination that shows the correlation between the estimated value and the quantitative value obtained by the PLS regression analysis described above, all carbon, total nitrogen, available nitrogen, CN ratio, and available phosphoric acid are shown in order of increasing numbers. . When available nitrogen, total carbon, and total nitrogen are the dependent variables, the coefficient of determination is as high as 0.82 or higher, so use the PLS regression analysis method based on the first derivative of the fluorescence spectrum of the soil sample. Thus, it is possible to obtain highly accurate information by estimating the amount of available nitrogen, total carbon, and total nitrogen. Moreover, since there are few latent variables, such as 3-5, the result of PLS regression analysis is good.
可給態リン酸については、決定係数が0.60であった。可給態リン酸の簡易推定法としては高感度反射式光度計を用いる簡易推定法がある。この簡易推定法による可給態リン酸の推定値と定量値との相関における決定係数は0.82であり、本実験における手法は、この簡易推定法と比べて精度は低くなっている。しかしながら、本実験方法の場合は、土壌を風乾させて蛍光スペクトルの測定を行うのみであり、従来法のように抽出液を用いてろ液を抽出するといった操作が不要で、簡便に測定できる点で優れている。 For available phosphoric acid, the coefficient of determination was 0.60. As a simple estimation method of available phosphoric acid, there is a simple estimation method using a highly sensitive reflection photometer. The coefficient of determination in the correlation between the estimated value and the quantitative value of available phosphoric acid by this simple estimation method is 0.82, and the method in this experiment is less accurate than this simple estimation method. However, in the case of this experimental method, the soil is only air-dried and the fluorescence spectrum is measured, and the operation of extracting the filtrate using the extract as in the conventional method is not necessary and can be easily performed. Are better.
CN比については、決定係数が0.70と比較的高い数値を示した。CN比は全窒素と全炭素の定量値から算出して求める方法が従来法である。本実験方法によれば、全窒素と全炭素の算出結果に基づいてCN比を求めるのではなく、蛍光スペクトルデータから直接CN比を求めることができる点で特徴的である。この分析方法は、堆肥等の有機質肥料のCN比を推定する他に、水耕栽培における溶液中のCN比を推定するといった場合にも適用することが可能である。 Regarding the CN ratio, the coefficient of determination was relatively high at 0.70. The conventional method is to calculate and obtain the CN ratio from the quantitative values of total nitrogen and total carbon. This experimental method is characteristic in that the CN ratio can be obtained directly from the fluorescence spectrum data, not the CN ratio based on the calculation results of total nitrogen and total carbon. This analysis method can be applied not only to estimate the CN ratio of organic fertilizers such as compost but also to estimate the CN ratio in a solution in hydroponics.
なお、PLS回帰分析法と、前述したNDSI値を用いる解析方法、蛍光強度の積分値（蛍光指数）を用いる解析方法とを比較すると、PLS回帰分析法は、NDSI値、蛍光指数を用いる方法と比べて精度の高い推定が可能であるものの、100（少なくとも50）程度の解析データを用いる必要がある。一方、NDSI値を用いる方法は、PLS回帰分析法にくらべて精度は劣るものの、ホットスポットの２波長のNDSI値のみから容易に推定できるという利点があり、蛍光指数を用いる方法も特定の蛍光指数から土壌地力形質を推定することができるという利点がある。 In addition, comparing the PLS regression analysis method with the analysis method using the NDSI value described above and the analysis method using the integrated value of fluorescence intensity (fluorescence index), the PLS regression analysis method is a method using the NDSI value and the fluorescence index. Although more accurate estimation is possible, it is necessary to use analysis data of about 100 (at least 50). On the other hand, the method using the NDSI value is less accurate than the PLS regression analysis method, but has the advantage that it can be easily estimated from the NDSI value of the two wavelengths of the hot spot. The method using the fluorescence index is also a specific fluorescence index. From this, there is an advantage that the soil geological traits can be estimated.
