Characteristic Spectral Data Research Articles

Development of an online prediction system for soil organic matter and soil moisture content based on multi-modal fusion

Realizing accurate determination of in situ soil organic matter (SOM) content and soil moisture (SM) content in the field is of great importance for improving agricultural production efficiency. However, the feature information of a single sensor is limited, and there is still a certain gap in modeling accuracy compared to traditional laboratory methods. The variations of SM in the field also interfere with data collection, limiting the application of single sensor. In order to realize the efficient detection of in-situ SOM and SM content, this study developed an online detection system for SOM and SM content based on the fusion of characteristic wavelengths, visible images and thermal imaging image features. Firstly, based on a vehicle-mounted platform, a visible-thermal imaging camera and a characteristic wavelength integration device were integrated in a deep pine plow to realize the simultaneous acquisition of in-situ soil multi-sensor data. Then, a lightweight multimodal network was constructed to obtain thermal visible light image features and characteristic wavelength features through branch networks, achieving deep fusion of different modal data and predicting SOM and SM content. Finally, output the forecasting results of SOM and SM content, and transmit the predictive information to the cloud platform for storage. It was verified that the Multi-modal proposed in this study worked best in the laboratory environment, with a predicted R2 of 0.91 and RMSE of 2.9 g/kg for SOM, and a predicted R2 of 0.92 and RMSE of 0.77 % for SM. Compared with single image or characteristic spectral data, the fusion of visible image and characteristic wavelength effectively improved the prediction accuracy of SOM. The real-time prediction of SM was realized by fusing thermal imaging data, and the elimination of the moisture effect of visible images and characteristic wavelengths was also realized with the help of deep fusion of Multi-modal network. After field validation, the R2 of the Multi-modal system was 0.84 and the RMSE was 5.0 g/kg for SOM, and the R2 of the SM was 0.88 and the RMSE was 1.03 %. Despite the differences in soil types between the validation field and the sampling field, the system still demonstrated strong generalization and achieved high accuracy prediction of in-situ SOM and SM in the field, which effectively improves the efficiency and applicability of field. The efficiency and applicability of soil testing effectively improve the efficiency and provide technical guidance for precision management in the field.

Digital Prediction of the Purchase Price of Fresh Tea Leaves of Enshi Yulu Based on Near-Infrared Spectroscopy Combined with Multivariate Analysis.

In this study, near-infrared spectroscopy (NIRS) combined with a variety of chemometrics methods was used to establish a fast and non-destructive prediction model for the purchase price of fresh tea leaves. Firstly, a paired t-test was conducted on the quality index (QI) of seven quality grade fresh tea samples, all of which showed statistical significance (p < 0.05). Further, there was a good linear relationship between the QI, quality grades, and purchase price of fresh tea samples, with the determination coefficient being greater than 0.99. Then, the original near-infrared spectra of fresh tea samples were obtained and preprocessed, with the combination (standard normal variable (SNV) + second derivative (SD)) as the optimal preprocessing method. Four spectral intervals closely related to fresh tea prices were screened using the synergy interval partial least squares (si-PLS), namely 4377.62 cm-1-4751.74 cm-1, 4755.63 cm-1-5129.75 cm-1, 6262.70 cm-1-6633.93 cm-1, and 7386 cm-1-7756.32 cm-1, respectively. The genetic algorithm (GA) was applied to accurately extract 70 and 33 feature spectral data points from the whole denoised spectral data (DSD) and the four characteristic spectral intervals data (FSD), respectively. Principal component analysis (PCA) was applied, respectively, on the data points selected, and the cumulative contribution rates of the first three PCs were 99.856% and 99.852%. Finally, the back propagation artificial neural (BP-ANN) model with a 3-5-1 structure was calibrated with the first three PCs. When the transfer function was logistic, the best results were obtained (Rp2 = 0.985, RMSEP = 6.732 RMB/kg) by 33 feature spectral data points. The detection effect of the best BP-ANN model by 14 external samples were R2 = 0.987 and RMSEP = 6.670 RMB/kg. The results of this study have achieved real-time, non-destructive, and accurate evaluation and digital display of purchase prices of fresh tea samples by using NIRS technology.

