Effect of nanobubble concentrations on fouling control capacity in biogas slurry wastewater distribution systems.

Nanobubble (NB) represents a promising practice for mitigating fouling in biogas slurry distribution systems. However, its anti-fouling effectiveness and optimal use dosage are unknown. This study investigated the NB anti-fouling capacity at six concentrations (0 %-100 %, denoting the ratio of maximum NB-infused water; particle concentrations in 0 % and 100 % ratios were 1.08 × 107 and 1.19 × 109 particles mL-1, respectively). Results showed that NB effectively mitigated multiple fouling at 50 %-100 % ratios, whereas low NB concentration exacerbated fouling. NB functioned both as an activator and a bactericide for microorganisms, significantly promoting biofouling at 5 %-25 %, and inhibiting biofouling at 50 %-100 %. Owing to an enhanced biofilm biomineralization ability, low NB concentration aggravated precipitate fouling, whereas high NB doses effectively mitigated precipitates. Additionally, higher NB concentrations demonstrated superior control efficiency against particulate fouling. This study contributes insights into NB effectiveness in controlling various fouling types within wastewater distribution systems.

Effects of irrigation scheduling on the yield and irrigation water productivity of cucumber in coconut coir culture.

Optimum irrigation scheduling is important for ensuring high yield and water productivity in substrate-cultivated vegetables and is determined based on information such as substrate water content, meteorological parameters, and crop growth. The aim of this study was to determine a precise irrigation schedule for coconut coir culture in a solar greenhouse by comparing the irrigation, evapotranspiration (ET), substrate water content (VWC), as well as the crop growth indices and yield of cucumber, and irrigation water productivity (IWP) under three irrigation schedules: the soil moisture sensor-based method (T-VWC), the accumulated radiation combined with soil moisture sensor-based method (Rn-VWC), and the crop evapotranspiration estimated method using the hourly PM-ETo equation with an improved calculation of Kc (T-ETc). The results showed that the daily irrigation and evapotranspiration amount were the highest under T-VWC treatment, while the lowest under T-ETc treatment. In different meteorological environments, the change in irrigation amount was more consistent with the ET,and the VWC was relatively stable in T-ETc treatment compared with that under T-VWC or Rn-VWC treatments. The plant height, leaves number, leaf area, and stem diameter of T-VWC and Rn-VWC treatments were higher than those of the T-ETc treatments, but there was no significant difference in cucumber yield. Compared with the T-VWC treatment, total irrigation amount under Rn-VWC and T-ETc treatments significantly decreased by 25.75% and 34.04%, respectively ([Formula: see text]). The highest IWP values of 25.07 kg m[Formula: see text] was achieved from T-ETc treatment with significantly increasing by 44.33% compared to the T-VWC treatment (17.37 kg m[Formula: see text]). In summary, the T-ETc treatment allowed more reasonable irrigation management and was appropriate for growing cucumber in coconut coir culture.

Performance analysis of two typical greenhouse lettuce production systems: commercial hydroponic production and traditional soil cultivation.

Introduction: Due to the shortage of land and water resource, optimization of systems for production in commercial greenhouses is essential for sustainable vegetable supply. The performance of lettuce productivity and the economic benefit in greenhouses using a soil-based system (SBS) and a hydroponic production system (HPS) were compared in this study. Methods: Experiments were conducted in two identical greenhouses over two growth cycles (G1 and G2). Three treatments of irrigation volumes (S1, S2, and S3) were evaluated for SBS while three treatments of nutrient solution concentration (H1, H2, and H3) were evaluated for HPS; the optimal levels from each system were then compared. Results and discussion: HPS was more sensitive to the effects of environmental temperature than SBS because of higher soil buffer capacity. Compared with SBS, higher yield (more than 134%) and higher water productivity (more than 50%) were observed in HPS. We detected significant increases in ascorbic acid by 28.31% and 16.67% and in soluble sugar by 57.84% and 32.23% during G1 and G2, respectively, compared with SBS. However, nitrate accumulated in HPS-grown lettuce. When the nutrient solution was replaced with fresh water 3 days before harvest, the excess nitrate content of harvested lettuce in HPS was removed. The initial investment and total operating cost in HPS were 21.76 times and 47.09% higher than those in SBS, respectively. Consideration of agronomic, quality, and economic indicators showed an overall optimal performance of the H2 treatment. These findings indicated that, in spite of its higher initial investment and requirement of advanced technology and management, HPS was more profitable than SBS for commercial lettuce production.