なお、上述した各実施形態においては、検査対象である土壌の蛍光スペクトルに基づいて可給態窒素、可給態リン酸、全炭素、全窒素、CN比を求める方法について説明した。蛍光スペクトルの解析によって検出し得る土壌地力形質としては、これら以外に塩基置換容量（CEC)、易分解性炭素等がある。塩基置換容量は土壌が肥料を吸着することができる能力（保肥力）に関し、易分解性炭素は有機態窒素の無機化速度に関する。易分解性炭素が多いと有機態窒素の無機化速度が低下し、多すぎると、作物は普通「窒素飢餓」になる。 In each of the above-described embodiments, the method for obtaining the available nitrogen, the available phosphoric acid, the total carbon, the total nitrogen, and the CN ratio based on the fluorescence spectrum of the soil to be inspected has been described. Other soil geological traits that can be detected by analysis of the fluorescence spectrum include base substitution capacity (CEC) and readily degradable carbon. Base substitution capacity relates to the ability of soil to adsorb fertilizer (fertilizing power), and readily degradable carbon relates to the mineralization rate of organic nitrogen. If there is a lot of readily degradable carbon, the mineralization rate of organic nitrogen will decrease, and if it is too much, the crop will normally be “nitrogen starved”.
（CECについての追加実験）
PLS回帰分析方法を利用し、上述した30サンプルについて、塩基置換容量（CEC)について同様の解析を行った。図２５に、PLS回帰分析法によって求めたCECの推定値とCECの定量値との関係を示す。CECについての決定係数R2=0.652であり、他の土壌地力形質と比較すると推定精度が若干低くなっているが、推定値とCECの定量値との相関関係が認められた。潜在変数は３である。
(Additional experiment on CEC)
Using the PLS regression analysis method, the base analysis capacity (CEC) was similarly analyzed for the 30 samples described above. FIG. 25 shows the relationship between the estimated value of CEC obtained by the PLS regression analysis method and the quantitative value of CEC. The coefficient of determination for CEC was R 2 = 0.652, and the estimation accuracy was slightly lower than that of other soil geological traits, but there was a correlation between the estimated value and the quantitative value of CEC. The latent variable is 3.
CECはCation Exchange Capacityの略であり、電気的にマイナスの土壌が、最大限どの程度、塩基(Ca・Mg・K・Na・アンモニア・H等)の陽イオンを吸着できるかの指標であり、肥効養分を蓄えておける量や緩衝力を示す数値である。
土壌の肥沃度は、CECが大きい場合に高く、作物の生育も良くなる。CECが小さい土壌では緩衝力も小さい肥培管理がむずかしい。一般に、粘土および腐植の多い土では、塩基置換容量(CEC)が大きく、緩衝力も大きくなる。
CECの従来法による測定では濾過が必要であり、測定には約２日要する。これに対して、本実施形態の紫レーザ光励起による方法によれば、１〜３時間で分析することができる。
CEC is an abbreviation for Cation Exchange Capacity, and it is an index of how much cation of the base (Ca, Mg, K, Na, ammonia, H, etc.) can be adsorbed to the maximum extent by electrically negative soil. It is a numerical value indicating the amount and buffering power that can store fertilizers.
Soil fertility is high when CEC is large and crop growth is improved. In soil with small CEC, it is difficult to manage fertilizer with low buffering capacity. In general, soil with a lot of clay and humus has a large base substitution capacity (CEC) and a large buffering capacity.
The CEC conventional method requires filtration, and the measurement takes about 2 days. On the other hand, according to the method by violet laser light excitation of this embodiment, it can analyze in 1-3 hours.
本発明に係る土壌地力形質の分析方法は、レーザ光励起による蛍光スペクトル分析により土壌の地力形質を分析する手法であり、同一の計測系を使用して、可給態窒素、可給態リン酸等の複数の土壌地力形質を同時に計測することができる。従来、土壌地力形質を計測する場合は、測定しようとする土壌の地力形質、すなわち可給態窒素、可給態リン酸、全窒素、全炭素といった計測対象に応じて、別々の測定系や測定手段を用意して個別に測定している。本発明方法によれば、計測で得られた蛍光スペクトルを共通に利用して、複数の土壌地力形質を推定することができる点で有効である。 The soil geological trait analysis method according to the present invention is a technique for analyzing soil geological traits by fluorescence spectrum analysis by laser light excitation, and using the same measurement system, available nitrogen, available phosphoric acid, etc. It is possible to simultaneously measure multiple soil geological traits. Conventionally, when measuring soil geological traits, separate measurement systems and measurements are made according to the geological traits of the soil to be measured, ie, available nitrogen, available phosphoric acid, total nitrogen, total carbon. A measure is prepared and measured individually. According to the method of the present invention, it is effective in that a plurality of soil geological traits can be estimated by commonly using the fluorescence spectrum obtained by measurement.