Inversion prediction of COD in wastewater based on hyperspectral technology

COD is an important detection index in the field of water environmental treatment. At present, COD detection methods and instruments have shortcomings such as long detection time, complicated detection process and high consumption of chemical agent. In this paper, a rapid detection method for COD index of wastewater based on hyperspectral technology and machine learning is developed, and a complete non-contact detection scheme is formed. In the method, the characteristic spectral data of standard COD in the sample spectral curve are extracted by successive projections algorithm (SPA) and genetic algorithm (GA) to establish the regression model of the index. The model is applied to the rapid detection of COD index in the textile desizing wastewater treatment process, and the accuracy of the model in real environment is comprehensively evaluated by root mean square error (RMSE), relative analysis error (RPD) and determination coefficient (R2). Our results indicate that the model has high prediction stability and strong generalization ability (the RMSE is 40.4489 mg/L, RPD is 9.37, and R2 is 0.97) and is a green method for COD detection in wastewater.

Terpenoids and Phenylpropanoids Isolated from the Twigs and Leaves of Abelia macrotera and Their Anti-Inflammatory Activities.

A new triterpenoid, 3β-hydroxyurs-12-en-28,20β-olide (1), as well as thirteen known terpenoids (2-14) and three known phenylpropanoids (15-17), were isolated from the twigs and leaves of Abelia macrotera. Compounds 2, 5-17 were isolated for the first time from the Abelia genus. The structure of compound 1 was determined using the characteristic spectral data (HR-ESI-MS, UV, 1D and 2D-NMR, and X-ray single-crystal diffraction. Furthermore, the inhibitory effects of all compounds on NO production in LPS-induced RAW 264.7 cells were tested, and compound 15 showed obvious inhibitory effect, with IC50 values of 23.77±1.61 μM. Through target screening and molecular docking technology, it can be speculated that compound 15 may play an anti-inflammatory role by combining with Cathepsin G & Chymase and HPG D.

Fusion of THz-TDS and NIRS Based Detection of Moisture Content for Cattle Feed

As an essential index to evaluate feed quality, feed moisture content which is too high or too low will impose an adverse impact on feed nutritional value. Therefore, the quantitative analysis of feed moisture content is significant. In this paper, the detection of feed moisture content based on terahertz (THz) and near-infrared (NIR) spectroscopy and data fusion technology of THz and NIR (THz-NIR) was investigated. First, feed samples with different water content (29.46%–49.46%) were prepared, and THz (50–3000 μm) and NIR (900–1700 nm) spectral data of samples was collected and preprocessed, and the feed samples were divided into correction set and verification set by 2:1. Second, the spectral data was fused through the head-to-tail splicing, and the feed moisture content prediction model was established combined with partial least squares regression (PLSR). Third, competitive adaptive reweighting sampling (CARS) was applied to extract spectral characteristic variables for feature layer fusion, and the feed moisture content prediction model in feature level was constructed combined with PLSR. Finally, the evaluation parameters validation set correlation coefficient (Rp), the root mean square error of prediction (RMSEP), and the residual predictive deviation (RPD) were employed to evaluate the prediction effect of the model. The results indicated that THz, NIR spectra, and data fusion technology could quickly and effectively predict feed moisture content. Among them, the characteristic layer spectral data fusion model achieved the optimal prediction effect while Rp, RMSEP, and RPD reached 0.9933, 0.0069, and 8.7386 respectively. In conclusion, compared with the prediction model established by single THz and NIR spectrum, THz-NIR spectrum data fusion could more accurately predict feed moisture content and provide certain theoretical and technical support for inspirations and methods for quantitative analysis of feed moisture content of livestock and poultry.

Handheld SERS coupled with QuEChERs for the sensitive analysis of multiple pesticides in basmati rice

Pesticides are a safety issue globally and cause serious concerns for the environment, wildlife and human health. The handheld detection of four pesticide residues widely used in Basmati rice production using surface-enhanced Raman spectroscopy (SERS) is reported. Different SERS substrates were synthesised and their plasmonic and Raman scattering properties evaluated. Using this approach, detection limits for pesticide residues were achieved within the range of 5 ppb-75 ppb, in solvent. Various extraction techniques were assessed to recover pesticide residues from spiked Basmati rice. Quick, Easy, Cheap, Effective, Rugged and Safe (QuEChERs) acetate extraction was applied and characteristic spectral data for each pesticide was obtained from the spiked matrix and analysed using handheld-SERS. This approach allowed detection limits within the matrix conditions to be markedly improved, due to the rapid aggregation of nanogold caused by the extraction medium. Thus, detection limits for three out of four pesticides were detectable below the Maximum Residue Limits (MRLs) of 10 ppb in Basmati rice. Furthermore, the multiplexing performance of handheld-SERS was assessed in solvent and matrix conditions. This study highlights the great potential of handheld-SERS for the rapid on-site detection of pesticide residues in rice and other commodities.

