extfieldsofstudy:
Medicine
Materials Science

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Signal Enhancement of Cadmium in Lettuce Using Laser-Induced Breakdown Spectroscopy Combined with Pyrolysis Process

Fast detection of heavy metals in lettuce is significant for food market regulation and the control of heavy metal pollution. Advanced methods like laser-induced breakdown spectroscopy (LIBS) technology have been tried to determine the cadmium (Cd) content. To retard the negative effect of complex matrix composition from samples and improve quantitative performance of LIBS technology, the pyrolysis process combined with LIBS was adopted to determine the cadmium (Cd) content of lettuce. Adaptive iteratively reweighted penalized least squares (airPLS) was used to preprocess the LIBS spectra and solve the baseline drift. For multivariate linear regression based on the three selected Cd emission lines correlation coefficient in the prediction set Rp2 increased from 0.9154 to 0.9969, and the limit of detection (LOD) decreased from 9.1 mg/kg to 0.9 mg/kg after the pyrolysis process. The partial least squares (PLS) regression and support vector regression (SVR) were applied to construct calibration models based on full spectra. In addition, the least absolute shrinkage and selection operator (LASSO) was implemented to choose limited lines to predict the Cd content. The PLS model with the pyrolysis process obtained the best results with Rp2 = 0.9973 and LOD = 0.8 mg/kg. The results indicated that the pyrolysis method could enhance the spectral signal of cadmium and thus significantly improve the analysis results for all the models. It is shown in this experiment that proper sample preprocessing could effectively amplify the Cd signal in LIBS and make LIBS measurement an efficient method to assess Cd contamination in the vegetable industry.

Introduction
With the exponential population growth and rapid development of industrialization, the problem of environmental pollution is getting worse, especially the toxic heavy metal contamination such as mercury, lead, cadmium, zinc, copper, nickel, and chromium [1]. As one of the most toxic heavy metals, cadmium (Cd) is attracting worldwide attention because it is non-biodegradable and widespread in water, soil and the other environment [2]. The accumulation of heavy metal Cd in the environment finally cause adverse effects on human health through the food chain. Heavy metal Cd can cause undesirable effects and severe problems for the human body even at very low concentrations, including cancer, mutation, renal failure and chronic anemia [3][4][5].
Lettuce is a common vegetable which represents the most frequently and worldwide consumed green leaf vegetable [6]. However, it has been found that lettuce which grows in the sludge-treated 25 min and rinsed with sterile distilled water, the seeds were then germinated on a sterile Murashige and Skoog culture medium at 35 • C and 65% relative humidity for five days until the roots grew to approximately 3 cm. Then, the seedlings were transplanted into 10 L full strength Yamazaki's nutrient solution [22], which would be renewed every three days. Growth conditions were adjusted to 27/22 • C (16:8 h light-dark cycle), 65% relative humidity and a light intensity of 200 µmol m −2 s −1 [23]. After nine days, plants with similar growing states were treated with four different cadmium solutions (10,30,60, and 100 µM cadmium prepared by CdCl 2 solution). The concentration of Cd is referenced [24][25][26]. After 30 days' treatment, lettuce leaves were dried at 60 • C for 5 h in an oven, and ground to powder separately. One hundred and fifty milligrams of single lettuce powders were pressed into a square pellet by a tablet pressing machine (FY-24, SCJS, Tianjin, China) with a pressure of 600 MPa for 30 s. Finally, five samples were prepared for each four different Cd concentration groups, and 20 pellets are used for the LIBS analysis.

LIBS Measurements
This experiment used a self-assembled LIBS device [27]. A laser pulse with maximum energy of 200 mJ and 8 ns pulse width were generated at 532 nm by Q-switched Nd: YAG pulse laser (Vlite 200, Beamtech, Beijing, China). A self-made optical system was used to deliver the laser beam to a plano-convex lens (f = 100 mm) which focused the beam on the pellet surface. The laser ablated the sample mass and generated plasma which diffused outward to emit electromagnetic waves. Then the waves were collected by an optical fiber and received by the spectrometer (SR-500i-A-R, Andor Technology, Belfast, UK) combined with an intensified charge coupled device (ICCD) camera (DH334T-18F-03, Andor Technology, Belfast, UK). The spectra between 211.92-232.90 nm with 0.02 nm resolution were collected. To control the delay time between the ICCD camera and laser Q-switch, a delay generator (DG645, Stanford Research Systems, Sunnyvale, CA, USA) was used. We set the optimal experimental parameters before the experiment, with a laser energy of 60 mJ, delay time of 1.5 µs and gate width of 10 µs. Lettuce pellets were placed by an automatic x-y-z positioning system to maintain the laser ablation path with 4 × 4 array craters and each crater had five times accumulation of laser pulses. The distance between locations in the sample is 2 mm. An average of the 80 spectra (4 × 4 × 5) was recorded as the spectrum for each sample to reduce fluctuation. The laser pulse frequency range in this study was 1-10 hz, and 1 hz was used in this study. All samples were measured on the same day. The samples were divided into four groups due to different Cd concentrations, and the samples in each group were marked in random order. The LIBS data was acquired one by one from Group 1 to Group 4.

Pyrolysis Process
After LIBS measurements, the tablets were reground to powder. In order to remove residual water and decompose small organic matters in the sample, the powder would be treated by pyrolysis. The samples were put into the muffle furnace (SX-1000, CEF, Tianjin, China) and were heated at a rate of 5 • C/min. The heating was stopped immediately when the temperature reached 250 • C, which only took 45 min. The weight of all the samples before and after treatment was recorded. The samples were stored in the incubator, where the temperature was controlled at 25 • C and the humidity below 5%. Next day, the samples were pressed into square pellets and were measured by LIBS.
The reference Cd contents of lettuce samples before and after pyrolysis were determined with a flame atomic absorption spectrophotometer (AAS) (AA800, PerkinElmer, Waltham, MA, USA). Sample pretreatment methods before AAS can be found in our previous study [18]. The digested solution obtained after microwave digestion was placed in the AAS inlet for Cd content detection. This step was repeated three times and the AAS data was the average of three injection measurements. The standard material GBW10020 (Beijing, China) and GBW10023 (Beijing, China) were used as a control group to guarantee the analysis quality of AAS. The Cd content of lettuce leaves before pyrolysis and after pyrolysis is shown in Table 1.

Data Analysis
In this experiment, we tried to use the adaptive iteratively reweighted penalized least squares (airPLS) to correct the baseline drift; PLS regression and SVR were also used for Cd content prediction based on the LIBS spectra data.
In the multivariate analysis, the baseline drift always blurs signals and thus deteriorates analytical results. A novel algorithm namedairPLS was used by previous studies [28,29] to solve this problem. This method works by iteratively changing weights of sum squares errors (SSE) between the fitted baseline and original signals, and the weights of the SSE are obtained adaptively using the difference between the previously fitted baseline and the original signals.
In the LIBS spectroscopy, different transition processes can produce light radiation of different wavelengths; the wavelength of light radiation produced by different elements may be similar, which would cause overlap between characteristic peaks and lead to the deviation of prediction. The partial least squares (PLS) was first introduced by the Swedish statistician Herman [30] and is a widely used multivariate analysis method. Particularly, PLS regression is still effective when the variables are highly linearly correlated just like our spectroscopy [31]. Support vector regression (SVR) is one of the regression versions of SVM. SVR projects data to a high-dimensional feature space through a nonlinear mapping and perform linear regression in this space [32]. A loss function of the modified distance is introduced by SVR based on the classification model and the cost function ignores the support vectors which are training data close to the model prediction. In this experiment, the radial basis function (RBF) was utilized as the kernel function. Two parameters of SVR need to be adjusted. One is the regularization parameter (gam), which determines the tradeoff cost between minimizing the training error and minimizing model complexity. The other is the kernel function parameter (sig2), which equals to σ 2 and sigma defines the non-linear mapping from the input space to some high-dimensional feature space [33]. The two parameters were optimized by a grid-search procedure. The parameters with the minimal value of RMSE were chosen and then adopted to build the model.
The least absolute shrinkage and selection operator (LASSO) is a data dimension reduction method that is applicable to linear and nonlinear cases, which was first introduced by Robert [34]. LASSO select the variables of the sample data based on the penalty method, the original small coefficients are directly compressed to zero and discarded as non-significant variables.
In order to compare with the above algorithms, three Cd emission lines were selected and the multivariate linear regression was performed to predict the Cd content.

