Beyond the Spectrum: Unleashing the Potential of Infrared Radiation in Poultry Industry Advancements.

The poultry industry is dynamically advancing production by focusing on nutrition, management practices, and technology to enhance productivity by improving feed conversion ratios, disease control, lighting management, and exploring antibiotic alternatives. Infrared (IR) radiation is utilized to improve the well-being of humans, animals, and poultry through various operations. IR radiation occurs via electromagnetic waves with wavelengths ranging from 760 to 10,000 nm. The biological applications of IR radiation are gaining significant attention and its utilization is expanding rapidly across multiple sectors. Various IR applications, such as IR heating, IR spectroscopy, IR thermography, IR beak trimming, and IR in computer vision, have proven to be beneficial in enhancing the well-being of humans, animals, and birds within mechanical systems. IR radiation offers a wide array of health benefits, including improved skin health, therapeutic effects, anticancer properties, wound healing capabilities, enhanced digestive and endothelial function, and improved mitochondrial function and gene expression. In the realm of poultry production, IR radiation has demonstrated numerous positive impacts, including enhanced growth performance, gut health, blood profiles, immunological response, food safety measures, economic advantages, the mitigation of hazardous gases, and improved heating systems. Despite the exceptional benefits of IR radiation, its applications in poultry production are still limited. This comprehensive review provides compelling evidence supporting the advantages of IR radiation and advocates for its wider adoption in poultry production practices.

Insight into the effective electrocatalytic sulfide removal from aqueous solutions using surface oxidized stainless-steel anode and its desulfurization mechanism.

The electrochemical oxidation of hydrogen sulfide (H2S) has shown its potential for the real application of H2S emission control in wastewater treatment. In this study, a surface corrosion treatment of stainless steel (SS) was optimized by regulate Ni content in the oxide film on the SS AISI 304 surface for sulfide removal. The X-ray photoelectron spectroscopy and linear sweeping voltammetry results indicated a higher Ni content in the oxide film of surface-oxidized stainless steel (SOSS) attributed to a higher sulfide removal potential. Sulfide removal experiment results showed that SS-150 (with 150 s anodic pretreatment) anodes achieved the highest Ni content of 69% with the best sulfide removal efficiency, i.e., 97% within 48 h, which increased by 20% compared to the untreated SS. This study also demonstrated a strategy for in situ removal of deposited sulfur on the anodes by cathodic treatment at -0.38 V vs. RHE to alleviate the common issue of sulfur passivation. Density functional theory (DFT) calculation revealed that NiOOH was the major active species in SS-150 oxide film for a faster sulfide removal rate. The study developed a SS surface modification process for Ni content regulation that contributed to better sulfide removal efficiency.

An efficient segmentation model for abnormal chicken droppings recognition based on improved deep dual-resolution network.

The characteristics of chicken droppings are closely linked to their health status. In prior studies, chicken droppings recognition is treated as an object detection task, leading to challenges in labeling and missed detection due to the diverse shapes, overlapping boundaries, and dense distribution of chicken droppings. Additionally, the use of intelligent monitoring equipment equipped with edge devices in farms can significantly reduce manual labor. However, the limited computational power of edge devices presents challenges in deploying real-time segmentation algorithms for field applications. Therefore, this study redefines the task as a segmentation task, with the main objective being the development of a lightweight segmentation model for the automated monitoring of abnormal chicken droppings. A total of 60 Arbor Acres broilers were housed in 5 specific pathogen-free cages for over 3 wk, and 1650 RGB images of chicken droppings were randomly divided into training and testing sets in an 8:2 ratio to develop and test the model. Firstly, by incorporating the attention mechanism, multi-loss function, and auxiliary segmentation head, the segmentation accuracy of the DDRNet was enhanced. Then, by employing the group convolution and an advanced knowledge-distillation algorithm, a lightweight segmentation model named DDRNet-s-KD was obtained, which achieved a mean Dice coefficient (mDice) of 79.43% and an inference speed of 86.10 frames per second (FPS), showing a 2.91% and 61.2% increase in mDice and FPS compared to the benchmark model. Furthermore, the DDRNet-s-KD model was quantized from 32-bit floating-point values to 8-bit integers and then converted to TensorRT format. Impressively, the weight size of the quantized model was only 13.7 MB, representing an 82.96% reduction compared to the benchmark model. This makes it well-suited for deployment on the edge device, achieving an inference speed of 137.51 FPS on Jetson Xavier NX. In conclusion, the methods proposed in this study show significant potential in monitoring abnormal chicken droppings and can provide an effective reference for the implementation of other agricultural embedded systems.