Wood classification study based on thermal physical parameters with intelligent method of artificial neural networks

In this study, 65 kinds of wood samples were classified by using artificial neural networks based on the measured value of wood thermal physical parameters. First, the thermal conductivities and the thermal diffusion coefficients of the wood samples were measured. The transient temperature rise curve of wood samples during the test process was recorded, and the characteristic values of the transient temperature rise curve were extracted by logarithmic curve fitting. The emissivity spectrum representing the thermal physical properties of wood surface was measured, and the characteristic spectral data were selected according to the principal component analysis. An artificial neural network model was established based on the extracted feature values and characteristic spectral data to classify the wood species. The experimental results showed that the comprehensive correct classification rate of the proposed wood classification method was 99.85%. In addition, the proposed wood classification method was compared with a wood classification method based on laser induced breakdown spectrum and near infrared spectrum, which indicates the feasibility of wood classification based on the values of wood thermal physical properties.

Total Synthesis of the Proposed Microcyclamides MZ602 and MZ568.

The first convergent total synthesis for the proposed structures of microcyclamides MZ602 (1) and MZ568 (2) has been accomplished in 11 linear steps with 12.5 and 16.8% overall yield, respectively. Key features of the syntheses include a one-pot cascade reaction to construct core Boc-l-Ile-Thz-OAllyl fragment 5, and a removable pseudoproline (ΨMe,Me pro) inducer assisted cyclization of thiazole-containing all-l linear peptides. The spectral data (1H NMR, 13C NMR, and HRMS) of synthetic MZ602 (1) were quite similar to those of the proposed natural microcyclamide MZ602, except to an opposite sign of the optical rotation value. Surprisingly, the synthetic MZ568 (2) presented large discrepancies in characteristic spectral data from those of the reported natural product, although the absolute configuration of key intermediate 36 was unambiguously determined by single-crystal X-ray analysis in our work. These findings revealed that the proposed structures of natural microcyclamides MZ602 and MZ568 required revision.

Natural products isolated from Casimiroa

AbstractAbout 140 genera and more than 1,600 species belong to the Rutaceae family. They grow in temperate and tropical zones on both hemispheres, as trees, shrubs, and herbs. Casimiroa is one of the genera constituting 13 species, most of which are found in tropical and subtropical regions. Many chemical constituents have been derived from this genus, including quinoline alkaloids, flavonoids, coumarins, and N-benzoyltyramide derivatives. This article reviews different studies carried out on aromatic compounds of genus Casimiroa; their biological activities; the different skeletons of coumarins, alkaloids, flavonoids, and others; and their characteristic NMR spectral data.

Prediction of moisture content of wood using Modified Random Frog and Vis-NIR hyperspectral imaging

Vis-NIR hyperspectral imaging was adopted to predict the moisture content (MC) of wood. A total of 30 beech blocks were used in the experiments, each block was dried 7 times to generate different cases of moisture contents. The 210 samples were divided into a calibration set (140) and a prediction set (70) using Kennard-stone (KS) algorithm. The spectral data of each sample was collected by the hyperspectral imaging system, and pretreated using standard normal variate (SNV). To solve the problem that the random frog algorithm (RF) needs to reset threshold after obtaining the selection probability of all variables at a time, adaptive reweighted sampling (ARS) and exponentially decreasing function (EDF) are applied to improve RF in this paper. The modified RF (MRF) was compared with RF, successive projections algorithm (SPA) and competitive adaptive reweighted sampling (CARS). Based on the full spectrum data (FS) and four characteristic spectral data, different models were built using Gaussian process regression (GPR). The results show that the MRF not only avoids setting thresholds, but also improves the stability and accuracy of the model. The MRF-GPR model achieved the best predictive performance of wood moisture content, with Rp2, RMSEP of 0.9785, 1.6125%, respectively. So the hyperspectral imaging technique is suitable for predicting the moisture content of wood.