Performance Evaluation
The effect of the pyrolysis process was assessed by the relative standard deviation (RSD), signal-to-noise ratio (SNR) and signal-to-background ratio (SBR). RSD is the ratio of the standard deviation to the mean. SNR is defined as the ratio of signal power to the noise power and SBR is the ratio of signal power to the background power. By these standards, the enhancement of pyrolysis to the LIBS signal could be analyzed.
To measure the performance of the above quantitative models for the Cd content detection, the root mean square error of cross validation (RMSECV) and root mean square error of prediction (RMSEP) were used. The RMSE evaluates the deviation between the predicted and the referred content. The limit of detection (LOD) was used to evaluate the sensitivity of PLS models. The calculation method of LOD can refer to our previous research [18]. The correlation coefficient (R 2 ) was also calculated which stands for the correlation between the element content of the models predicted and the reference Cd content. R c 2 and R p 2 are correlation coefficients of the calibration set and prediction set respectively, showing the accuracy of calibration and prediction models. Figure 1 shows the average raw LIBS spectra of the four different Cd-stress group lettuces before and after pyrolysis (Figure 1a,b), and the spectra preprocessed by the airPLS method (Figure 1c were observed in all Cd stress lettuce sample. As shown in Figure 1a,c, the baseline shifts occur in the LIBS spectra due to the random errors caused by the environment and instrument. Compared to Figure 1a, the baseline has been adjusted by the airPLS method in Figure 1c, which indicates that the data preprocessing is useful to decrease the random errors. As shown in Figure 1a,b, the pyrolysis of the sample makes huge contributions to correcting the baselines and enhancing the Cd peak signal in the spectral lines. That was because the pyrolysis process improved the properties of the sample and reduces the matrix effect.

Performance Evaluation
The effect of the pyrolysis process was assessed by the relative standard deviation (RSD), signal-to-noise ratio (SNR) and signal-to-background ratio (SBR). RSD is the ratio of the standard deviation to the mean. SNR is defined as the ratio of signal power to the noise power and SBR is the ratio of signal power to the background power. By these standards, the enhancement of pyrolysis to the LIBS signal could be analyzed.
To measure the performance of the above quantitative models for the Cd content detection, the root mean square error of cross validation (RMSECV) and root mean square error of prediction (RMSEP) were used. The RMSE evaluates the deviation between the predicted and the referred content. The limit of detection (LOD) was used to evaluate the sensitivity of PLS models. The calculation method of LOD can refer to our previous research [18]. The correlation coefficient (R 2 ) was also calculated which stands for the correlation between the element content of the models predicted and the reference Cd content. Rc 2 and Rp 2 are correlation coefficients of the calibration set and prediction set respectively, showing the accuracy of calibration and prediction models. Figure 1 shows the average raw LIBS spectra of the four different Cd-stress group lettuces before and after pyrolysis (Figure 1a,b), and the spectra preprocessed by the airPLS method ( Figure  1c Figure 1a,c, the baseline shifts occur in the LIBS spectra due to the random errors caused by the environment and instrument. Compared to Figure 1a, the baseline has been adjusted by the airPLS method in Figure 1c, which indicates that the data preprocessing is useful to decrease the random errors. As shown in Figure 1a and 1b, the pyrolysis of the sample makes huge contributions to correcting the baselines and enhancing the Cd peak signal in the spectral lines. That was because the pyrolysis process improved the properties of the sample and reduces the matrix effect.    Figure 2 shows the details of three Cd spectral peaks from different groups in Figure 1d. After the pyrolysis of the sample and the preprocess of the airPLS method, the height of the Cd II 226.50 nm spectral peak is higher than the Cd II 214.44 nm peak and Cd I 228.80 nm. The Cd spectral peak of the different groups is related to the Cd content, the higher Cd content groups have higher Cd peaks.

Spectra Analysis
Molecules 2019, 24, 2517 6 of 13 Figure 2 shows the details of three Cd spectral peaks from different groups in Figure 1d. After the pyrolysis of the sample and the preprocess of the airPLS method, the height of the Cd Ⅱ 226.50 nm spectral peak is higher than the Cd Ⅱ 214.44 nm peak and Cd Ⅰ 228.80 nm. The Cd spectral peak of the different groups is related to the Cd content, the higher Cd content groups have higher Cd peaks.  Figure 3 shows the three performance evaluation indexes including RSD, SBR and SNR of the four different Cd-stress group lettuces based on three Cd emission lines. The RSD of three Cd emission lines before and after pyrolysis are shown in Figure 3a,b, the SBR of three Cd emission lines before and after pyrolysis are shown in Figure 3c,d, the SNR of three Cd emission lines before and after pyrolysis are shown in Figure 3e,f. From Figure 3a,b, we found that the RSD of three Cd emission lines decreases in all four different Cd concentration groups after the process of pyrolysis, which indicates that the accuracy has been improved since the pyrolysis process is conducive to eliminate the matrix effect and reduce the random error. From Figure 3c Figure 3 shows the three performance evaluation indexes including RSD, SBR and SNR of the four different Cd-stress group lettuces based on three Cd emission lines. The RSD of three Cd emission lines before and after pyrolysis are shown in Figure 3a,b, the SBR of three Cd emission lines before and after pyrolysis are shown in Figure 3c,d, the SNR of three Cd emission lines before and after pyrolysis are shown in Figure 3e,f. From Figure 3a,b, we found that the RSD of three Cd emission lines decreases in all four different Cd concentration groups after the process of pyrolysis, which indicates that the accuracy has been improved since the pyrolysis process is conducive to eliminate the matrix effect and reduce the random error. From Figure 3c  . LIBS spectra. The relative standard deviation (RSD) of three Cd emission lines before pyrolysis (a) and after pyrolysis (b); the signal-to-background ratio (SBR) of three Cd emission lines before pyrolysis (c) and after pyrolysis (d); the signal-to-noise ratio (SNR) of three Cd emission lines before pyrolysis (e) and after pyrolysis (f). There are five samples in each group.

Multivariate Analysis
As an effective calibration method, the multivariate analysis is used to evaluate the Cd content of lettuce samples with multiple variables after the pretreatment of the LIBS spectra. Before the quantitative analysis, 20 samples were partitioned into a calibration set (13 samples) and a prediction set (7 samples). Selected variables and the full spectra were both applied to establish the models by using the partial least squares (PLS) regression and support vector regression (SVR) method. Figure 3. LIBS spectra. The relative standard deviation (RSD) of three Cd emission lines before pyrolysis (a) and after pyrolysis (b); the signal-to-background ratio (SBR) of three Cd emission lines before pyrolysis (c) and after pyrolysis (d); the signal-to-noise ratio (SNR) of three Cd emission lines before pyrolysis (e) and after pyrolysis (f). There are five samples in each group.

Multivariate Analysis
As an effective calibration method, the multivariate analysis is used to evaluate the Cd content of lettuce samples with multiple variables after the pretreatment of the LIBS spectra. Before the quantitative analysis, 20 samples were partitioned into a calibration set (13 samples) and a prediction set (7 samples). Selected variables and the full spectra were both applied to establish the models by using the partial least squares (PLS) regression and support vector regression (SVR) method.

Modeling Based on Three Cd Emission Lines
The three Cd emission lines Cd II 214.44 nm, Cd II 226.50 nm and Cd I 228.80 nm were selected as the input variables to establish the multiple regression model. The results of the multiple regression model based on the three Cd emission line variables are shown in Table 2. As Table 2 shows, the model performs poorly with the R c 2 value lower than 0.94 and R p 2 value lower than 0.84 before the pyrolysis, which is mainly due to the loss of some background information and matrix information contained by other variables. After the preprocess of the raw data, the model improves a lot with the R c 2 value of 0.9459 and R p 2 value of 0.9154. However, the accuracy of the Cd content concentration still needs to be improved. After the pyrolysis of the sample and acquired new LIBS data, the model preforms better than before with the R c 2 value of 0.9907 and R p 2 value of 0.9746 both in the calibration set and prediction set.
Moreover, the preprocess of the data also achieves good performance especially in the prediction set. Therefore, the best model is based on the data after pyrolysis and preprocess, where the R c 2 and R p 2 are higher than 0.9915. After the pyrolysis treatment, the LODs were greatly reduced. This was because the pyrolysis treatment simplified the sample matrix composition, the background near the Cd signal decreased, and the SBR was higher. This indicates that the method of pyrolysis and preprocess methods are quite acceptable to the multiple regression model based on three Cd variables. The multivariate analysis based on the above model is conducive to develop the portable instrument and improve its performance for rapid detection of heavy metal Cd in the management of the lettuce market.