The characteristics of chicken droppings are closely related to their health. In this study, we developed a lightweight segmentation model for chicken droppings and evaluated its inference speed on the edge device with limited computational power. The results showed that the proposed model exhibits significant potential in the early warning of abnormal chicken droppings, which can help producers implement interventions before disease outbreaks, thereby avoiding great economic losses. Additionally, the model optimization and compression processes proposed in this study can provide an effective reference for the implementation of other embedded systems.

Eggshell biometrics for individual egg identification based on convolutional neural networks.

Individual egg identification technology has potential applications in breeding, product tracking/tracing, and anti-counterfeit. This study developed a novel method for individual egg identification based on eggshell images. A convolutional neural network-based model, named Eggshell Biometric Identification (EBI) model, was proposed and evaluated. The main workflow included eggshell biometric feature extraction, egg information registration, and egg identification. The image dataset of individual eggshell was collected from the blunt-end region of 770 chicken eggs using an image acquisition platform. The ResNeXt network was then trained as a texture feature extraction module to obtain sufficient eggshell texture features. The EBI model was applied to a test set of 1,540 images. The testing results showed that when an appropriate Euclidean distance threshold for classification was set (17.18), the correct recognition rate and the equal error rate reached 99.96% and 0.02%. This new method provides an efficient and accurate solution for individual chicken egg identification, and can be extended to eggs of other poultry species for product tracking/tracing and anti-counterfeit.

A reliable and low-cost deep learning model integrating convolutional neural network and transformer structure for fine-grained classification of chicken Eimeria species.

Chicken coccidiosis is a disease caused by Eimeria spp. and costs the broiler industry more than 14 billion dollars per year globally. Different chicken Eimeria species vary significantly in pathogenicity and virulence, so the classification of different chicken Eimeria species is of great significance for the epidemiological survey and related prevention and control. The microscopic morphological examination for their classification was widely used in clinical applications, but it is a time-consuming task and needs expertise. To increase the classification efficiency and accuracy, a novel model integrating transformer and convolutional neural network (CNN), named Residual-Transformer-Fine-Grained (ResTFG), was proposed and evaluated for fine-grained classification of microscopic images of seven chicken Eimeria species. The results showed that ResTFG achieved the best performance with high accuracy and low cost compared with traditional models. Specifically, the parameters, inference speed and overall accuracy of ResTFG are 1.95M, 256 FPS and 96.9%, respectively, which are 10.9 times lighter, 1.5 times faster and 2.7% higher in accuracy than the benchmark model. In addition, ResTFG showed better performance on the classification of the more virulent species. The results of ablation experiments showed that CNN or Transformer alone had model accuracies of only 89.8% and 87.0%, which proved that the improved performance of ResTFG was benefit from the complementary effect of CNN's local feature extraction and transformer's global receptive field. This study invented a reliable, low-cost, and promising deep learning model for the automatic fine-grain classification of chicken Eimeria species, which could potentially be embedded in microscopic devices to improve the work efficiency of researchers and extended to other parasite ova, and applied to other agricultural tasks as a backbone.

In vivo prediction of abdominal fat and breast muscle in broiler chicken using live body measurements based on machine learning.

The purpose of this study was to predict the carcass characteristics of broilers using support vector regression (SVR) and artificial neural network (ANN) model methods. Data were obtained from 176 yellow feather broilers aged 100-day-old (90 males and 86 females). The input variables were live body measurements, including external measurements and B-ultrasound measurements. The predictors of the model were the weight of abdominal fat and breast muscle in male and female broilers, respectively. After descriptive statistics and correlation analysis, the datasets were randomly divided into train set and test set according to the ratio of 7:3 to establish the model. The results of this study demonstrated that it is feasible to use machine learning methods to predict carcass characteristics of broilers based on live body measurements. Compared with the ANN method, the SVR method achieved better prediction results, for predicting breast muscle (male: R2 = 0.950; female: R2 = 0.955) and abdominal fat (male: R2 = 0.802; female: R2 = 0.944) in the test set. Consequently, the SVR method can be considered to predict breast muscle and abdominal fat of broiler chickens, except for abdominal fat in male broilers. However, further revaluation of the SVR method is suggested.