Quantitative determination and characteristic wavelength selection of available nitrogen in coco-peat by NIR spectroscopy

Available nitrogen content reflects the nitrogen latest supply capacity of coco-peat. Rapid determination of available nitrogen content in coco-peat is of great significance for precision fertilization in precision agriculture. In this study, available nitrogen of coco-peat was rapidly and quantitatively detected by near-infrared (NIR) spectroscopy. The mathematical model between spectral data and measured available nitrogen values was established, and the impacts of different spectral pre-processing on the whole band modeling results were compared and analyzed. Successive projections algorithm (SPA) and elimination of uninformative variables (UVE) were applied to remove redundant and irrelevant information variables from original spectrum and various pre-processing spectra, and the corresponding PLSR and MLR spectral prediction models were established. Comparing the modeling results of using full-band spectral data and eliminating the irrelevant information spectral data, the optimal spectral prediction model was established by using MLR. And the model with filtered characteristic wavelength spectral data by SPA after Savitzky-Golay smoothing (SG smoothing) pre-processing yielded optimum results with the correlation coefficients for calibration set (RC) 0.996 and prediction set (RP) 0.990; the root mean square errors for calibration set (RMSEC) and prediction set (RMSEP) were 4.634 mg/100 g and 7.203 mg/100 g, respectively; and the ratio of prediction to deviation (RPD) was 7.011. The results showed that fast quantitative detection of available nitrogen of coco-peat could be achieved by NIR spectroscopy, and it could provide a reference for the rapid detection of substrate fertilizer content in facility agriculture.

Research on Detection of Multi-adulteration of Sesame Oils by Near-infrared Spectroscopy

Aiming at the adulteration of sesame oil, our research is focused on using near-infrared spectroscopy combined with chemometrics to achieve rapid detection. The near-infrared spectrum of the sample was collected, and the data analysis and modeling were conducted on MATLAB. The raw spectral data was pretreated using multiplicative scatter correction (MSC) and standard normal variate (SNV). Support vector machine (SNM) model was established by using competitive adaptive reweighed sampling (CARS) and combined synergy interval partial least squares (SiPLS) to select characteristic spectral data. The highest correct recognition rate of the qualitative model is 100%, the mean square error MSE of the quantitative model is 0.0829, and the correlation error R is 99.0772%. The results prove that the support vector machine classification model established by near-infrared spectroscopy combined with chemometrics can qualitatively detect whether sesame oil is adulterated. In the meanwhile, the SNM model can quantitatively predict the content of active components.

Spectroscopic studies of aryl substituted 1-phenyl-2-pyrazolines: Steric and electronic substitution effects

A series of aryl substituted 1-phenyl-2-pyrazolines containing electron-donating and electron-withdrawing substituents on different positions of the C3 or C5-aryl groups were synthesized and their steric and electronic effects on characteristic spectral data were investigated by experimental spectroscopic methods (UV–Vis, IR and NMR) and DFT computations. Whereas the C5-aryl group of the heterocyclic ring behaves as σ-donor/acceptor substituent, the π-donor/acceptor ability of the C3-aryl group depends on the co-planarity of the substituent with the aryl ring and also the extent of the orientation of this C3-aryl ring towards the CN double bond of the heterocyclic ring. A significant through conjugation of the lone pair on the N1-atom towards the C3-aryl ring is observed when the electron-withdrawing nitro group is located on the para-position of this aryl ring. The experimental spectroscopic results for the substitution effects are also supported by (TD)DFT/6-311++G(d,p) computed UV–Vis spectra. Experimental and theoretical NMR chemical shifts and spin-spin coupling constants obtained for these 2-pyrazolines validated by Karplus diagram approves the structures predicted for these compounds.

Identification of multiple constituents in shuganjieyu capsule and rat plasma after oral administration by ultra-performance liquid chromatography coupled with electrospray ionization and ion trap mass spectrometry

Shuganjieyu (SGJY) capsule is a classical formula widely used in Chinese clinical application. In this paper, an ultra-performance liquid chromatography coupled with electrospray ionization and ion trap mass spectrometry has been established to separate and identify the chemical constituents of SGJY and the multiple constituents of SGJY in rats. The chromatographic separation was performed on a C18 RRHD column (150 × 2.1 mm, 1.8 μm), while 0.1% formic acid–water and 0.1% formic acid–acetonitrile was used as mobile phase. Mass spectral data were acquired in both positive and negative modes. On the basis of the characteristic retention time (Rt) and mass spectral data with those of reference standards and relevant references, 73 constituents from the SGJY and 15 ingredients including 10 original constituents and 5 metabolites from the rat plasma after oral administration of SGJY were identified or tentatively characterized. This study provided helpful chemical information for further pharmacology and active mechanism research on SGJY.