Modeling Using Full Spectra
Compared to the model based on the three Cd emission lines, the model based on the full spectra obviously has a better performance on the Cd content concentration prediction because the full LIBS spectra contained all emission lines for elements and continuous background information. The range of the full spectra is from 211.92 nm to 232.90 nm with 1024 variables. The results of the multivariate analysis using the full spectra based on PLS and SVR models are shown in Table 3. As Table 3 shows, the PLS and SVR models based on the data acquired after the sample pyrolysis process achieve better performance than the models based on the un-pyrolysis data.
For the PLS model, the multivariate analysis based on the full spectra obtained poor performance with the R c 2 value lower than 0.95 and R p 2 value lower than 0.93 before the pyrolysis process. After applying the preprocessing algorithm, the PLS model performed better with the R p 2 value higher than 0.96 while the R c 2 value was lower than before. After the pyrolysis of the sample, the PLS model improves the performance with the R c 2 value of 0.9973, RMSECV of 12.2 mg/kg in the calibration set, and R p 2 value of 0.9973, RMSEP of 13.3 mg/kg in the prediction set. However, the preprocessing of data seems to achieve quite a little improvement on the PLS model after the pyrolysis. For the SVR model based on the un-pyrolysis data with full spectra variables, the performance of the Cd content prediction is better than the PLS model with the R c 2 value of 0.9887 and R p 2 value of 0.9553. After the pyrolysis of the sample, the performance of the SVR model improved a lot especially the R p 2 value of 0.9922 and RMSEP of 21.9 mg/kg in the prediction set, which indicates that the pyrolysis improves the property of the sample and reduces the matrix effects. However, the SVR model based on the preprocessing of the raw data achieves negative impact on the Cd content prediction, which seems that this preprocessing method may not be suitable for this model. The SVR model after pyrolysis and preprocessing seems overfitting in the calibration set, thus the R c 2 value is as high as 1 and the R p 2 value is quite low as 0.9693.
Overall, the PLS and SVR model for the multivariable analysis based on the data after pyrolysis both achieve a good performance due to the elimination of the matrix effect. The full spectra provide a useful multi-variable which contains all the background and matrix information, and the method of pyrolysis make it possible to improve the properties of the sample and enhance the Cd signal in the LIBS spectra. However, the preprocessing algorithm of airPLS has no improvement for the above model. Therefore, the multivariable analysis based on the raw LIBS data after the pyrolysis is more suitable for accurate detection of the Cd content in lettuce leaves for laboratory research and food market regulation. Figure 4 shows the PLS and SVR model without the preprocessing method.
According to the National Standards GB 2762-2017 in China, the maximum permitted concentration of Cd in vegetable leaves is 0.2mg/kg. For the multiple regression analysis based on the three Cd emission lines, LODs before pyrolysis is 12.1 mg/kg for raw spectra and 9.1 mg/kg for airPLS preprocessed spectra. LODs after pyrolysis is 1.1 mg/kg for raw spectra and 0.9 mg/kg for airPLS preprocessed spectra. For the multiple regression analysis based on full spectra, LOD of the PLS model after PLS is 0.8 mg/kg. Optimal results obtained by our previous lettuce Cd content based on the LIBS approach was LOD = 1.672 mg/kg [18]. The detection capability is inferior to the combination of LIBS and pyrolysis. Although the LODs of the combination of LIBS and pyrolysis did not meet the GB2762-2017, the pyrolysis greatly reduced the LODs, and the subsequent combination of other signal enhancement methods in further will be attempted to reduce the LODs to approach the GB requirement.
of pyrolysis make it possible to improve the properties of the sample and enhance the Cd signal in the LIBS spectra. However, the preprocessing algorithm of airPLS has no improvement for the above model. Therefore, the multivariable analysis based on the raw LIBS data after the pyrolysis is more suitable for accurate detection of the Cd content in lettuce leaves for laboratory research and food market regulation. Figure 4 shows the PLS and SVR model without the preprocessing method.

Selecting Variables Using LASSO
As shown above, Cd has limited emission lines and the majority of the full spectra are not sensitive to the Cd content. In addition, providing too much variables will easily lead to the model overfitting. Therefore, it is important to select a subset of the provided full spectra to create the model rather than using all of them. To this end, the penalty method and LASSO model are introduced.
LASSO will effectively choose a simpler model by forcing certain coefficients of some variables to be set to zero and remained variables are selected to construct the model. The alpha parameter of the LASSO model was determined by the cross validation of the calibration set. The selected lines and results of the LASSO model are shown in Table 4.  Figure 5.
Molecules 2019, 24, 2517 11 of 13 Figure 5. Least absolute shrinkage and selection operator (LASSO) coefficient. The coefficient of full spectra before pyrolysis without preprocess (a) and with preprocess (b); the coefficient of full spectra after pyrolysis without preprocess (c) and with preprocess (d).

Conclusions
In this experiment, we improved the performance of the model by enhancing the heavy metal Cd signal in the laser-induced breakdown spectroscopy combined with pyrolysis process. Compared with chemometric methods with or without pyrolysis process, we achieved the rapid and accurate quantitative analysis for the Cd content in lettuce samples. A total of 20 sample solid pellets with Cd stress were prepared after the pyrolysis of lettuce powder. For the multivariable analysis, the multiple regression model based on the three Cd emission lines, the PLS and SVR model based on the full spectra all accomplish improvement compared to the data acquired from the un-pyrolysis sample. A total of three Cd emission lines Cd II 214.44 nm, Cd II 226.50 nm, and Cd I 228.80 nm were selected as three input variables to establish the multiple regression model, the one after the pyrolysis of the sample and preprocess of the raw data preformed best with the Rc 2 value of 0.9915 and Rp 2 value of 0.9969. For the PLS and SVR model based on the full spectra after the pyrolysis, the improvement created by the airPLS preprocessing method can be ignored. The PLS model without the preprocess achieved better performance with the Rc 2 and Rp 2 value of 0.9973, RMSECV of 12.2 mg/kg and RMSEP of 13.3 mg/kg, and the SVR model without the preprocess achieved better performance with the Rc 2 value of 0.9995, RMSECV of 5.5 mg/kg, Rp 2 value of 0.9922 and RMSEP of 21.9 mg/kg. Therefore, the PLS model based on the full spectra has better performance than the multiple regression model based on three Cd emission lines in both the calibration set and prediction set for Cd content prediction. For the LASSO model based on selected variables, the performance of the LASSO model improved significantly after the pyrolysis of the sample with the Figure 5. Least absolute shrinkage and selection operator (LASSO) coefficient. The coefficient of full spectra before pyrolysis without preprocess (a) and with preprocess (b); the coefficient of full spectra after pyrolysis without preprocess (c) and with preprocess (d).

Conclusions
In this experiment, we improved the performance of the model by enhancing the heavy metal Cd signal in the laser-induced breakdown spectroscopy combined with pyrolysis process. Compared with chemometric methods with or without pyrolysis process, we achieved the rapid and accurate quantitative analysis for the Cd content in lettuce samples. A total of 20 sample solid pellets with Cd stress were prepared after the pyrolysis of lettuce powder. For the multivariable analysis, the multiple regression model based on the three Cd emission lines, the PLS and SVR model based on the full spectra all accomplish improvement compared to the data acquired from the un-pyrolysis sample. A total of three Cd emission lines Cd II 214.44 nm, Cd II 226.50 nm, and Cd I 228.80 nm were selected as three input variables to establish the multiple regression model, the one after the pyrolysis of the sample and preprocess of the raw data preformed best with the R c 2 value of 0.9915 and R p 2 value of 0.9969. For the PLS and SVR model based on the full spectra after the pyrolysis, the improvement created by the airPLS preprocessing method can be ignored. The PLS model without the preprocess achieved better performance with the R c 2 and R p 2 value of 0.9973, RMSECV of 12.2 mg/kg and RMSEP of 13.3 mg/kg, and the SVR model without the preprocess achieved better performance with the R c 2 value of 0.9995, RMSECV of 5.5 mg/kg, R p 2 value of 0.9922 and RMSEP of 21.9 mg/kg. Therefore, the PLS model based on the full spectra has better performance than the multiple regression model based on three Cd emission lines in both the calibration set and prediction set for Cd content prediction. For the LASSO model based on selected variables, the performance of the LASSO model improved significantly after the pyrolysis of the sample with the R p 2 value of 0.9924 in the prediction set. Compared to the PLS and SVR model, the LASSO model achieved nearly the same accuracy but used less variables.