また、本発明方法では被検体である土壌は、風乾させただけで分析装置にセットして測定すればよく、計測のために、培養法や抽出法といった処理を行う必要がなく、きわめて簡便に、短時間のうちに測定することができる。また、蛍光スペクトルの分析も周知のデータ処理方法を利用するものであって、データ解析も容易である。
また、蛍光測定に使用する分析装置は、簡易な構成からなるものであり、あらかじめ、複数のサンプルを用いて検量線を作成することにより、この検量線に基づいて被検体の土壌の地力形質を分析し、推定することができる。
Further, in the method of the present invention, the soil that is the subject may be measured by setting it in an analyzer just by air-drying, and it is not necessary to perform a treatment such as a culture method or an extraction method for the measurement. Can be measured in a short time. In addition, the analysis of the fluorescence spectrum uses a known data processing method, and the data analysis is easy.
Moreover, the analyzer used for the fluorescence measurement has a simple configuration, and by preparing a calibration curve using a plurality of samples in advance, the geological characteristics of the soil of the subject can be determined based on the calibration curve. Can be analyzed and estimated.
上記実施形態においては、土壌地力形質を推定する方法について説明したが、本発明方法は、土壌地力形質の分析に限らず、有機物の総量や、類似した分解特性を有する組成部分の近似分析に利用することが可能であり、食品中の易分解性のたんぱく質などへの適用が考えられる。近似分析による分析対象は、粗たんぱく質や粗繊維や粗灰分などのような特定の画分で、ひとつの物質ではなく類似した物質群をまとめた成分量である。食品成分や飼料成分では、類似した栄養特性をもつ成分がひとくくりにされて分析され、有用な情報として得ることができる。本発明方法はHPLC等の定量分析とは異なり、近似分析における定量に適するという特徴がある。 In the above embodiment, the method for estimating soil geological traits has been described. However, the method of the present invention is not limited to the analysis of soil geological traits, but is used for the approximate analysis of the total amount of organic matter and composition parts having similar decomposition characteristics. It can be applied to easily degradable proteins in foods. The target of analysis by the approximate analysis is a specific fraction such as crude protein, crude fiber, and crude ash, and the amount of components that are not a single substance but a group of similar substances. In food ingredients and feed ingredients, ingredients having similar nutritional characteristics are grouped and analyzed to obtain useful information. Unlike the quantitative analysis such as HPLC, the method of the present invention is characterized by being suitable for quantitative analysis in approximate analysis.