Application of Permutation Entropy in Feature Extraction for Near-Infrared Spectroscopy Noninvasive Blood Glucose Detection

Diabetes has been one of the four major diseases threatening human life. Accurate blood glucose detection became an important part in controlling the state of diabetes patients. Excellent linear correlation existed between blood glucose concentration and near-infrared spectral absorption. A new feature extraction method based on permutation entropy is proposed to solve the noise and information redundancy in near-infrared spectral noninvasive blood glucose measurement, which affects the accuracy of the calibration model. With the near-infrared spectral data of glucose solution as the research object, the concepts of approximate entropy, sample entropy, fuzzy entropy, and permutation entropy are introduced. The spectra are then segmented, and the characteristic wave bands with abundant glucose information are selected in terms of permutation entropy, fractal dimension, and mutual information. Finally, the support vector regression and partial least square regression are used to establish the mathematical model between the characteristic spectral data and glucose concentration, and the results are compared with conventional feature extraction methods. Results show that the proposed new method can extract useful information from near-infrared spectra, effectively solve the problem of characteristic wave band extraction, and improve the analytical accuracy of spectral and model stability.

Examination of l-Glutamic Acid Polymorphs by Solid-State Density Functional Theory and Terahertz Spectroscopy.

The ability of l-glutamic acid to crystallize in two different forms has long been the subject of study due to its commercial importance. While a solvent-mediated phase transformation between the α and β polymorphs is the prevailing theory, recent reports indicate a thermal solid-solid transformation between the two may be possible. However, determining accurate thermodynamic stabilities of these crystals has been challenging. Here new low-temperature single-crystal X-ray diffraction data coupled to solid-state density functional theory simulations have enabled a detailed description to be achieved for the energetic parameters governing the stabilization of the two l-glutamic acid solids. The temperature-dependent Gibbs free-energy curves show that α-glutamic acid is the preferred form at low temperatures (<222 K) and the β form is most stable at ambient temperatures. Terahertz time-domain spectroscopy was utilized to evaluate the quality of the intermolecular force modeling as well as to provide characteristic low-frequency spectral data that can be used for quantification of polymorph mixtures or crystal growth monitoring.

Si3C2-Rings: From a Nonconjugated Trisilacyclopentadiene to an Aromatic Trisilacyclopentadienide and Cyclic Disilenide

1,2,3-Trisilacyclopenta-1,4-diene 2, featuring three skeletal Si atoms in the five-membered ring, was synthesized by the thermolysis of the 1,2,3-trisilabicyclo[1.1.0]butane derivative 1 at 130 degrees C in the presence of hex-3-yne. Possessing the properties of nonconjugated cyclopentadiene, 2 readily underwent reduction with KC(8), which was followed by treatment with LiBr to form the lithium salt of 1,2,3-trisilacyclopentadienide 3(-)*[Li(+)(thf)], from which the ketone-coordinated derivative 3(-)*[Li(+)(O=C(t)Bu(2))] was prepared. Both 3(-)*[Li(+)(L)] (L = thf, O=C(t)Bu(2)) are classified as novel 6pi-electron aromatic systems based on their characteristic X-ray crystal and NMR spectral data. Addition of 12-crown-4 to 3(-)*[Li(+)(thf)] resulted in the unexpected formation of 4(-)*[Li(+)(12-crown-4)(2)], featuring the unprecedented cyclic disilenide ion 4(-).

A Web-Based Spectral Database for Environmental Application

The administration and storage of environmental characteristic spectral data are highly relevant in many fields of environmental study, such as measurement of trace gases in the atmosphere and air quality estimation. For this reason, a web-accessible database has been developed, offering ready access to the main parameters of molecular absorption spectral data. Web-based and friendly interfaces allow for interactive queries as well as previews of plots and downloads of files of the resulting spectral data for thorough comparative analyses.