provenance: AgriculturalAndFoodSciences,2019-2020-Agricultural And Food Sciences-2019.jsonl.gz.gz

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Response surface modeling and optimizing conditions for anthocyanins extraction from Hibiscussabdariffa L. (Roselle) grown in Lam Dong, Vietnam

Hibiscus sabdariffa L. (Hs, roselle; Malvaceae) is a common ingredient used in the food and pharmaceutical industries for color and health benefits. Anthocyanins along with protocatechuic acid and quercetin have been recognized as bioactive compounds in Hibiscussabdariffa L. aqueous extracts. In this work, Response Surface Methodology was implemented together with Box-Behnken experimental design to investigate the impacts of process variables on anthocyanin extraction yields from Hibiscus sabdariffa L. (Roselle) grown in Lam Dong, Vietnam. The effects of three independent variables; namely the extraction temperatures of solvent ethanol (X1); the duration of extraction (X2); solid-liquid ratios (X3) on the total anthocyanins content (Y1) were explored. The optimization model showed that with the solid liquid ratio 7.7:1, extraction time 33.29 min, and temperature 56.9°C, the highest anthocyanin concentration of 186.006 mg/L was obtained. Hibiscussabdariffa L. anthocyanin yield detailed significant correlation with high F values, low P values (<0.0001), and desirable determination coefficient (R2 = 0.9770). The resulting quadratic model could be used to predict yields with given conditions. Actual experimental verification and residual testing revealed that the actual anthocyanin yields could be accurately predicted by the model.

Introduction
Hibiscus sabdariffa L., commonly known as roselle or red sorrel, is one of the most commonly cultivated plants globally. The plant has tropical origin and belongs to the Malvaceae family. The plant is a common ingredient in traditional medicine and extracts from the plant has been shown to exhibit a wide spectrum of therapeutic effects regarding various diseases such as cardiovascular disease, liver disease, fever and hypertension [1][2][3]. In addition, due to its colour and unique flavor, Hibiscus sabdariffa L. are utilizable in culinary as a cooking ingredient and colorant. A prominent feature of the Hibiscus sabdariffa L extract is its high content of antioxidants where anthocyanins are major components. Anthocyanins are water-soluble glycosides and acylglycosides of anthocyanidins, and they are found in the form of polyhydroxylated and or methoxylated heterosides which derive from the flavylium ion or 2-phenylbenzopyrilium in nature. Anthocyanins are compounds of interest because they are suitable replacements for chemical dyes. The compounds is characterized polyphenolic family, commonly existing in the plant kingdom [4][5][6]. However, a suitable extraction technique is important to maintain the antioxidant activity of the extract from the plant and to obtain the highest yield of anthocyanins. Although parameters including solvent acidity, solid-to-solvent ratio, time or temperature of extraction were individually studied in different studies, a study which include all important parameters is lacking in the literature. The aforementioned issue could be addressed by a technique that accommodates variables in an interactive manner. Optimization, in most cases, is performed with response surface methodology (RSM). The technique is a powerful and widely used technique devised for testing of multiple-process variables and optimizing experimental responses. The advantage of the technique is numerous ranging from simplicity to high efficiency and consistency with comprehensive theories. In addition, it also allows fewer experimental trials in comparison with studies of one variable at a time and is applicable in various fields, including construction field [7][8][9][10][11][12][13][14][15]. In order to achieve the above purpose, RSM combined with Box-Behnken design was employed in this study to identify the set of conditions which yields the highest anthocyanin yields from Hibiscus sabdariffa L. (Roselle) grown in Lam Dong, Vietnam. Following parameters were optimized: solid-liquid ratios, extraction temperatures and duration of extraction. The established model will serve as reasonable relationship between the independent variables and the response.

Material and methods 2.1. Sample preparation
Hibiscus sabdariffa L. dried calyces were used, provided by farmers of Da Lat city, Lam Dong Province, Viet Nam. Dried petals of roselle were ground using a commercial grinder and were weighed to 10g, put in the two neck round bottom flask and was extracted by Ethanol 50 o solutions. Ethanol (C 2 H 5 OH) is purchased from Sigma Aldrich (US). The different particle diameter ground samples were stored in polyethylene vacuum bags at room temperature until extraction was carried out. First of all, each experimental condition will be tested individually to determine the optimum condition. For extraction parameter study, 10g of roselle powder was placed in the two neck round bottom flask as and was extracted by ethanol with concentration at 50. The liquid/solid ratio in this experiment ranges from 2:1 to 10:1 (mL/g) and. The extraction temperature is adjusted from 40 to 80 ( o C) and time varies from 15 to 35 (min). Then, centrifugation took place at 4500 rpm for 15 min by high speed centrifuge Model LACE16 (from COLO lab expert). The supernatant was collected and the extract, after being filtered with filter paper, was transferred into plastic bottle to estimate anthocyanin content. The pH scanning of supernatant ranges from λvis max to 700 nm were recognized for anthocyanin content. The total anthocyanin content was determined by using the pH-differential method [16] 2.2. Experimental design using RSM Following the estimation of the statistical model, analysis of variance (ANOVA) was performed to evaluate the significance of the experimental variables of consideration. These variables include solid/liquid ratio (X 1 ), extraction temperature (X 2 ), and time extraction (X 3 ). The whole optimization process was administered in the Design Expert 7.0 software.Based on the results obtained from the single factor investigation, 3-level factors (Table 1) were produced and attempted in actual  (Table 2) for estimating the second order polynomial model, which is described as follows: ,where, Y is a response variable, β 0 , β i , β ii and β ij are the regression coefficients of the intercept, linear, quadratic and interaction terms, respectively. x i and x j are coded values of independent variables affecting the response of Y.  Table 2. To be specific, variables of interest include concentration of ethanol 50%, liquid/solid ratio ranged from 4:1 to 6:1 (mL/g), temperature ranged from 60 to 70 o C and reaction time ranged from 35-45 (min). No.1~14 were the factorial experiments, and No.15~20 were the central experiments. The resulting anthocyanin content ranges from 163.86 mg/L to 186.77 mg/L. The results indicated that all factors showed statistical significance, solid/liquid ratio at the p ≤ 0.05 level and both temperature and time at a ≤ 0.01 level. Additionally, there was a high statisticalsignificance (p ≤ 0.01) in the interaction between solid/liquid, temperature and time; This occurs when one of the independent variables exerts an effect on another of the independent factors of the experimental design. The results implied that the anthocyanin content would be severely altered as survey parameters change (ratio, temperature, time). The difference between actual values and predicted values was not substantial indicating that the results of the experimental experiments have high accuracy. As indicated by Table 3, determination coefficient R 2 = 0.9770 shows a high goodness-of-fit of the predicted values to the real data. Overall, the model is significant as demonstrated by the F-value of 47.18. The probability of the model to obtain such value owing to noise is minimal (0.79%). All model terms are also statistically significant as indicated by low p-values. Insignificance of the lack of fit shows that the model fits well with the data, thus no further specification of the model is required. After estimating model coefficients, the following model is obtained: Y = 186.6 -2.82X 1 -1.31X 2 + 1.36X 3 -1.37X 1 X 2 -2.57X 2 X 3 -2.16X 1 X 3 -5.01X 1 2 -3.00X 2 2 -3.89X 3 2 (3) The predictive model calculation (second order polynomial equation model) leads to the optimal theoretical calculation of extraction in order to achieve the maximum value of 187.006 mg/L anthocyanin content, using 50% EtOH, at 56.9 °C, and 7.7:1 (mL/g) solid/liquid ratio.  Table 3 ANOVA data for removal models

Analysis of response surface
The coinciding relationship of various variables and the response could be described by the surface plot. Based on the model estimated by the software, three response surface plots of the anthocyanin content, corresponding to different combinations of the solid-liquid ratios (X 1 ), extraction temperatures (X 2 ) and duration of extraction (X 3 ) were plotted as in Fig.1. The contour plots represented impact intensity of the interaction variables on the content. According to the model results, all three interaction terms representing combinations of three factors are significant (P<0.05). From the response surface analysis, optimum process of anthocyanin extraction are identified with the following parameters: temperature 56.9 ( o C), time 33.29 (min), and liquid-solid ratio 7.7:1 (mL/g). The maximum predicted anthocyanin content was 187.006 mg/L.