Nickel-Catalyzed mesoporous biochar for enhanced adsorptive oxidation of aqueous Sulfide: An investigation of influencing factors and mechanisms.

Biochar (BC) is a low-cost and electroactive adsorbent for removing sulfide in aqueous media, which toxifies aquatic organisms and corrodes water treatment facilities. However, it lacks a pore structure for sulfide ion (S2-) mass transfer to active sites. Herein, it is shown that nickel-modified biochar (BC-Ni) adsorbed S2- 2.72-fold faster than BC alone and attained a 1244 ± 252 mg-sulfide/g maximum adsorption capacity due to markedly increased mesopores, while BC attained 583 ± 250 mg-sulfide/g. Factors influencing S2-sorption and theoretical sorption kinetics and isotherms models were evaluated. Structural and surface compositions of BC and BC-Ni were examined using state-of-the-art characterizations. The results suggest that S2- was adsorbed via pore diffusion, pore filling, and cation bridging and oxidized to elemental sulfur and sulfate with quinone and hydrogen peroxide generated from dehydrogenation of hydroquinone on the BC-Ni by metallic nickel in the carbon matrix. This study would spur biomass valorization and desulfurization.

Impacts of molybdate and ferric chloride on biohythane production through two-stage anaerobic digestion of sulfate-rich hydrolyzed tofu processing residue.

Biohythane production through one-stage anaerobic digestion of sulfate-rich hydrolyzed tofu processing residue has been hampered by high H2S production. Herein, two-stage anaerobic digestion was investigated with the addition of molybdate (MoO42-; 0.24-3.63 g/L) and ferric chloride (FeCl3; 0.025-5.4 g/L) to the dark fermentation stage (DF) to improve biohythane production. DF supplemented with 1.21 g/L MoO42- increased hydrogen yield by 14.6% over the control (68.39 ml/g-VSfed), while FeCl3 had no effect. Furthermore, the maximum methane yields of methanogenic fermentation were 524.8 and 521.6 ml/g-VSfed with 3.63 g/L MoO42- and 0.6 g/L FeCl3 compared to 466.07 ml/g-VSfed of the control. The maximum yields of biohythane and energy were 796.7 ml/g-VSfed and 21.8 MJ/kg-VSfed with 0.6 g/L FeCl3 when the sulfate removal efficiency was 66.7%, and H2S content was limited at 0.08%. Therefore, adding 0.6 g/L FeCl3 is the most beneficial in improving energy recovery and sulfate removal with low H2S content.

Combination of ultrasonic and acidic pretreatments for enhancing biohythane production from tofu processing residue via one-stage anaerobic digestion.

Tofu processing residues (TPR) have received more attention as a source of bioenergy. However, their low solubility has hindered biohythane generation. Consequently, the ultrasonic and H2SO4 pretreatments were combined and compared for the first time to improve the hydrolysis of organic matter and carbohydrate and increase free amino nitrogen generation from TPR. Besides, the impact of pretreatments on biohythane generation was investigated. Under the optimal conditions of 7.54% substrate level, 8% H2SO4 concentration, 80 °C and 50 min, the coincident ultrasonic-H2SO4 pretreatment enriched the contents of soluble chemical oxygen demand, reducing sugar, and free amino nitrogen to 49675 mg/L, 26 g/L, and 1721 mg/L, respectively, greater than individual pretreatments. Also, Biohythane yield increased by 4.24-13.61% over control (389.42 ± 23.7 ml/g-VSfed). Furthermore, hydrogen yield at 42.5 ± 2.08 and 28.1 ± 1.07 ml/g-VSfed and sulfate removal efficiency at 93 and 92% were significantly improved with ultrasonic-H2SO4 and H2SO4 pretreatments, respectively, indicating acidogenic and sulfidogenic activity enhancement.

Scalable Production of Boron Quantum Dots for Broadband Ultrafast Nonlinear Optical Performance.

A simple and effective approach based on the liquid phase exfoliation (LPE) method has been put forward for synthesizing boron quantum dots (BQDs). By adjusting the interactions between bulk boron and various solvents, the average diameter of produced BQDs is about 7 nm. The nonlinear absorption (NLA) responses of as-prepared BQDs have been systematically studied at 515 nm and 1030 nm. Experimental results prove that BQDs possess broadband saturable absorption (SA) and good third-order nonlinear optical susceptibility, which are comparable to graphene. The fast relaxation time and slow relaxation time of BQDs at 515 nm and 1030 nm are about 0.394-5.34 ps and 4.45-115 ps, respectively. The significant ultrafast nonlinear optical properties can be used in optical devices. Here, we successfully demonstrate all-optical diode application based on BQDs/ReS2 tandem structure. The findings are essential for understanding the nonlinear optical properties in BQDs and open a new pathway for their applications in optical devices.