１０ セット部
１３ レーザヘッド
１５ レーザ電源
１６ 受光ヘッド
１６a フィルタ
１７石英光ファイバ
１８ 分光器
２０ 解析部
DESCRIPTION OF SYMBOLS 10 Set part 13 Laser head 15 Laser power supply 16 Light receiving head 16a Filter 17 Quartz optical fiber 18 Spectrometer 20 Analysis part
Claims (9)
前記蛍光スペクトルの解析結果に基づいて前記土壌地力形質を個別に推定するための検量線を作成する工程として、
異なる土壌地力形質を備える複数種の評価用の土壌を定量分析して各々の土壌の前記土壌地力形質の定量値を特定する工程と、
前記評価用の土壌に前記励起光を照射して各々の土壌の蛍光スペクトルを取得し、蛍光スペクトルを解析することにより蛍光解析値を算出する工程と、
前記土壌地力形質の定量値と前記蛍光解析値との相関関係から、前記各々の土壌地力形質と蛍光解析値との検量線を作成する工程とを備え、
前記被検体の土壌地力形質を分析する方法として、
前記被検体の蛍光スペクトルを解析して前記土壌地力形質の各々に対応する蛍光解析値を算出する工程と、該蛍光解析値と前記検量線に基づき、当該被検体の土壌地力形質として、可給態窒素、可給態リン酸、全窒素、全炭素、CN比、CECのいずれかを分析することを特徴とする土壌地力形質の分析方法。 Using air-dried soil as an object, irradiating the object with excitation light, and analyzing the fluorescence spectrum from the object, the soil geological characteristics of the object are available nitrogen, available phosphoric acid, total nitrogen, and total carbon. , CN ratio, CEC analysis method,
As a step of creating a calibration curve for individually estimating the soil geological traits based on the analysis result of the fluorescence spectrum,
A step of quantitatively analyzing a plurality of types of soils for evaluation having different soil geological traits to identify quantitative values of the soil geological traits of each soil;
Irradiating the soil for evaluation with the excitation light to obtain a fluorescence spectrum of each soil, and calculating a fluorescence analysis value by analyzing the fluorescence spectrum;
Wherein the quantitative value of the soil 壌地 force transformed from the correlation between the fluorescence analysis values, and a step of creating a calibration curve of the soil 壌地 force trait fluorescence analysis value of the respective,
As a method of analyzing the soil geological traits of the subject,
Before SL calculating a fluorescence analysis values corresponding to each of the soil fertility trait analyzes the fluorescence spectrum of the object, based on the calibration curve and fluorescent analysis value, as soil fertility traits of the subject, allowed A method for analyzing soil geological characteristics, characterized by analyzing supply nitrogen, available phosphoric acid, total nitrogen, total carbon, CN ratio, or CEC .
蛍光スペクトルの一次微分値を説明変数とし、土壌地力形質を従属変数とするPLS回帰分析法を利用して算出した推定値を蛍光解析値とすることを特徴とする請求項１記載の土壌地力形質の分析方法。 Te process smell of calculating the fluorescence analysis value,
The primary differential value of the fluorescence spectrum as explanatory variables, soil fertility trait of claim 1, wherein the estimated value calculated by using the PLS regression analysis of the soil fertility traits as the dependent variable, characterized in that the fluorescence analysis value Analysis method.
蛍光スペクトルの波長間の関係を正規化分光指数（NDSI値)として算出し、土壌地力形質の推定に有効に寄与する波長の組み合わせに係るNDSI値を蛍光解析値とすることを特徴とする請求項１記載の土壌地力形質の分析方法。 Te process smell of calculating the fluorescence analysis value,
Claims calculating the relationship between the wavelength of the fluorescence spectrum as the normalized spectral index (NDSI value), the NDSI value according to a combination of effectively contributes wavelength to estimate the soil land force trait characterized by the fluorescence analysis value Item 1. The soil geological trait analysis method according to Item 1 .
蛍光スペクトルを一定波長範囲ごとに区切った波長域ごとの蛍光強度の積分値を、蛍光スペクトル全体の積分値により除した蛍光指数を求め、前記波長域ごとの蛍光指数のうち他の蛍光指数と比較して前記定量値と相関関係の高い波長域の蛍光指数を蛍光解析値とすることを特徴とする請求項１記載の土壌地力形質の分析方法。 Te process smell of calculating the fluorescence analysis value,
Find the fluorescence index obtained by dividing the integral value of the fluorescence intensity for each wavelength range obtained by dividing the fluorescence spectrum into a certain wavelength range by the integral value of the entire fluorescence spectrum, and compare it with other fluorescence indexes among the fluorescence indexes for each wavelength range. claim 1 method for analyzing soil fertility trait, wherein the a fluorescence analysis values the fluorescence index of wavelength range having high correlation with the quantitative value was.