Ammonia oxidizing archaea and bacteria respond to different manure application rates during organic vegetable cultivation in Northwest China.

Ammonia oxidization is a critical process in nitrogen cycling that involves ammonia oxidizing archaea (AOA) and bacteria (AOB). However, the effects of different manure amounts on ammonia-oxidizing microorganisms (AOMs) over the course of organic vegetables production remains unclear. We used the amoA gene to evaluated AOMs abundance and community structure in organic vegetable fields. Quantitative PCR revealed that AOB were more abundant than AOA. Among them, the amoA copy number of AOB treated with 900 kgN ha-1 was 21.3 times that of AOA. The potential nitrification rate was significantly correlated with AOB abundance (P < 0.0001) but not with AOA, suggesting that AOB might contribute more to nitrification than AOA. AOB sequences were classified into Nitrosomonas and Nitrosospira, and AOA into Nitrosopumilus and Nitrososphaera. Nitrosomonas and Nitrosopumilus were predominant in treatments that received manure nitrogen at ≥ 900 kg ha-1 (52.7-56.5%) and when manure was added (72.7-99.8%), respectively, whereas Nitrosospira and Nitrososphaera occupied more than a half percentage in those that received ≤ 600 kg ha-1 (58.4-84.9%) and no manure (59.6%). A similar manure rate resulted in more identical AOMs' community structures than greater difference manure rate. The bacterial amoA gene abundances and ratios of AOB and AOA showed significantly positive correlations with soil electrical conductivity, total carbon and nitrogen, nitrate, phosphorus, potassium, and organic carbon, indicating that these were potential key factors influencing AOMs. This study explored the AOMs' variation in organic vegetable fields in Northwest China and provided a theoretical basis and reference for the subsequent formulation of proper manure management.

Effects of light quality on growth, nutritional characteristics, and antioxidant properties of winter wheat seedlings (Triticum aestivum L.).

Wheat seedlings are becoming popular for its high nutritional value. Effects of White (W), White + Red (WR), and White + Blue (WB) light-emitting diodes (LEDs) treatments on growth, nutritional characteristics and antioxidant properties of wheat seedlings were studied in a plant factory. The results showed that height, leaf area, shoot fresh, and shoot dry weight per wheat seedling were the highest under WR at 13 and 22 days after planting. Soluble sugar content in leaves and stems were 22.3 and 65% respectively higher under WB than those under W. Soluble protein content in leaves and stems were 36.8 and 15.2% respectively lower under WR than those under W. Contents of total flavonoids, glutathione (GSH) and ascorbic acid (ASA) in leaves were the highest under WB, whereas malondialdehyde (MDA) content in leaves was the lowest under WB. The activities of antioxidant enzymes [superoxide dismutase (SOD), peroxidase (POD), and ascorbate peroxidase (APX)] in leaves and 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging ability were also the highest under WB. In conclusion, WR promoted the growth of wheat seedlings, and WB promoted antioxidant level and nutritional accumulation. This study provides guidance for wheat seedlings to carry out preferential production (biomass or quality).

Effects of light-emitting diode spectral combinations on growth and quality of pea sprouts under long photoperiod.

Pea sprouts have rich nutrition and are considered good for heart health. In this study, the kaspa peas and black-eyed peas were chosen to clarify the effect of different LED spectral combinations on the growth, yield, and nutritional quality of pea sprouts under long photoperiod (22 h light/2 h dark). The results showed that the two pea varieties responded differently to light spectral combinations. Black-eyed pea sprouts had higher plant height, fresh weight per plant, dry weight per plant, soluble sugar content, and lower malondialdehyde (MDA) content than kaspa peas under the same light treatment. Compared with white light, red-to-blue ratio of 2:1 significantly increased peroxidase (POD) and superoxide dismutase (SOD) activity, soluble sugar and soluble protein content of kaspa pea sprouts, and decreased MDA content of black-eyed pea sprouts. Blue light was negatively correlated with the plant height of pea sprouts and positively correlated with SOD activity, vitamin C, soluble sugar, and soluble protein content. Antioxidant capacity, yield, and nutritional quality of black-eyed pea sprouts were higher than those of kaspa pea sprouts under the same light treatment. Blue light improved the nutritional quality of pea sprouts. Compared with other light treatments, the red-to-blue ratio of 2:1 was more conducive to improving the antioxidant capacity and nutritional quality of pea sprouts under long photoperiod.