Effects of Hydrothermal Pretreatment and Hydrochar Addition on the Performance of Pig Carcass Anaerobic Digestion.

Proper disposal and utilization of dead pig carcasses are problems of public concern. The combination of hydrothermal pretreatment (HTP) and anaerobic digestion is a promising method to treat these wastes, provided that digestion inhibition is reduced. For this reason, the aim of this work was to investigate the optimal HTP temperature (140-180°C) for biogas production during anaerobic digestion of dead pigs in batch systems. In addition, the effects of hydrochar addition (6 g/L) on anaerobic digestion of pork products after HTP in continuous stirred tank reactors (CSTR) were determined. According to the results, 90% of lipids and 10% of proteins present in the pork were decomposed by HTP. In addition, the highest chemical oxygen demand (COD) concentration in liquid products (LP) reached 192.6 g/L, and it was obtained after 170°C HTP. The biogas potential from the solid residue (SR) and LP was up to 478 mL/g-VS and 398 mL/g-COD, respectively. A temperature of 170°C was suitable for pork HTP, which promoted the practical biogas yield because of the synergistic effect between proteins and lipids. Ammonia inhibition was reduced by the addition of hydrochar to the CSTR during co-digestion of SR and LP, maximum ammonia concentration tolerated by methanogens increased from 2.68 to 3.38 g/L. This improved total biogas yield and degradation rate of substrates, reaching values of 28.62 and 36.06%, respectively. The acetate content in volatile fatty acids (VFA) may be used as an index that reflects the degree of methanogenesis of the system. The results of the present work may also provide guidance for the digestion of feedstock with high protein and lipid content.

Electrochemical mitigation of hydrogen sulfide in deep-pit swine manure storage.

Hydrogen sulfide (H2S) is a toxic and hazardous gas and is commonly present in livestock operations, which occasionally causes associated exposure accidents. This study evaluated the effectiveness of electrochemical control of H2S in lab-scale swine manure storage using different electrode materials, and further selected suitable materials to demonstrate the performance of a pilot-scale field test in the deep-pit manure storage of a 200-head swine barn. In the lab-scale test, electrochemical sulfide oxidation mainly contributed to the H2S mitigation, resulting in high H2S removal efficiencies when using low carbon steel (LCS) and stainless steel 304 (SS304) as electrodes. Based on their better H2S treatment performance and lower material costs, LCS and SS304 were selected for the pilot-scale test. In a 92-day operation, the pilot-scale demonstration showed H2S removal efficiencies of 84.0% and 63.5% for LCS and SS304, respectively. A techno-economic assessment indicated that the installation and operation of the electrochemical system accounted for 16% of barn construction cost using LCS as electrodes. Further optimization may substantially decrease the electrode material consumption and the overall cost.

The Flame-Retardant Mechanisms and Preparation of Polymer Composites and Their Potential Application in Construction Engineering.

Against the background of people's increasing awareness of personal safety and property safety, the flame retardancy (FR) of materials has increasingly become the focus of attention in the field of construction engineering. A variety of materials have been developed in research and production in this field. Polymers have many advantages, such as their light weight, low water absorption, high flexibility, good chemical corrosion resistance, high specific strength, high specific modulus and low thermal conductivity, and are often applied to the field of construction engineering. However, the FR of unmodified polymer is not ideal, and new methods to make it more flame retardant are needed to enhance the FR. This article primarily introduces the flame-retardant mechanism of fire retardancy. It summarizes the preparation of polymer flame-retardant materials by adding different flame-retardant agents, and the application and research progress related to polymer flame-retardant materials in construction engineering.

Low-voltage electrochemical treatment to precipitate sulfide during anaerobic digestion of beet sugar wastewater.