Figure1
. 3D model about the influence and interaction of Y with (a) the solid-liquid ratios (X 1 ) and extraction temperatures (X 2 ); (b) the solid-liquid ratios (X 1 ) and duration of extraction (X 3 ); (c) extraction temperatures (X 2 ) and duration of extraction (X 3 )

Testing the Model Precision
The yield of anthocyanin extraction could be predicted using the above model. To validate the model, residuals of 20 runs and yields of oil were plotted in the Figure 2. A normal plot of residuals was generated ( Figure 2) and it can be observed that most data points are grouped reasonably near to, and

. Conclusion
In this work, a RSM procedure was applied to study the effect of three variables (solid-liquid ratios, extraction temperatures, duration of extraction) on anthocyanin extraction yield from Vietnamese Hibiscus sabdariffa L. (Roselle). The 20experiments wasplanned by CCD to generate the data for estimation of the model. The best combination of factors yielding the highest anthocyanin content (187.006 mg/L) was as follows: 33.29 (min), 56.9 ( o C) temperature and 7.7:1 (mL/g) solid/liquid ratio. The ANOVA results indicated that the solid-liquid ratios (X 1 ), extraction temperatures (X 2 ) and duration of extraction (X 3 ) had significant effects on the responses. The obtained results suggested that RSM is a reasonable tool for optimization not only for extraction processes, but also for other applications involving multiple experimental conditions.


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Biodegradation by composting of municipal organic solid waste into organic fertilizer using the black soldier fly (Hermetia illucens) (Diptera: Stratiomyidae) larvae

The objectives of this study were to assess the black soldier fly larvae (BSFL) composting potential and to analyse the quality of organic fertilizer produced for agricultural purposes. The waste biodegradation was determined by varying waste feed treatment (2, 2.5, 3.0, 3.5, to 4 kg) and control treatment of (2 kg) of heterogeneous mixture of municipal organic solid waste from market, restaurant and households. Each of the setups received equal number of viable larvae (i.e. 2000) which were 5–6 days old. To analyse the nutrient concentration of the compost residues with BSFL, the substrate and final compost were evaluated based on the levels of NPK as well as the C:N ratio. To evaluate the toxic levels of the final compost in terms of heavy metals, the presence and levels of As, Cd, Fe, Pb and Ni were investigated. The analysis showed that there was high percentage increase of nitrogen, phosphorus and potassium levels, i.e. 41.2% (SD ± 0.71%), 32.4% (SE ± 0.2%) and 77.1% (SE ± 0.19%), respectively. It was found that the larvae degraded more than half of the total substrate within 2 weeks. The study showed a decrease in heavy metal concentrations after larvae composting. The study revealed that the concentration of NPK increased significantly among the treatment groups. The study further revealed that some of the heavy metals under investigation had reduced to an acceptable level according to the standards of both local and international regulatory bodies.

Introduction
Municipal solid waste management is an issue of great concern to especially urban governance because of solid waste effects on the environmental health most especially in the developing countries (UN-HABITAT 2010). This is due to inadequate infrastructure and technical inefficiencies. The impact on poor environmental sanitation and solid waste in the cities and towns could threaten nation's development (Sarkar and Chourasia 2017). In the year 2016, about 50% of the world population lived in cities and generate more than 3 million metric tons of waste (including, household items, food waste, and packaging) on a daily basis. By the year 2025, this number will double (Hoornweg and Bhada-Tata 2012).
A report by FAO estimated that 1.6 billion tons of food waste were generated worldwide in 2007 and that accounted for about one-third of the global food production. This waste occurred at all stages from production to consumption. In addition, improper disposal of solid waste takes up space in landfills. This eventually contributes to the spread of disease, and the production of noxious odour (Hoornweg and Bhada-Tata 2012). It is also reported that food waste is the number three contributor of global carbon dioxide production and produces more than double the carbon dioxide produced by all ground transportation in the United States of America.
In the year 2012, globally, solid waste management costs approximately $205.4 billion and it is expected to increase to about $375.5 billion in 2025 (Hoornweg and Bhada-Tata 1 3 2012). In the cities and towns, uncollected solid waste contributes to flooding, air pollutions, and public health impact such as respiratory ailment, diarrhoea, and dengue fever (Barry 2004).
There are several naturally occurring microorganisms that can convert organic waste into valuable resources such as nitrogen, phosphorus and potassium which are useful to plants. A typical example is the use of worms to degrade waste.
Vermicomposting is an aerobic process of organic waste degradation and stabilization by interaction of microorganisms and earthworms under controlled conditions (Dominguez and Edwards 2011).Vermicomposting is not known to be a widespread approach to urban waste management in low-and middle-income countries (Diener et al. 2011). The expected barriers to vermicomposting are the large space requirement, poor supporting policies and measures from government and low revenue to sustain its operation (Mainoo 2007;Dominguez and Edwards 2011).
For several years, researchers globally have proposed using the larvae of black soldier fly (Hermetia illucens) (Diptera: Stratiomyidae) as a potential means to degrade organic matter such as food waste to divert the materials away from the limited landfills (Diener et al. 2011;Gabler and Vinnerås 2014). The black soldier fly (BSF) is a wasplike fly distributed over the tropical and temperate regions of the world (Sarpong et al. 2018). The insect is native to America but through human-mediated dispersal, now they are found almost all over the world (Rana 2014;Tomberlin et al. 2002;Sarpong et al. 2018).
The uniqueness of the insect, black soldier fly, is their ability to successfully colonize a wide variety of resources ranging from swine manure (Alvarez 2012), animal remains (Wang and Shelomi 2017). It has been reported that the BSF larvae are capable of degrading human faeces (Lalander et al. 2013;Banks et al. 2014) and animal faeces (Charlton et al. 2015). Past researchers have established that many insects could be selective with regard to what and how much waste they can consume (Cammack and Tomberlin 2017).
The aforementioned studies used either homogeneous agricultural, livestock manure or human faeces and vegetable waste as feedstock. Black soldier fly larvae application to treat unshredded feeding sources of municipal organic solid waste is yet to be fully understood and proven. In addition, limited literature exists on the use of black soldier fly larva's ability to remove heavy metals from heterogeneous organic fraction of municipal organic solid waste (OFMSW) to be considered as safe organic compost.
Once these facts are well established, organic waste from municipalities could be manipulated to optimize waste reduction and composting materials into valuable products. In view of the above, the objectives of the study are to (1) investigate the decomposition efficiency of the black soldier fly larvae on heterogeneous mixture of municipal organic solid waste, (2) assess the larvae compost maturity and (3) analyse the heavy metal removal of the compost for agricultural purposes.

Study site
The research study site was located in the campus of the Kwame Nkrumah University of Science and Technology (Civil Engineering Department) in Kumasi, Ghana. The experiment was carried out under a constructed shelter (45 × 10 m) roof of corrugated metal sheet and enclosed by mosquito nets.

Black soldier fly colony
A population of black soldier fly (Hermetia illucens) (Diptera: Stratiomyidae) was attracted from the natural ecosystem and kept in five different cages of size (60 × 60 × 45 cm each), covered with transparent mosquito nylon net. The cages were placed on top of a table (0.5 m height), exposed daily to direct sunlight for approximately 12 h. In the cages, transparent plastic bows (10 L) containing organic waste were used to attract the BSF females for oviposition.
A pre-feed placed inside a plastic bowl was covered with perforated black polytene to prevent direct exposure to sunlight and loss of excessive moisture. The hatched eggs remained in the pre-feed for 4 days. The young larvae (4-6 days old) were collected and counted manually at 2-day interval for a week. The hatched larvae were kept in a container, with wetted restaurant waste as pre-feedstock under the prevailing temperature of 25.5-26.8 °C and relative humidity at 60-85%. To supply the colony of new adult, 300 adult black soldier flies were attracted to the system and the same procedure was followed as described above.