被検体である風乾土壌をセットするセット部と、
前記被検体に励起光を照射する光照射部と、
前記被検体からの蛍光を計測する蛍光測定部と、
前記蛍光測定部の測定結果に基づき蛍光データを解析する解析部と、
を備え、
前記解析部は、
前記蛍光スペクトルの解析結果に基づいて前記土壌地力形質を個別に推定するための検量線を作成する手段として、
異なる土壌地力形質を備える複数種の評価用の土壌に前記励起光を照射して各々の土壌の蛍光スペクトルを取得し、蛍光スペクトルを解析することにより蛍光解析値を算出する手段と、
前記評価用の土壌について特定された定量値と前記蛍光解析値との相関関係から、前記各々の土壌地力形質と蛍光解析値との検量線を作成する手段とを備え、
前記被検体の土壌地力形質を分析する手段として、
前記被検体の蛍光スペクトルを解析して前記土壌地力形質の各々に対応する蛍光解析値を算出する手段と、該蛍光解析値と前記検量線に基づき、当該被検体の土壌地力形質として、可給態窒素、可給態リン酸、全窒素、全炭素、CN比、CECのいずれかを分析する手段とを備えることを特徴とする土壌地力形質の分析装置。 Using air-dried soil as an object, irradiating the object with excitation light, and analyzing the fluorescence spectrum from the object, the soil geological characteristics of the object are available nitrogen, available phosphoric acid, total nitrogen, and total carbon. An analyzer for analyzing CN ratio and CEC,
A set unit for setting the air-dried soil as the subject;
A light irradiation unit that irradiates the subject with excitation light;
A fluorescence measuring unit for measuring fluorescence from the subject;
An analysis unit for analyzing the fluorescence data based on the measurement result of the fluorescence measurement unit,
With
The analysis unit
As means for creating a calibration curve for individually estimating the soil geological traits based on the analysis result of the fluorescence spectrum,
Means for irradiating a plurality of types of soil for evaluation having different soil geological traits with the excitation light to obtain a fluorescence spectrum of each soil, and calculating a fluorescence analysis value by analyzing the fluorescence spectrum;
From the correlation between the quantitative value identified for the soil for evaluation and the fluorescence analysis value, and comprising means for creating a calibration curve of each soil geological trait and fluorescence analysis value,
As a means for analyzing the soil geological traits of the subject,
A means for analyzing a fluorescence spectrum of the subject to calculate a fluorescence analysis value corresponding to each of the soil geological traits, and based on the fluorescence analysis value and the calibration curve, as a soil geological trait of the subject A device for analyzing soil geological characteristics, characterized in that it comprises means for analyzing any of nitrogen, available phosphoric acid, total nitrogen, total carbon, CN ratio, and CEC .
蛍光スペクトルの一次微分値を説明変数とし、土壌地力形質を従属変数とするPLS回帰分析法を利用して算出した推定値を蛍光解析値とすることを特徴とする請求項５記載の土壌地力形質の分析装置。6. The soil geological trait according to claim 5, wherein an estimated value calculated using a PLS regression analysis method using the first derivative of the fluorescence spectrum as an explanatory variable and the soil geological trait as a dependent variable is used as a fluorescence analysis value. Analysis equipment.
蛍光スペクトルの波長間の関係を正規化分光指数（NDSI値)として算出し、土壌地力形質の推定に有効に寄与する波長の組み合わせに係るNDSI値を蛍光解析値とすることを特徴とする請求項５記載の土壌地力形質の分析装置。The relationship between the wavelengths of the fluorescence spectrum is calculated as a normalized spectral index (NDSI value), and the NDSI value relating to the combination of wavelengths that effectively contributes to estimation of soil geological traits is used as the fluorescence analysis value. 5. The soil geological trait analyzer according to 5.
蛍光スペクトルを一定波長範囲ごとに区切った波長域ごとの蛍光強度の積分値を、蛍光スペクトル全体の積分値により除した蛍光指数を求め、前記波長域ごとの蛍光指数のうち他の蛍光指数と比較して前記定量値と相関関係の高い波長域の蛍光指数を蛍光解析値とすることを特徴とする請求項５記載の土壌地力形質の分析装置。Find the fluorescence index obtained by dividing the integral value of the fluorescence intensity for each wavelength range obtained by dividing the fluorescence spectrum into a certain wavelength range by the integral value of the entire fluorescence spectrum, and compare it with other fluorescence indexes among the fluorescence indexes for each wavelength range. 6. The soil geological trait analyzer according to claim 5, wherein a fluorescence index in a wavelength region having a high correlation with the quantitative value is used as a fluorescence analysis value.
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