Sugar beet processing generates a large amount of wastewater with a high chemical oxygen demand (COD). During wastewater storage and treatment, the hydrogen sulfide (H2S) generated from anaerobic digestion (AD) poses unique safety and environmental challenges due to air emissions to the local environment. A new approach of low-voltage electrochemical treatment using low-cost sacrificial anode material was developed in this study to remove sulfide, maintain a proper pH, and produce low-H2S biogas during the AD of beet sugar wastewater. The wastewater collected was categorized as the medium or high strength wastewater depending on the COD content. By using the medium strength wastewater as the test media, the effects of electrochemical and storage conditions, including the applied voltage, immersed electrode area, initial sulfate level, and operating temperature, on the sulfide removal were studied. The effective electrical charge consumption ranged from 6.0 to 14.4 C·mg-1 S2-, and the headspace H2S concentration was reduced by over 96% for most conditions after 204 h treatment. During the 10-week experiment on high strength wastewater, intermittent electrochemical treatment at 0.7 V applied voltage and 1.2 cm2·L-1 electrode area for two weeks reduced the H2S content in the biogas by up to 96%. The cathodic hydroxyl anion generation during the electrochemical treatment significantly increased the pH from 4.61 to 6.95 and led to earlier biogas production than the one without electrochemical treatment. This technique may feasibly be applied in the AD of other sulfur-compound-rich waste streams.

Anaerobic co-digestion of fish processing waste with a liquid fraction of hydrothermal carbonization of bamboo residue.

The effect of different mixing ratios of fish processing waste (FPW) with a liquid fraction (LF) of hydrothermal carbonization (HTC) of bamboo residues on biogas and methane yield was investigated. The different mixing ratios (FPW + LF) and HTC temperature (200-280 °C) had significant effects on biogas and methane production. The anaerobic co-digestion of the various mixing ratio of FPW and LF of bamboo residues did not enhance the methane yield compared to the AD of FPW alone. However, a mixture of 75FPW + 25LF(2 2 0) presented a comparable methane production (133 mL/g VS) to that achieved with 100FPW (142 mL/g VS), which represents an increase of only 6.4%. The ratio of 75FPW + 25LF(2 2 0) increased the biogas yield by 81% compared to the control group of 100LF(2 2 0). The mixing ratio of 75 FPW + 25LF(2 2 0) did not require clean water input to dilute FPW for biogas production and can be a practical waste management method.

Study of food waste degradation in a simulated septic tank.

Septic systems are typically designed to treat domestic wastewater from households without access to centralized facilities. The installation of a food waste disposer (FWD) may increase the discharge of food waste (FW) into the wastewater; therefore, the installation of a FWD is discouraged in households that have a septic system. This study was conducted to determine how a typical dose of FW from a FWD can affect the performance of a septic system in terms of sewage treatment and solids accumulation. A 20-L control tank was compared with an experiment tank to which FW was added, increasing the amount of total suspended solids (TSS) by 31.3% and total chemical oxygen demands by 46.3% for a period of 110 days. Although the influent water quality changed dramatically, the effluent from the experiment tank had a substantially lower percentage increase in water quality parameters compared with the effluent from the control. It was found that in the experiment tank, 75.8% of FW TSS was degraded, whereas only 36.7% of sewage TSS was degraded, and that 18.8% of FW TSS and 44.9% of sewage TSS accumulated in the experiment tank. The addition of FW increased the scum accumulation, even though the dry matter of the scum layer was much less in quantity than the sludge layer. It also increased the lipid content in the sludge. The increase in the scum layer was mainly due to the increase in protein from the addition of the FW. Overall, compared with sewage TSS, FW TSS tends to be more biodegradable, which indicates that the impact on pumping frequency from adding FW will be insignificant.

Effect of bamboo hydrochar on anaerobic digestion of fish processing waste for biogas production.

The effect of hydrothermal carbonization (HTC) temperature and bamboo hydrochar (BHC) addition on biogas production in anaerobic digestion of fish processing waste (FPW) was studied. HTC temperature (200-280 °C) had significant effects on methane yield and content, but the BHC had little effects. The maximum biogas yield observed with HTC at 200 °C and a BHC adding ratio of 1:2 (dry mass ratio of FPW to BHC) reached 292 L/kg volatile solids (VS), which were 64% higher than the control group with only FPW, with the maximum methane yield of 219 L/kg-VS and highest net methane energy yield of 3410 kJ/kg-VS. The obtained results can be used to design an efficient anaerobic digestion process for treating and effectively utilizing fish processing waste.

Effect of hydrochar on anaerobic digestion of dead pig carcass after hydrothermal pretreatment.

