SOIL MANAGEMENT AND NITROGEN DYNAMICS IN BURLEY TOBACCO ROTATIONS

Agronomic practices, including tillage, crop rotation and N fertilization, have been developed to efficiently manage soil N dynamics and crop N nutrition. These practices can affect soil organic carbon (SOC) and soil total nitrogen (STN) sequestration, and consequently influence soil nitrogen mineralization (SNM) and crop N nutrition. However, little research has been systematically and simultaneously conducted to examine the effect of agronomic management on (1) SOC and STN stocks; (2) SNM; and (3) crop N nutrition. Burley tobacco (Nicotiana tobacum L.) is a N demanding crop and subject to inefficiency in N fertilization. Moreover, conservation tillage and rotation have been integrated into traditionally tillage intensive tobacco cropping systems. Thus, a tobacco tillage and rotation study was used to test how agronomic practices can affect N dynamics and crop N status in a series of sequential experiments. Firstly, different tobacco production systems were utilized to investigate the effects of tillage and rotation on soil aggregate stabilization and associated SOM sequestration. No-tillage and rotation management enhanced SOC and STN stocks, mainly by increasing the proportion of macroaggregates and SOC and STN concentrations. Secondly, a series of studies were conducted on SNM, including: (1) comparison of laboratory and in situ resin-core methods in estimating SNM; (2) evaluation of the influence of N fertilizer application on SNM; and (3) comparison of chemical indices for predicting SNM across management treatments over time. Laboratory method had different results relative to in situ method due to sample pretreatments. Fertilizer N application had a priming effect on SNM, but priming depended on both the N fertilizer rate and the background SOM level. The effect of rotation/tillage treatments on SNM was stable across years and SOC appeared to be the best indicator of SNM among other soil carbon and N estimates. Thirdly, a N fertilizer study for different tillage systems was conducted in 2012 and 2013. Crop parameters and plant available N (PAN) were collected to investigate the impact of tillage on tobacco production. Crop parameters showed that no-tillage can result in N deficiency in dry years. Similar PAN for both tillage methods suggested N deficiency in no-till tobacco was due to the crop’s lower N uptake capacity. In 2014, tobacco root analysis confirmed that no-tillage can result in less root exploration of the soil volume than conventional tillage

Investigation of Haemophilus parasuis from healthy pigs in China

Haemophilus parasuis is a common colonizer of the upper respiratory tract of swine and frequently causes disease, especially in weaner pigs. To date, limited epidemiological data was available for H. parasuis from healthy pigs, which might be carriers of potential pathogenic strains. In this study, from September 2016 to October 2017, we investigated the prevalence and characteristics of H. parasuis from healthy pigs in China. Totally, we obtained 244 isolates from 1675 nasal samples from 6 provinces. H. parasuis isolation was more successful in weaner pigs (22.6%, 192/849), followed by finisher pigs (9.3%, 43/463), and sows (2.5%, 9/363). The most prevalent serovars were 7 (20.1%, 49/244), followed by 3 (14.8%, 36/244), 2 (14.3%, 35/244), 11 (12.7%, 31/244), 5/12 (5.7%, 14/244) and 4 (2.5%, 6/244). Bimodal or multimodal distributions of MICs were observed for most of the tested drugs, which suggested the presence of non-wild type populations. It was noted that the MIC90 values of tilmicosin (64 μg/ml) was relatively higher than that reported in previous studies. Our results suggest that: 1) potentially pathogenic serovars of H. parasuis are identified in healthy pigs, and 2) elevated MICs and presence of mechanisms of resistance not yet described for clinically important antimicrobial agents would increase the burden of disease caused by H. parasuis.info:eu-repo/semantics/acceptedVersio

Relationship of Agronomic Practices to Soil Nitrogen Dynamics

Soil nitrogen (N) dynamics are a major concern of soil nutrient status and its supply for crop uptake and growth. They are a central focus of agroecosystems. Agronomic practices play a central role in regulating soil N dynamics; the methodologies for investigating soil N mineralization are diverse, but debatable. This chapter discusses the pros and cons of different methods for measuring soil N mineralization, including laboratory, in-situ, and modeling procedures. This chapter illustrates the influence of agronomic practices on root architecture that potentially affects crop nutrient uptake. The relationship between agronomic practices and soil N dynamics were fully discussed, which can substantially inform soil fertility and crop nutrition management

Different yellowing degrees and the industrial utilization of flue-cured tobacco leaves