Data-Driven Calibration of Soil Moisture Sensor Considering Impacts of Temperature: A Case Study on FDR Sensors.

Commercial soil moisture sensors have been widely applied into the measurement of soil moisture content. However, the accuracy of such sensors varies due to the employed techniques and working conditions. In this study, the temperature impact on the soil moisture sensor reading was firstly analyzed. Next, a pioneer study on the data-driven calibration of soil moisture sensor was investigated considering the impacts of temperature. Different data-driven models including the multivariate adaptive regression splines and the Gaussian process regression were applied into the development of the calibration method. To verify the efficacy of the proposed methods, tests on four commercial soil moisture sensors were conducted; these sensors belong to the frequency domain reflection (FDR) type. The numerical results demonstrate that the proposed methods can greatly improve the measurement accuracy for the investigated sensors.

Research on soil moisture prediction model based on deep learning.

Soil moisture is one of the main factors in agricultural production and hydrological cycles, and its precise prediction is important for the rational use and management of water resources. However, soil moisture involves complex structural characteristics and meteorological factors, and it is difficult to establish an ideal mathematical model for soil moisture prediction. Existing prediction models have problems such as prediction accuracy, generalization, and multi-feature processing capability, and prediction performance must improve. Based on this, taking the Beijing area as the research object, the deep learning regression network (DNNR) with big data fitting capability was proposed to construct a soil moisture prediction model. By integrating the dataset, analyzing the time series of the predictive variables, and clarifying the relationship between features and predictive variables through the Taylor diagram, selected meteorological parameters can provide effective weights for moisture prediction. Test results prove that the deep learning model is feasible and effective for soil moisture prediction. Its' good data fitting and generalization capability can enrich the input characteristics while ensuring high accuracy in predicting the trends and values of soil moisture data and provides an effective theoretical basis for water-saving irrigation and drought control.

Potential using of infrared thermal imaging to detect volatile compounds released from decayed grapes.

Previous studies have demonstrated variations in volatile compound content during fruit spoilage. Infrared spectroscopy was proposed as an alternative method to discriminate the various states of decayed fruit through the makeup of their volatile compounds. Based on the infrared spectra of volatile compounds obtained from decayed grapes, this study simplified the extraction of their feature spectra and visualized their gas plumes by using a commercial infrared thermal camera equipped with a custom-made wavelength filter. As a function of volatilization gradients, accumulated gray value and imaging area were proposed as indicators for semi-quantitative analysis in a volatilization range similar to that of ethanol solutions ranging from 10% to 70%. Fresh, seriously decayed, and slightly or moderately decayed grapes were rapidly discriminated through their alcoholic volatiles by thermal images with correct classification ratings of 100%, 93.3%, and 90%, respectively.

In-Field, In Situ, and In Vivo 3-Dimensional Elemental Mapping for Plant Tissue and Soil Analysis Using Laser-Induced Breakdown Spectroscopy.

Sensing and mapping element distributions in plant tissues and its growth environment has great significance for understanding the uptake, transport, and accumulation of nutrients and harmful elements in plants, as well as for understanding interactions between plants and the environment. In this study, we developed a 3-dimensional elemental mapping system based on laser-induced breakdown spectroscopy that can be deployed in- field to directly measure the distribution of multiple elements in living plants as well as in the soil. Mapping is performed by a fast scanning laser, which ablates a micro volume of a sample to form a plasma. The presence and concentration of specific elements are calculated using the atomic, ionic, and molecular spectral characteristics of the plasma emission spectra. Furthermore, we mapped the pesticide residues in maize leaves after spraying to demonstrate the capacity of this method for trace elemental mapping. We also used the system to quantitatively detect the element concentrations in soil, which can be used to further understand the element transport between plants and soil. We demonstrate that this method has great potential for elemental mapping in plant tissues and soil with the advantages of 3-dimensional and multi-elemental mapping, in situ and in vivo measurement, flexible use, and low cost.