Incineration and burial are the current practices for pig carcasses disposal but are not environmentally friendly. Anaerobic digestion can be a better alternative if the process inhibition by carcass digestion can be ameliorated. This study successfully mitigated the inhibition in anaerobic digestion of carcasses by hydrochar addition and by co-digestion with RS and HRS. Biogas production from SP of the pretreated hydrothermal carcasses was enhanced by 60.7 to 90.8% through hydrochar addition. The highest biogas production of 450 mL/g-VS was obtained at 4 g-hydrochar/L addition. The methane content was also increased from 57.5% to up to 69.8%. Each gram of hydrochar removed 25 mg of ammonium and 50 mg of VFA. Hydrochar addition promoted the conversion of VFA to biogas by strengthening the intensity of functional groups and the immobilization of microbial biomass. Co-digestion of SP with RS or HRS also increased the biogas production, and the optimal production of 428 mL/g VS was obtained at 70% SP and 30% RS. The co-digestion of carcass SP with RS and the addition of hydrochar can be a promising solution for improving biogas production from a pig carcass, and can be potentially developed as a sustainable waste management method.

Electricity generation and nutrients removal from high-strength liquid manure by air-cathode microbial fuel cells.

Air-cathode microbial fuel cells (MFCs) are widely tested to recover electrical energy from waste streams containing organic matter. When high-strength wastewater, such as liquid animal manure, is used as a medium, inhibition on anode and cathode catalysts potentially impairs the effectiveness of MFC performance in power generation and pollutant removal. This study evaluated possible inhibitive effects of liquid swine manure components on MFC power generation, improved liquid manure-fed MFCs performance by pretreatment (dilution and selective adsorption), and modeled the kinetics of organic matter and nutrients removal kinetics. Parameters monitored included pH, conductivity, chemical oxygen demand (COD), volatile fatty acids (VFAs), total ammoniacal nitrogen (TAN), nitrite, nitrate, and phosphate concentrations. The removals of VFA and TAN were efficient, indicated by the short half-life times of 4.99 and 7.84 d, respectively. The mechanism for phosphate decrease was principally the salt precipitation on cathode, but the removal was incomplete after 42-d operation. MFC with an external resistor of 2.2 kΩ and fed with swine wastewater generated relatively small power (28.2 µW), energy efficiency (0.37%) and Coulombic efficiency (1.5%). Dilution of swine wastewater dramatically improved the power generation as the inhibitory effect was decreased. Zeolite and granular activated carbon were effective in the selective adsorption of ammonia or organic matter in swine wastewater, and so substantially improved the power generation, energy efficiency, and Coulombic efficiency. A smaller external resistor in the circuit was also observed to promote the organic matter degradation and thus to shorten the treatment time. Overall, air-cathode MFCs are promising for generating electrical power from livestock wastewater and meanwhile reducing the level of organic matter and nutrients.

[Discussion of the Application and Influence Factors of Low-Background Gamma Spectrometry in Distinguishing Sedimentary Rock Types].

The contents of radionuclides uranium, thorium and potassium in the sedimentary rocks mainly depend on the contents of clay in the rocks. And the content of clay is the main basis for distinguishing types of sedimentary rock. Therefore, the value of specific activity or content of uranium, thorium and potassium can be as the quantitative index to distinguish sedimentary rock type. The specific activity or content of radionuclides uranium, thorium and potassium with the method of low-background gamma spectrometry can distinguish the type of rock quickly and accurately. Because of the influence of geometry, mass and moisture content in the sample, the accuracy of distinguishing types of rocks is influenced. This paper makes a theoretical discussion and experimental verification on the influence of mass and moisture content on the results of low-background gamma spectrometry. Results show that there is a linear relationship between (cps) of characteristic peak of all radionuclides and the mass of sample while different energy ranges and lithologies have different linear coefficient and trend fitting degree; The moisture content which is no more than 10%(while collecting samples, the moisture content is no more than 10%) has a little influence on the measurement results( the change values are within the twice standard deviation), so the moisture content which has no significant influence on the accuracy of distinguishing types of sedimentary rock using the method of low-background gamma spectrometry could not be considered. The distinguishing experiment of drilling cuttings samples collected from one oil and gas exploration area in Shanxi Dingbian is done. By the mass correction of the measured data, normalized (cps) ((cps) of per unit mass) of uranium, thorium and potassium channel can only roughly divide the types of sedimentary rocks. Therefore, synthetic distinguishing mode is established with (cps) of combination peak of characteristic peak of uranium, thorium and potassium. The type of rocks is further subdivided, and the distinguishing accuracy is more than 75%.