Yellowing is a key stage in the curing of flue-cured tobacco (Nicotiana tobacum L.) as much of the chemical transformation occurs during this period. This study examined the effect of different yellowing degrees on the value of flue-cured tobacco leaves at the farm level for both processing and manufacturing. The study was conducted in the counties of Chuxiong, Dali, and Yuxi in Yunnan, China over two years. Yellowing treatments have been designed to have either a mild or a regular yellowing degree. Yield, value, appearance, suction property, smoking characteristics, and physical resistance to further processing were investigated to evaluate the effect of degree of yellowing on the industrial utilization of flue-cured tobacco leaves. The regular yellowing degree enhanced yield, value, and appearance compared to the mild yellowing degree, regardless of cultivar or location; however, physical resistance to further processing and the suction property of the mild yellowing degree treatment were better than with the regular yellowing degree regardless of cultivar or location. Furthermore, although the regular yellowing degree recorded higher smoking characteristic scores than the mild yellowing degree immediately after flue-curing, the scores of mild yellowing degree leaves could be further augmented by increasing intensity in the re-drying stage. The smoking characteristic score in the regular yellowing degree can only be increased by low intensity re-drying, and significantly decreased by mild and high intensity re-drying. Therefore, in terms of industrial utilization, mild yellowing is the better choice for flue-curing tobacco. This study also suggested that the current regular yellowing stage in Yunnan should be shortened to meet the demands of the traditional tobacco industry

Discrimination of Fresh Tobacco Leaves with Different Maturity Levels by Near-Infrared (NIR) Spectroscopy and Deep Learning

The maturity affects the yield, quality, and economic value of tobacco leaves. Leaf maturity level discrimination is an important step in manual harvesting. However, the maturity judgment of fresh tobacco leaves by grower visual evaluation is subjective, which may lead to quality loss and low prices. Therefore, an objective and reliable discriminant technique for tobacco leaf maturity level based on near-infrared (NIR) spectroscopy combined with a deep learning approach of convolutional neural networks (CNNs) is proposed in this study. To assess the performance of the proposed maturity discriminant model, four conventional multiclass classification approaches—K-nearest neighbor (KNN), backpropagation neural network (BPNN), support vector machine (SVM), and extreme learning machine (ELM)—were employed for a comparative analysis of three categories (upper, middle, and lower position) of tobacco leaves. Experimental results showed that the CNN discriminant models were able to precisely classify the maturity level of tobacco leaves for the above three data sets with accuracies of 96.18%, 95.2%, and 97.31%, respectively. Moreover, the CNN models with strong feature extraction and learning ability were superior to the KNN, BPNN, SVM, and ELM models. Thus, NIR spectroscopy combined with CNN is a promising alternative to overcome the limitations of sensory assessment for tobacco leaf maturity level recognition. The development of a maturity-distinguishing model can provide an accurate, reliable, and scientific auxiliary means for tobacco leaf harvesting

Chromatographic Profiling with Machine Learning Discriminates the Maturity Grades of <i>Nicotiana tabacum</i> L. Leaves

Nicotiana tabacum L. (NTL) is an important agricultural and economical crop. Its maturity is one of the key factors affecting its quality. Traditionally, maturity is discriminated visually by humans, which is subjective and empirical. In this study, we concentrated on detecting as many compounds as possible in NTL leaves from different maturity grades using ultra-performance liquid chromatography ion trap time-of-flight mass spectrometry (UPLC-IT-TOF/MS). Then, the low-dimensional embedding of LC-MS dataset by t-distributed stochastic neighbor embedding (t-SNE) clearly showed the separation of the leaves from different maturity grades. The discriminant models between different maturity grades were established using orthogonal partial least squares discriminant analysis (OPLS-DA). The quality metrics of the models are R2Y = 0.939 and Q2 = 0.742 (unripe and ripe), R2Y = 0.900 and Q2 = 0.847 (overripe and ripe), and R2Y = 0.972 and Q2 = 0.930 (overripe and unripe). The differential metabolites were screened by their variable importance in projection (VIP) and p-Values. The existing tandem mass spectrometry library of plant metabolites, the user-defined library of structures, and MS-FINDER were combined to identify these metabolites. A total of 49 compounds were identified, including 12 amines, 14 lipids, 10 phenols, and 13 others. The results can be used to discriminate the maturity grades of the leaves and ensure their quality

On Market Equilibrium Analysis

In this paper we develop the implications of competitive market equilibrium for production and household behavior when some prices are endogenously determined. The properties of market equilibrium functions are explored, including the effects of pricing policy. A Slutsky-type equation relating compensated and uncompensated market equilibrium functions is derived. Implications for multimarket welfare analysis are presented, focusing on the effects of pricing policy and technical change. Copyright 1997, Oxford University Press.