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Pollution generated by livestock and poultry rearing is an important environmental issue, and gas emissions during animal production are continuously increasing. A digital rearing chamber inspection system was designed in the present study in order to examine the waste tea litter's impact on the growth performance and harmful gas emissions, such as ammonia (NH3) and carbon dioxide (CO2), during broiler rearing. Broilers were raised without litter and with waste tea litter. According to the results, broiler growth showed little difference between the two groups during the experimental period, and it was concluded that waste tea litter had no impact on broiler growth. Meanwhile, the gas emissions of the waste tea-litter group were lower than the non-bedding-materials group. In detail, the average concentrations of NH3 and CO2 of the non-bedding-materials group were 9.33 ± 3.65 ppm and 797 ± 107 ppm, respectively; while these concentrations in the waste-tea-litter group were 1.01 ± 0.35 ppm and 713 ± 69 ppm, respectively. According to the analysis of the litter properties, it was suggested that waste tea litter can reduce the moisture content in litter, and affect microbial and urease activity due to its low carbon nitrogen ratio (C/N), weak acid, and porous structure characteristics. In conclusion, this study showed the potential of waste tea litter in NH3 and CO2 emission reduction during broiler rearing. [ABSTRACT FROM AUTHOR]

With the development of Chinese large-scale and intensive livestock production, the animal stocking density increases, resulting in a lot of pollutant gas emissions. They are not only the important sources of greenhouse gas (GHG) emissions such as carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), but also the sources of nitrogen or sulfur organic odors such as hydrogen sulfide (H2S), ammonia (NH3), mercaptan, phenol, paracresol, indole, skatole, which are produced by manure fermentation and decomposition. These gases contain large amounts of toxic and hazardous ingredients. If the concentration of pollution gas is small, the gas can be diluted by diffusion after emitting into the air. If the gas fails to be cleaned up or improperly handled, the odors will keep increasing and gather together. These gases will affect the growth of livestock and poultry, and they will cause environmental pollution, seriously affecting the air quality in urban and rural areas when these contaminated gases largely diffuse into the atmosphere. The environment could be deteriorating; the health of the feeders and residents also could be influenced. This paper reviewed the characteristics of several typical pollutant gases mainly including NH3, H2S, volatile organic compounds (VOCs) and other toxic and harmful gases. We also reviewed the research status of the pollution detection methods and analytical instruments at home and abroad for determining pollutant gas discharged from large-scale livestock and poultry breeding. Along with the development of computer technology, spectral analysis technology, sensor technology and wireless communication technology, there are more researchers applying the novel techniques on pollutant gas emissions from livestock farms in the domestic and foreign. This review synthesized the development of the methods and analyzers for the component and concentration detection of the gases emitted from livestock farms. According to the principal of the detection methods, the detection methods can be classified into optical methods and chemical methods. Optical methods can be divided into two types. One is the conventional optical method that determines the concentration of the pollution gas through measuring the light intensity change; the other is the spectral method that obtains the spectral information on the pollution gas using the spectrum analyzer. Chemical methods mainly include electrochemical method, chemiluminescence method, chromatography and mass spectrometry. In accordance with the measurement methods we summarized the type and origin of the instruments, the corresponding usage in the researches and the research findings using these instruments. In the end we compared the technical characteristics and application between internal and external situation. The goal of this review is for providing the basis to quick and accurate detection methods of the pollutant gases, which include the gases composition and concentration determination, and gives a reference for the development of pollution gas detection technology in livestock farming. To develop detection technology and integration system in situ, which can simultaneously detect all varieties of pollution gases emitted from livestock husbandry, will be the direction for the instrument and equipment development of livestock farm's gas emission detection in future. [ABSTRACT FROM AUTHOR]

Nondestructive detection of the soluble solid content (SSC) is very important to determine the internal quality of watermelon. To enhance the competition of the Chinese equipment manufacturing industry in fruit quality detection, and to improve the benefits of domestic fruit production and processing enterprises, the watermelon, a widely planted thick skinned variety, was selected as the study object. In the study of near-infrared spectra based detective technology of SSC, the spectra collection at different position on the watermelon could result in the variation of precision for the predictive mode by the influencing the spectral signal. In this work, 222 samples were collected at harvest time. The spectra was acquired from the calyx, equator and stem parts of each sample melon. After spectra acquisition, all watermelons were cut into halves from the stem end to the calyx end, and edible portions were removed and cut into proper pieces for obtaining watermelon juice by a juicer. The different spectral data sets were then used as the different inputs of the linear algorithm (partial least squares, PLSR) and nonlinear algorithm (least squares support vector machine, LS-SVM). The 214 samples were retained after getting rid of the abnormal samples; 143 and 71 samples were set aside as the calibration set and prediction set, respectively. The predictive abilities of the different model was compared after the SSC calibration models were established. Both the PLSR models and LS-SVM models showed that the models using the spectra collected from the melon equator as input had the worst performance, while the models using the spectra collected at the calyx were the best. For the calyx collected spectra based PLSR model, the correlation coefficient (rpre) was 0.823, and the root mean square error of prediction (RMSEP) was 0.652 percent. The calyx collected spectra based PLSR model was better than the calyx collected spectra based LS-SVM model with a rpre of 0.768 and a RMSEP of 0.731 percent. For stem collected spectra based models, the predictive results were close to the calyx collected spectra based models. It was proposed that the spectra at the calyx part of watermelon should be acquired for our home-built detection system. This work illustrated how the spectra acquired at different parts of watermelons impact the final detection accuracy of the predictive model, but the methods needed to reduce or eliminate this phenomenon require further study. [ABSTRACT FROM AUTHOR]