Metallacycle Expansion via butadiyne/octadiyne Insertion into a Four-membered Ruthenium Organometallic

The reaction of 1,4-diphenylbutadiyne and 1,7-octadiyne with Ru(RL1)(PPh3)2(CO)Cl (1) has respectively generated the inserted product [Ru(RL2XY)(PPh3)2(CO)Cl] (X=Ph, Y=-C≡C-Ph), (2) and [Ru(RL2Z)- (PPh3)2(CO)Cl]2(CH2)4 (Z=H), (3) in excellent yield (RL1 is C6H2O-2-CHNHC6H4R(p)-3-Me-5, RL2 is C6H2(C=C-1)-O-2-CHNHC6H4R(p)-3-Me-5 and R is Me, OMe or Cl). In the conversions (1)(2)/(3) the Ru(C,O) chelate ring expands from four-membered to six-membered, and the structure determination of [2(Cl) · H2O] authenticates the insertion process. The (σ-styryl)phenolato chelate ring, along with the benzene ring and the aldimine function (C6H4Cl and Me excluded), constitutes a good plane (mean deviation, 0.06 A). The aryl rings at C9 and N1 make dihedral angles of 77° and 27° respectively with the above plane. Characteristic spectral data (u.v.–vis, i.r. and 1H-n.m.r.) of the complexes are reported. A notable feature is that an allowed band appears near 620 nm due to the t\( _{2{{\rm g}}}\rightarrow \pi^{\ast}\) (azomethine) charge transfer transition which is diagnostic of the coordinated iminium-phenolato function present in (2) and (3). In 1H-n.m.r. the N+–H signals in (2) and (3) (near 12.5 ppm) are split into a doublet due to trans coupling with the azomethine proton. The C=N stretching frequency is relatively high (near 1630 cm−1) and this is consistent with the protonation of nitrogen. In CH2Cl2 solution (2) and (3) display one and two quasireversible RuIII/RuII cyclic voltammetric responses with E1/2 near 0.4 V and 0.4 V, 0.7 V versus s.c.e. due to the presence of one and two RuII centers, respectively. The conversions (1)(2)/(3) are accompanied by the cleavage of the Ru-O bond by MeOH. Then alkyne π-anchoring and activation is believed to occur via displacement of MeOH. Subsequent (2+2) addition between Ru-C and C=C(alkyne), and regeneration of the Ru-O(phenolato) bond, completes the two carbon metallacycle expansions, furnishing (2) and (3).

Structurally characterized acylruthenium organometallics bearing a pendant aldehyde function

By reacting [Ru(RL1)(PPh3)2(CO)Cl], (1) (R = C6H4Me, Et) with an excess of CNBu t in the presence of NH4PF6, organometallics of the type [Ru(RL2)(PPh3)2(CNBu t )2]PF6, (2) have been isolated in excellent yield [RL1 = C6H2O-2-CHNHR(p)-3-Me-5, RL2 = C6H2(CO)-O-2-CHNHR(p)-3-Me-5]. These organometallics, on controlled hydrolysis, produce [Ru(L3)(PPh3)2(CNBu t )2], (3) in very good yield (L3 = C6H2(CO)-O-CHO-3-Me-5). In both ([2(C6H4Me)] · 2H2O) and ([3] · 2CH2Cl2) the two phosphine ligands lie in trans positions. In ([2(C6H4Me)] · 2H2O) the Ru(C6H4MeL2) fragment, excluding the pendant tolyl ring, is a near perfect plane (mean dev ~ 0.02A) which makes a dihedral angle of 5.2° with the tolyl plane. The acyl chelate ring in ([2(C6H4Me)] · 2H2O) is excellently planar with a mean deviation of 0.006°. In ([3] · 2CH2Cl2) the Ru(L3) fragment defines a crystallographic plane of symmetry, the coordinates of the atom being of the type x, 1/4z. The complex ([2C6H4Me)] · 2H2O) displays N–HȮFO (iminium-phenolato) hydrogen bonding while in ([3] · 2CH2Cl2) C–H...O hydrogen bonding is present. Characteristic spectral data (u.v.–vis, i.r. and 1H n.m.r.) of the complexes are reported. A notable feature is that an allowed band near 500 nm due to the t2g → π*(azomethine) charge transfer transition, which is diagnostic of the coordinated iminium-phenolato function, is present in (3) but this band is absent in the aldehydic acyl complex (2). In the 1H n.m.r. spectrum the N+–H signal in (2) (near 13.5 ppm) is split into a doublet due to transcoupling with the azomethine proton. The aldehydic proton of (3) resonates as a sharp singlet near 10 ppm. In CH2Cl2 solution (2) and (3) display quasireversible a Ru III /Ru II cyclic voltammetric response with E1/2 near 0.9 and 0.5 V versuss.c.e. The conversion (2) → (3) is accompanied by the nucleophilic attack of water. The complex (3) is also obtained directly from (1) by reaction with CNBu t in the presence of H2O. The aldehyde function in (3) is deactivated by the existing acyl moiety; as a result further decarbonylation does not take place.