[Research on Grape Deterioration Process via Volatiles -Using Long Optical-Path Infrared Spectroscopy and Simplified E-Nose].

Grapes vaporize volatiles in specific compositions and concentrations during deterioration processes. Our previous study demonstrated that it is possible to analyze grapes spoilage stages by using the infrared spectra of their volatiles. However, only the spectral characteristics of alcohol, ethyl acetate and carbon dioxide were observed in the experiment because of the low concentration of the volatiles. In this paper, the sensitivity of the spectrometry system was enhanced by increasing the optical-path with multi-reflecting mirrors. We used the new spectrometry system to study the details of the infrared spectra of the volatiles from grapes during spoilage, and observed the spectral characteristics of several kinds of ethanol, esters, aldehyde and ethylene. The concentrations of some components in the volatiles changes with storage time, which can be a biomarker to represent the spoilage stages of grapes. Chemometrics were used to analyze the spectral bands of ethanol and esters, demonstrating there are obvious differences between fresh and decayed grapes. Furthermore, we developed a simplified E-nose system comprised by sensor array, based on the results of spectral analysis. The classification and discrimination of grape spoilage were tested with E-nose. This was a further study of the previous publication and had given a more precise observation of the infrared spectral characteristics of the volatiles from decayed grapes. This study provided a basis for developing real-time monitoring techniques of fruits deterioration.

[Application of Fourier transform infrared spectroscopy in identification of wine spoilage].

In the present work, fresh and spoiled wine samples from three wines produced by different companies were studied u- sing Fourier transform infrared (FTIR) spectroscopy. We analyzed the physicochemical property change in the process of spoil- age, and then, gave out the attribution of some main FTIR absorption peaks. A novel determination method was explored based on the comparisons of some absorbance ratios at different wavebands although the absorbance ratios in this method were relative. Through the compare of the wine spectra before and after spoiled, the authors found that they were informative at the bands of 3,020~2,790, 1,760~1,620 and 1,550~800 cm(-1). In order to find the relation between these informative spectral bands and the wine deterioration and achieve the discriminant analysis, chemometrics methods were introduced. Principal compounds analysis (PCA) and soft independent modeling of class analogy (SIMCA) were used for classifying different-quality wines. And partial least squares discriminant analysis (PLS-DA) was applied to identify spoiled wines and good wines. Results showed that FTIR technique combined with chemometrics methods could effectively distinguish spoiled wines from fresh samples. The effect of classification at the wave band of 1 550-800 cm(-1) was the best. The recognition rate of SIMCA and PLSDA were respectively 94% and 100%. This study demonstrates that Fourier transform infrared spectroscopy is an effective tool for monitoring red wine's spoilage and provides theoretical support for developing early-warning equipments.

[Research on error reduction of path change of liquid samples based on near infrared trans-reflective spectra measurement].

Based on sucrose solution as the research object, this paper measured the trans-reflective spectrum of sucrose solution of different concentration by the technique of near infrared spectrum in three optical path (4, 5, 6 mm). Five kinds of pretreatment method (vector normalization, baseline offset correction, multiplicative scatter correction, standard normal variate transformation, a derivative) were used to eliminate the influence of the optical path difference, and to establish model of the calibration set in combination with the PLS (Partial Least Squares)method. Five kinds of pretreatment method could restrain the inter ference of light path in varying degrees. Compared with the PLS model of original spectra, the model of multiple scattering correction combined with PLS method is the optimal model. The results of quantitative analysis of original spectra: the number of principal component PC= 6, the determination coefficient R2 = 0.891 278, the determination coefficient of cross validation R2CV = 0.888 374, root mean square error of calibration RMSEC = 1.704%, root mean square error of cross validation RMSECV = 1.827%; The results of quantitative analysis of spectra after MSC pretreatment: the number of principal component PC = 3, the determination coefficient R2 = 0.987 535, the determination coefficient of cross validation R2CV = 0.983 343, root mean square er- ror of calibration RMSEC = 0.89%, root mean square error of cross validation RMSECV = 1.05%. The correlation coefficient of the prediction set is as much as 0.976 22. root mean square error of prediction is 0.01, lesser than 0.014 36. The results show that the MSC can eliminate the influence of optical path difference, improve the prediction precision and improve the stability.