Experimental setup
The larvae composting experiments were conducted in plastic containers (41 × 69 cm; Ø × h) (75 L capacity) (Fig. 1). A drain tap was fixed at the bottom side (2 cm height) of the container. The top lid of the containers was perforated (hole dia. 10 mm) to improve aeration in the system. No ramp was provided to prevent the escape of the prepupae, so that they remain in the residue. To avoid invasion of predators such as ants, reptiles and birds, the containers were mounted on top of a table, made of wood at a height of 0.5 m. To avoid other insects from breeding, each plastic container (biodigester) was covered thoroughly with mosquito nets, prior to covering them with lids.
Municipal organic solid wastes from domestic, markets and restaurant in the towns near the University were used for the experiments. A bucket full of unshredded organic wastes weighing about 30 kg was collected daily. They were mixed thoroughly using ordinary ladle to attain certain homogeneity and then added to the designed containers (75 L) with varying amount of organic waste ranging from 2, 2.5, 3, 3.5 and 4 kg. The feeding rates (FR) 71 mg/larvae/ day, 89 mg/larvae/day, 107 mg/larvae/day, 125 mg/larvae/ day to 143 mg/larvae/day and a control (2 kg), which is represented as T-1, T-2, T-3, T-4, T-5 and T-c, respectively, were established. The feeding rate (FR) was expressed as the total amount of organic waste given to 2000 number of larvae over a period of 14 days, taking into account the life cycle of the black soldier fly. In addition to the substrate in the containers, each of the five experimental containers was inoculated with 2000 5-day-old larvae and each larvae weighed approximately 0.03 mg. The 6th container received 2 kg of homogenate without larvae (natural compost without larvae) and it served as a control for the analysis.
To ensure a coequal establishment of the larvae population, all the five experimental setups and the control (degradation without larvae) were fed at once (i.e. batch system). In total, 15 kg of fresh and untreated organic solid waste was given to 10,000 larvae. The system was monitored continuously for a period of 14 days according to the life cycle of the BSF. At the starting phase, fresh food wastes were placed at the bottom and then the larvae were placed on top of the waste materials. The feeding rates were maintained for repeated experiment, five times over a period of 108 weeks. Samples of organic solid waste and residue were collected for further analysis on total organic carbon (TOC), total nitrogen (TN), total phosphorus (TP), and total potassium (TK).
The nitrogen contents were investigated utilizing the Kjeldahl method as clarified in the Swedish Standard, SS-EN 13342. The phosphorus contents were investigated utilizing the ISO 11466 (Soil quality-Extraction of trace solvent in water regia). The potassium contents were broken down utilizing ICP-AES spectrophotometry and a mix of ISO 11466 (Soil quality-Extraction of trace elements dissolvable in water regia). Heavy metals (As, Ni, Cd, Pb, Fe) were also analysed. The temperature, pH and moisture contents of the substrate were also investigated. Trace elements and phosphorus were determined using water regia extraction strategy and AES spectrophotometry. The TOC was determined by total organic carbon analyser.
Due to limited funding, the scope of the research did not consider the final utilization of the prepupae for agricultural purposes. The aquaculture and agronomical aspects of the end product would be of great interest and it would be considered in the near future.

Statistical analysis
Linear regression and one-way analysis of variance (ANOVA) with subsequent Tukey HSD test were conducted to establish relations and difference between the various treatments (P < 0.05). An increase in nutrient concentration of the treatment groups was calculated according to the formula (residue − substrate)/substrate.

Physiochemical characteristics of the substrate and compost
The temperature of the substrate ranges from 26.0 to 26.7 °C with a mean value of 26.4 °C. The lowest temperature of the residue ranges from 24.2 to 24.7 °C, with mean value of 24.5 °C, while the highest temperature ranges from 26.3 to 26.7 °C with mean value of 26.5 °C. The results also showed a temperature range from 25.7 to 25.8 °C, with a mean value of 25.8 °C for the control (Table 1).
The pH of the substrate ranges from 5.05 to 5.51, with mean value of 5.3. After 14 days of larvae composting, the lowest pH recorded ranges from 7.04 to 7.51, with mean value of 7.3. However, the highest pH ranges from 7.02 to 7.72, with mean value of 7.4 as shown in Table 1. The study also reported a pH range of 6.04-6.31, with a mean value of 6.2 for the control treatment group.
The pH of the substratum was acidic in the feedstock. An increase in pH was in line with observations made by other researchers (Verma 2002;Diener et al. 2011). Earlier authors fed the larvae of black soldier fly with chicken manure and pig manure and this was consistent with our study. An increase in the pH values was associated with curing of compost (Wei et al. 2007;Bernal et al. 2009).
The dark brown colour of the final compost could be due to the presence of oxygen and stability. It has been reported that the appearance of a dark brown colour and earthly aromatic flavour in compost often shows its maturity (Bernal et al. 2009;Diener et al. 2011).
The moisture contents of the substrate and the residue were measured (Table 1). The study showed that the highest and the lowest moisture contents of the substrate were 63.1% and 60.3%, respectively, while the mean value amounted to 62.7%. The lowest mean moisture content of the residue was 62.7%, while the highest mean moisture content of the residue was 64.9%.
A high moisture content (≥ 60%) of compost usually required post-treatment such as further drying. Post-treatment with thermophilic aerobic composting usually leads to a reduction in the volume of feed (Aja and Al-Kayiem 2014). The temperature of the composting was mesophilic. Aeration was improved on the compost system as a result of the movement and natural turning of the waste by the larvae. Other researchers have reported that high temperature (i.e. 45 °C or more) could cut down the pathogenic loads of the final compost (Banks 2014;Tirado 2008;Dortmans 2015).
Moisture plays an essential role in the metabolic activities of larvae and microorganisms because it indirectly supplies oxygen (Bernal et al. 2009;Dortmans 2015). In this study, the water contents of the feedstock were adequate for decomposition. There was no observable problem except the leachate generation of the bottom of the digesters during the biodegradation processes. A moisture content of 40-60% provides adequate water without hindering aeration. Moisture contents of 40% slow down both larvae and bacterial activities (Bernal et al. 2009). When moisture contents exceed 60%, it could lead to nutrient leachate and usually results in environmental odour (Dortmans 2015).
Variations in the total organic carbon, C:N ratio and C:P ratio of the substrate and residue

Total organic carbon (TOC) levels
An analysis of the results showed that the highest mean percentage TOC removal of 21% (SD ± 5%) was reported in treatment group T-3, which corresponded to the feeding rate (FR) of 107 mg/larvae/day. The lowest percentage mean TOC reduction of 11% (SD ± 2%) was measured in treatment group T-5, with feeding rate of 143 mg/larvae/day as shown in (Fig. 2). The study further showed a reduction of TOC in the control group (i.e. natural microbes) with removal efficiency of 4% (SD ± 1%). In comparing the TOC reduction efficiencies of the larvae (T-1) and control (T-c) treatment groups, it was found that the difference between TOC removal of T-1 and T-c amounts to 14% (Fig. 2) and it was statistically highly significant (p = 0.02) (Fig. 2). The reduction of TOC could be due to carbon loss in the form of CO 2 . It was observed that TOC removal rates increased significantly in treatment T-3. This demonstrated that carbon used by the BSF larvae was higher than in the other treatment groups (Sarpong et al. 2018). The treatment groups T-1, T-2, T-3, T-4, T-5, and T-c were represented by feeding rates FR-71, FR-89, FR-107, FR-125, FR-143 and control (microbes), respectively. The results obtained showed that T-2 and T-4 had the same reduction efficiency of TOC but these were not as high as T-1 and T-3. So far, the control (microbial composting, T-c) did not show any statistical significant difference between reduction in TOC. This could probably be due to the fact that microbial organic waste degradation required adequate time for the microbes to multiply to be able to utilize the carbon compounds.
The utilization of carbon by BSF larvae has been reported by Diener et al. (2015) and Sarpong et al. (2018). It has also been reported that BSF larvae reduced TOC up to 62% in swine manure (Zhao et al. 2016). The loss of carbon in this study could be due to respiration of the larvae through the skin (Lin-ki 1975). It is being reported that the voracious eating habit of the larvae and its movement through the feedstock led to an increase in surface area, which eventually resulted in faster decline of TOC. This assertion was in line with results described by Dortmans (2015) and (Zhao et al. (2016).

Carbon to nitrogen ratio
The results of carbon to nitrogen ratio (C:N ratio) reduction are shown in Fig. 3. The highest C:N ratio reduction was from 14:1 to 8:1, which was measured in the treatment groups T-2, T-3 and T-4. The lowest C:N ratio reduction was from 14:1 to 9:1, which occurred in treatment groups T-1 and T-5. The study also showed a reduction in C:N ratio in the control treatment (microbes) from 12:1 to 11:1. The results obtained for final compost showed a significant difference in the C:N ratio reduction between the larvae treatment group and the control treatment group (p = 0.04).
It has been reported that carbon to nitrogen (C:N ratio) value of 15 or below is highly preferable for agronomic purposes (Jereb 2004;Pan et al. 2012). Therefore, the results of this study (C:N ratio falls within the limit) strongly suggest that the larvae compost obtained could be used for agricultural purpose. Any compost with C:N ratio greater than 30 is likely to immobilize nitrogen if applied to soil (Bernal et al. 2009). But if C:N ratio is less than 20, then it is likely to cause mineralisation of organic nitrogen to inorganic which is suitable for plants (Pan et al. 2012).

Carbon to phosphorus ratio
The highest C:P ratio reduction reported was from 48:1 to 21:1, which was measured in treatment group T-4 (Fig. 4). The lowest C:P ratio reduction was from 48:1 to 31:1, which was reported in treatment group T-1. The study also showed a reduction in C:P ratio in the control treatment group. However, the C:P ratio reduction between the larval treatment group and the control treatment group differed significantly (p = 0.03) (Fig. 4).
A progressive increase in total phosphorus was observed in all the treatment regimes including the microbial composting. However, there was a high reduction in carbon that resulted in a decrease in C:P ratio. An additional supply of phosphorus will be dependent on the amount of phosphorus in the feedstock (Polprasert and Koottatep 2007). The C:P ratio achieved in this study was within the acceptable range for organic waste. In all the treatment regimes, there was an improvement in the C:P ratio at the different feeding rates. Similar observations were made in decomposition of organic waste using earthworm species (Polprasert and   Koottatep 2007). A higher concentration of phosphate in compost is available during the crop-growing season. However, nutrient availability will depend on the quality of soil, the moisture contents and temperature of the environment (Pan et al. 2012).

Analysis of the nutrient concentrations of the compost residues
A percentage increase in total nitrogen (TN) was reported on the final compost ( Table 2). The highest increase in total nitrogen concentration of 41% (SD ± 1.0%) was reported on treatment group T-3. The lowest increase in total nitrogen concentration of 6% (SD ± 0.3%) was recorded in larvae treatment group T-5, whilst the mean percentage increase in TN of the control was 3% (SD ± 0.1%). In comparing the percentage increase in TN, the larvae treatment group T-1 performed higher (4%) than the control treatment group T-c, in 14 days and it was statistically significant (p = 0.04). The nitrogen concentrations increased over time, which could be due to the reduction of dry weight of organic matter (re-concentration) in the substrate by larvae decomposition. Another probable reason for this increase in nitrogen could be due to the biochemical activities of the larvae and the secretions of nitrifying bacteria from the gut of the larvae (Bernal et al. 2009). This was in line with a study conducted by Kim et al. (2011).

Total phosphorus concentration
The study showed an increase in the concentration of total phosphorus (TP) in the organic waste composting by BSF larvae (Table 3). The highest TP reported was 32.4% (SD ± 0.16, 0.14, 0.16%) in the final compost treatment group T-1, T-2 and T-3, respectively. In the larvae treatment group, the lowest increase in TP was 17.6% (SD ± 0.1%), which was reported in T-5, while the control showed much lower percentage increase (10.3%; SD ± 0.05%) in total phosphorus in the compost.

Total potassium concentration
The study showed an increased concentration in total potassium (TK) ( Table 4). The highest mean percentage increase in total potassium was 77.1% (SD ± 0.19%), which was reported in the treatment group T-3 and this was statistically significant (p = 0.02). The lowest percentage increase in TK was 42.9% (SD ± 0.11%), which was reported in the treatment group T-1. Further analysis showed that a percentage increase in total potassium in the control treatment group amounted to 14.3% (SD ± 0.04%), The high percentage increase in potassium (dry weight) content in the compost reported in this current study was similar to the results found in poultry manure compost (Bernal et al. 2009). The poultry manure content of the reference study was twice as much as the ammonium in dairy manure compost of the same study.

Heavy metal assessment of the compost
The toxicological assessment of the compost with respect to arsenic levels showed that the high level of heavy metal  in the substrate (approximately 0.01 mg/kg) was maximally reduced to 0.0002 mg/kg in the final compost (Table 5). The highest arsenic removal efficiency of the system by the larvae was 98% with a standard deviation of 0.01%. This was not significant in treatment groups T-2, T-3 and T-5 (p = 0.05) as shown in Table 5. As part of the study, the efficiency of the larvae in reducing cadmium levels in the feedstock was analysed. The highest statistically significant cadmium efficiencies were almost 100%, i.e. 99.78, 99.43 and 99.56% with standard deviations of 0.28, 0.21 and 0.14% in treatments groups T-1, T-3 and T-4, respectively (Table 6).
With respect to the levels of Fe in the compost after the larvae degradation, assessment of heavy metals was investigated (Table 7). Analysis of the results showed a high concentration of Fe (5.5 mg/kg) in the initial feedstock in Table 3 Mean values of total phosphorus (TP) in the substrate and residue a Mean value followed by the same letter in the same column varies significantly (P <0.05). Treatment regime values in parenthesis ranging from 2.0 to 4.0 kg are the initial quantities of substrate. The feeding rate (FR) was expressed as the total amount of organic waste given to 2000 larvae over a period of 14 days   treatment group T-1 and this was significantly (p = 0.04) reduced to 1.7 mg/kg (i.e. 69%) in the final compost as shown in Table 7. The Fe removal efficiency in the control group from 5.6 to 4.66 mg/kg amounted to 17%. The concentration of nickel, a heavy metal in both the feedstock and the final compost, was analysed as part of this study. There was virtually no observable nickel removal (from 0.3 to 0.3 mg/kg and from 0.01 to 0.01 mg/kg, depending on the treatments) by the larvae. The lead concentrations in the compost were also analysed to find out the extent of lead removal of the compost. The concentrations of lead (Pb) in the substrate range from 0.01 to 0.02 mg/kg, with mean value of 0.015 mg/kg ( Table 8).
The lowest mean removal efficiency of lead was 80% (SD ± 1.6%), which was measured in larvae treatment group T-4. The highest mean removal efficiency of lead was 90%, which happened to T-1, T2, T3 and T 5 with standard deviation of ± 6.6, ± 2.4, ± 2.9 and ± 2.4% respectively. The mean removal efficiency of lead in the control group was 5% (SD ± 1.6%).
The study showed a decrease in heavy metal concentration after larvae degradation. This might be due to the fact that the larvae could biologically accumulate heavy metals in their tissues. Heavy metals may have been accumulated in the larvae's tissues through two different methods: first, through direct skin contact with the nutrients dissolved in the waste; second, through the digestion of certain elements dissolved in the waste after absorption through the intestine. A similar report gave an account, where earthworm's skin absorbed heavy metals in vermicomposting.
A report by Deborah and Raj (2016) has revealed about 50% reduction in cadmium levels when BSFL was fed with feedstock spiked with a known concentration of this heavy metal. It has been reported by Diener and a group of researchers that when the prepupae were homogenized and assessed for the presence of cadmium, the levels had reduced by further 50% before they emerged as flies. The reason for this reduction was due to the fact that the larvae might have discharged the heavy metals through defecation (Zurbrügg 2015).
An effective elimination of heavy metals by defecation has also been reported in larvae of the social paper wasp (Polistes dominulus) (Diener et al. 2011). However, even if the heavy metal accumulates in the cells lining of the alimentary canal, they may be ejected after a short time (Zurbrügg 2015). For instance, Tenebrio molitor (Coleoptera Table 6 Cadmium (Cd) concentrations in the organic solid waste and in the compost obtained using different feeding rates (mg/larvae/day) for black soldier fly larvae (BSFL) Treatment regime values in parenthesis ranging from 2.0 to 4.0 kg are the initial quantities of substrate. Values with (P <0.05) were significantly different. The feeding rate (FR) was expressed as the total amount of organic waste given to 2000 larvae over a period of 14 days  Table 7 Iron (Fe) concentrations in the organic solid waste and in the compost obtained using different feeding rates (mg/larvae/day) for black soldier fly larvae (BSFL) Treatment regime values in parenthesis ranging from 2.0 to 4.0 kg are the initial quantities of substrate. Values with (P <0.05) were significantly different. The feeding rate (FR) was expressed as the total amount of organic waste given to 2000 larvae over a period of 14 days

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Tenebrionidae) discarded cells of the midgut epithelium after 4 days (Zurbrügg 2015). This assertion was consistent with the present study.