Analyzing strawberry spoilage via its volatile compounds using longpath Fourier transform infrared spectroscopy.

The volatile compounds from fruits vary based on the spoilage stage. We used FTIR spectroscopy to analyze and to attempt to identify the spoilage process of strawberries. To enhance the sensitivity of the measuring system, we increased the optical pathlength by using multi-reflecting mirrors. The volatile compounds that were vaporized from strawberries in different spoilage stages were tested. We analyzed the spectra and found that the concentrations of esters, alcohols, ethylene, and similar compounds changed with deterioration. The change patterns of the infrared spectra for the volatiles were further examined using 2D correlation spectroscopy. We analyzed the spectral data using PCA and were able to distinguish the fresh, slightly spoiled strawberries from the seriously spoiled strawberries. This study demonstrates that FTIR is an effective tool for monitoring strawberry spoilage and for providing status alerts.

[Determination of potassium in farmland soil using laser-induced breakdown spectroscopy].

The real-time measurement of potassium in farmland soil has great importance. A method to determine the potassium content in farmland soil based on laser-induced breakdown spectroscopy (LIBS) was studied using a LIBS equipment consisting of a 1,064 nm laser generator and a high resolution spectrometer. The farmland soil samples with potassium content in the range of 8.74-34.56 g.kg-1 were analyzed. The 766.49 nm was chosen as the analysis line, by comparing the potassium atom characteristic lines of 404.40, 404.72, 766.49 and 769.90 nm. The errors of characteristic line strength caused by the laser stability and random noise was analyzed. The silicon, which is nearly constant in farmland soil, was chosen as the standard element, and a calibration model between the ratio of potassium to silicon (K/Si) and the potassium content was established. The linear fitting degree of the calibration curve was 0.935, and the relative standard deviation of the calibration model for prediction set samples was 9.26%.

[Pretreatment method of near-infrared diffuse reflection spectra used for sugar content prediction of pears].

The content of sugar is an important quality index for pears. However, the traditional sugar measurement methods are time-consuming and destructive. In the present study, the authors measured the sugar content of pears using visible and near infrared diffuse reflection spectroscopy. The pretreatment methods of multiplicative scatter correction (MSC), baseline correction, standard normal variate (SNV) transformation, and moving average algorithms were used on the original absorbance spectrum. Results indicate that the absorbance spectra after pretreatment are better than the original absorbance spectra for prediction. Partial least squares (PLS) regression was also used on the original absorbance spectrum and the absorbance spectrum after moving average and baseline correction. It follows that the forecast accuracy of the absorbance spectra after moving average is higher than that of the original absorbance spectra. The models gave good predictions of the sugar content of pears, with corresponding r values of 0.990 8, and standard errors of predictions of 0.019 0.

[Laser-induced fluorescence spectroscopy characterization of farmland soil moisture content].

Online measurement of soil moisture is significant for agricultural production. The abundance and deficiency of leaf water shortage has been able to effect measured by fluorescence, but the research of correlation between soil moisture and laser-induced fluorescence spectroscopy has not been carried out yet. In this paper, the relationship between laser-induced plant chlorophyll fluorescence and soil moisture was studied. In the experiment with rice as the research object, the chlorophyll fluorescence induced by a 450 nm LED light source was measured by a Y-shaped fiber probe, and the soil moisture was obtained by TDR sensors. The changes in the peak intensity near 743 nm of chlorophyll fluorescence under continuous water stress and intermittent water stress were studied. The result showed that the intensity decreased with the soil moisture content. Finally, the model between the soil water content and the intensity of chlorophyll fluorescence under continuous water stress was created by using Lorentzian equation, and the coefficient of determination (R2) of the model was high. The result indicated that the method mentioned in paper can be applied to measure soil moisture in agricultural production.