Conclusions
Under the circumstances of this experiment, the BSFL organic solid waste treatment technology could contribute to reducing the burden of organic fertilizers shortage in the farm market and provide new income opportunities for small-scale enterprise in developing countries. Furthermore, the compost quality fell within the standard quality in agriculture as a fertilizer. However, since there is cadmium accumulation in the last stage of the larvae (prepupae), it could limit the use of the prepupae in animal feeds. In the case of lead and arsenic, concerns about the use of prepupae in animal feed are less critical. Future research could take steps to evaluate possible bioaccumulation of heavy metals and toxics in the Hermetia illucens larvae before they are used as animal feedstock.


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The influence of application hyperaccumulator plant straw on photosynthetic pigment content and photosynthetic parameter of lettuce under cadmium stress

. Pot experiments were conducted to study the effects of straw application of three hyperaccumulator plants ( Solanum nigrum , Bidens pilosa and Galinsoga parviflora ) influence photosynthetic pigments content and photosynthetic parameters of lettuce ( Lactuca sativa ) under Cd stress. The results showed that: compared with no straw application, the photosynthetic pigment content of lettuce was increased by applying three kinds of hyperaccumulator plants straw ( S. nigrum , B. pilosa and G. parviflora ), but there was no significant difference among the three kinds of hyperaccumulator plant straws; also improved the net photosynthetic rate (Pn), Stomatal conductance (Gs), transpiration rate (Tr), intercellular CO2 concentration (Ci) of lettuce, among them, the effect of G. parviflora straw was the most obvious. Application of three kinds of hyperaccumulator plant straw promoted the growth of lettuce by increasing the photosynthetic pigment content and photosynthetic parameter of lettuce under Cd stress.

Introduction
Straw returning is an agricultural measure being vigorously promoted, which can avoid air pollution caused by straw burning, it can also promote crop growth by improving soil fertility and soil properties, and reduce the bioavailability of heavy metals such as copper, cadmium (Cd) and zinc [1]. One of many heavy metals, Cd pollution in soil mainly comes from transportation, agricultural inputs, sewage irrigation and sludge fertilization [2]. Cd can seriously harm plants and affect human health, there are many ways to alleviate Cd toxicity: intercropping [3], grafting [4], application of biomass charcoal [5] and so on. Applying straw of Tagetes erecta and Solanum photeinocarpum to Cd-contaminated soil at 10 mg/kg significantly increase tomato biomass and photosynthetic pigments content, and significantly decrease Cd content [6]. Hyperaccumulator plant can effectively repair heavy metal pollution. Soil application of hyperaccumulator plant straw has little research on Cd accumulation in leafy vegetables. Therefore, this experiment explored the effects of hyperaccumulator plant straw on photosynthetic pigments and photosynthetic parameters of lettuce under Cd pollution. It provides a new method for leafy vegetables to alleviate heavy metal pollution.

Materials
In June 2015, three kinds of Cd hyperaccumulator plants were collected from the surrounding farmland (not contaminated by heavy metals) in the Sichuan Agriculture University: Solanum nigrum, Bidens pilosa and Galinsoga parviflora, after removed the seeds, they were washed with distilled water. After 15 minutes of killing fresh at 105 °C, they are dried to constant weight at 75 °C. Cutting the dried straw into about 1 cm segments and set aside.
Lettuce is a common glass lettuce in Sichuan, it has high purity, good quality, good tolerance and resistance, and can be planted all year round and sustainable harvest for more than 50 days.
The tested soil was paddy soil, which was taken from farmland not polluted by heavy metals around Chengdu campus of Sichuan Agricultural University, its basic physical and chemical properties are as follows: pH 6.36, organic matter 18.10 g/kg, total nitrogen1.04 g/kg, total phosphorus 1.36 g/kg, total potassium 20.78 g/kg, hydrolyzable nitrogen 43.90 mg/k, available phosphorus 92.71 mg/kg, available potassium134.25 mg/kg, available Cd not detected. CdCl2· 2.5H2O analytical pure solution was added to the tested soil for heavy metal Cd.

Experimental design
In June 2015, the air-dried and crushed soil was sifted through 300 meshes and loaded into barrels, each containing 20 kg. The Cd concentration was 10 mg/kg by adding analytical pure CdCl2· 2.5 H2O solution [7], after 30 days of moist storage, all contaminated soils were fully blended and packed in a pot of 3 kg per pot.
Full lettuce seeds were select for disinfection, evenly spread them on wet gauze, put them into 20 °C light incubator for germination, and then sow them in a pot dish with nutritive soil to raise seedlings. After one week of lettuce seedling raising, three kinds of hyperaccumulator plant straw were applied to the prepared Cd contaminated soil, 6 g per pot, and mixed evenly, with no straw as the control. The experiment was divided into four treatments: no straw, S. nigrum straw, B. pilosa straw and G. parviflora straw. After a week of balancing and watering, selected healthy lettuce seedlings and transplant them into Cd-contaminated soil prepared with straw. Four plants were transplanted in each pot and nine pots were treated in each pot. After transplanting, the seedlings were placed in plastic greenhouse, and the soil moisture was maintained at about 80%. After the lettuce grew 50d, chlorophyll content and photosynthetic parameters of lettuce were determined.

Statistical analyses
All data are collated with Excel 2010 software; SPSS 20.0 was used for variance analysis and Duncan's new complex range method was used for multiple comparisons.

3.1.
Effects of soil application of hyperaccumulator plant straw on photosynthetic pigment content in lettuce leaves Application of hyperaccumulator plant straw increased the chlorophyll content of lettuce ( Table 1). The application of B. pilosa straw and G. parviflora straw significantly increased chlorophyll a content in lettuce leaves. The content of chlorophyll a in lettuce leaves treated with B. pilosa straw was the highest, 25.27% higher than that of the control (P < 0.05). When application B. pilosa straw, lettuce had the highest chlorophyll b content, but there was no significant difference among the treatments. The different trend of total chlorophyll content of lettuce was the same as that of chlorophyll a content. The order from high to low was B. pilosa straw > G. parviflora straw > S. nigrum straw > no straw. The different trend of carotenoids in lettuce was the same as that of chlorophyll a and total chlorophyll. The carotenoid content of lettuce treated with B. pilosa straw was the highest, 42.86% higher than that of the control (P < 0.05). The ratio of chlorophyll a to chlorophyll b in lettuce increased after the application of hyperaccumulator plant straw, and the treatment with G. parviflora straw was the highest. Different lowercase letters in the same column indicate significant difference (P<0.05).

3.2.
Effects of soil application of hyperaccumulator plant straw on photosynthetic parameters of lettuce leaves All treatments increased Pn in lettuce leaves, there was no significant difference between B. pilosa straw and G. parviflora straw treatments, but they were significantly higher than no straw treatment, which increased by 14.06% (P < 0.05) and 14.06% (P < 0.05), respectively ( Table 2). Leaf Gs of lettuce increased after the application of hyperaccumulator plant straw, and the order of its size was: G. parviflora straw > S. nigrum straw > B. pilosa straw > no straw, there was no difference among the treatments, but it was significantly higher than the control. For lettuce leaf Ci, the application of G. parviflora straw increased by 6.13% compared with the control (P < 0.05). Hyperaccumulator plant straw significantly increased leaf Tr of lettuce under Cd stress. The order of Tr in each treatment was as follows: G. parviflora straw > B. pilosa straw > S. nigrum straw > no straw. The Tr of lettuce leaves was the highest after applying G. parviflora straw, 46.01% significantly higher than that of the control (P < 0.05).  Different lowercase letters in the same column indicate significant difference (P<0.05).

Conclusion
Under Cd stress, the chlorophyll content of lettuce leaves was significantly increased by applying straw from hyperaccumulator plants (S. nigrum straw, B. pilosa straw and G. parviflora straw) in soil, but there was no significant difference among treatments; the photosynthetic parameters of G. parviflora straw increased most obviously when applied. Therefore, under the condition of Cd pollution, the application of three hyperaccumulator plants straws (S. nigrum straw, B. pilosa straw and G. parviflora straw) were conducive to the normal growth of lettuce.