Synergistic Improvement of Production, Economic Return and Sustainability in the Tea Industry through Ecological Pest Management

The use of ecological principles to manage plant pests has attracted renewed attention, but our knowledge related to the contributions of ecological pest management to social and natural sustainability is fragmented. In this study, we compared the performance and resilience of tea production and the economic benefits of tea ecological management (TEM) and tea conventional management (TCM). We show that TEM significantly improved tea biomass and quality, nutritional efficiency, and beneficial insects, but reduced seasonal variation. As a result, economic return increased by $8045/ha in the TEM mode compared to$6064/ha in the TCM mode. These results confirm that TEM is a promising production mode that can reconcile the conflict between the immediate and long-term service of agriculture. However, environmental improvements associated with organic pest control benefit society, and the government should provide adequate financial support to promote the production system

Physiological responses to drought in three provenances of Discorea nipponica Makino

Dioscorea nipponica Makino is an optimal candidate to develop the diosgenin industry in North China. Given the large fluctuations in soil water availability induced by global climate change, information on drought tolerance of this species is urgently needed. Thus, seedlings of three provenances, selected from Manghe, Pangquangou nd Luyashan Nature Reserves in Shanxi Province, were exposed to 70%-85%, 55%-60%, 40%-45% and 20%-35% of water holding capacity, representing normal-watered, light drought stress, moderate drought stress and severe drought stress, respectively. Thirteen indices concerning plant water status, photosynthesis, antioxidants and osmotic regulation were recorded. Principal Component Analysis was applied to identify indices with a high contribution to drought tolerance, fulfilled by the average of subordinate function values (Xij) of drought tolerance index (Xij). We found that rhizome-propagated seedlings of D. nipponica Makino could survive eighty days of severe drought. The drought tolerance of this species is achieved mainly through physiological responses including decreased photosynthesis, increased activity of antioxidant enzymes, and accumulation of osmotic regulating compounds. The means of drought tolerance index for the provenances Manghe, Pangquangou and Luyashan were 0.29, 0.68 and 0.50, respectively. Pangquangou provenance showed higher drought tolerance than the other two, indicating that it might be a good candidate for cross breeding to combat the increasing drought climate in Shanxi Province

Random forest model based fine scale spatiotemporal O₃ trends in the Beijing-Tianjin-Hebei region in China, 2010 to 2017

Ambient ozone (O₃) concentrations have shown an upward trend in China and its health hazards have also been recognized in recent years. High-resolution exposure data based on statistical models are needed. Our study aimed to build high-performance random forest (RF) models based on training data from 2013 to 2017 in the Beijing-Tianjin-Hebei (BTH) region in China at a 0.01 ° × 0.01 ° resolution, and estimated daily maximum 8h average O₃ (O₃-8hmax) concentration, daily average O₃ (O₃-mean) concentration, and daily maximum 1h O3 (O3-1hmax) concentration from 2010 to 2017. Model features included meteorological variables, chemical transport model output variables, geographic variables, and population data. The test-R² of sample-based O₃-8hmax, O₃-mean and O₃-1hmax models were all greater than 0.80, while the R² of site-based and date-based model were 0.68–0.87. From 2010 to 2017, O₃-8hmax, O₃-mean, and O₃-1hmax concentrations in the BTH region increased by 4.18 μg/m³, 0.11 μg/m³, and 4.71 μg/m³, especially in more developed regions. Due to the influence of weather conditions, which showed high contribution to the model, the long-term spatial distribution of O₃ concentrations indicated a similar pattern as altitude, where high concentration levels were distributed in regions with higher altitude

Optimization of a static headspace GC-MS method and its application in metabolic fingerprinting of the leaf volatiles of 42 citrus cultivars

Citrus leaves, which are a rich source of plant volatiles, have the beneficial attributes of rapid growth, large biomass, and availability throughout the year. Establishing the leaf volatile profiles of different citrus genotypes would make a valuable contribution to citrus species identification and chemotaxonomic studies. In this study, we developed an efficient and convenient static headspace (HS) sampling technique combined with gas chromatography-mass spectrometry (GC-MS) analysis and optimized the extraction conditions (a 15-min incubation at 100 ˚C without the addition of salt). Using a large set of 42 citrus cultivars, we validated the applicability of the optimized HS-GC-MS system in determining leaf volatile profiles. A total of 83 volatile metabolites, including monoterpene hydrocarbons, alcohols, sesquiterpene hydrocarbons, aldehydes, monoterpenoids, esters, and ketones were identified and quantified. Multivariate statistical analysis and hierarchical clustering revealed that mandarin (Citrus reticulata Blanco) and orange (Citrus sinensis L. Osbeck) groups exhibited notably differential volatile profiles, and that the mandarin group cultivars were characterized by the complex volatile profiles, thereby indicating the complex nature and diversity of these mandarin cultivars. We also identified those volatile compounds deemed to be the most useful in discriminating amongst citrus cultivars. This method developed in this study provides a rapid, simple, and reliable approach for the extraction and identification of citrus leaf volatile organic compound, and based on this methodology, we propose a leaf volatile profile-based classification model for citrus

Long-term exposure to ambient fine particulate matter and fasting blood glucose level in a Chinese elderly cohort

Fasting blood glucose level is the primary indicator for the diagnosis of diabetes. We aim to conduct a longitudinal study on the association between long-term fine particulate matter (PM2.5) exposure and fasting blood glucose concentrations. We recruited and followed up 1449 participants older than 65 years of age in 2009, 2012, 2014, and 2017 in eight counties in China. Fasting blood glucose was repeatedly measured 3697 times in total among these participants. Data on annual ground-level PM2.5 concentrations with a 0.01° spatial resolution from 2005 to 2016 were used to assess exposures. An increase of 10 μg/m3 in 3-year average exposure to PM2.5 was associated with an increase of 0.146 mmol/L (95% confidence interval [CI]: 0.045, 0.248) in fasting blood glucose in all participants. The association was more pronounced among the subgroup with diabetes compared to the subgroup without diabetes (P < .05). In conclusion, Long-term PM2.5 exposure was associated with an increase in fasting blood glucose levels among elderly people. Elderly individuals with diabetes are particularly vulnerable to high level exposures of PM2.5. SUMMARY: Long-term PM2.5 exposure was associated with an increase in fasting blood glucose levels among elderly people. Elderly individuals with diabetes are particularly vulnerable to high level exposures of PM2.5. Keywords: elderly; fasting blood glucose; fine particulate matter; long-term exposur

A Random Forest Model for Daily PM2.5 Personal Exposure Assessment for a Chinese Cohort

Errors in air pollution exposure assessment are often considered as a major limitation in epidemiological studies. However, it is difficult to obtain accurate personal level exposure on cohort populations due to the often prohibitive expense. Personal exposure estimation models are used in lieu of direct personal exposure measures but still suffer from issues of availability and accuracy. We aim to establish a personal PM2.5 exposure assessment model for a cohort population and assess its performance by applying our model on cohort subjects. We analyzed data from representative sites selected from the subclinical outcomes of polluted air in China (SCOPA-China) cohort study and established a random forest model for estimating daily PM2.5 personal exposure. We also applied the model among subjects recruited in the project mentioned above within the same area and study period to estimate the reliability of the model. The established model showed a good fit with an R2 of 0.81. The model application results showed similar patterns with empirically measured data. Our pilot study provided a validated and feasible modeling approach for assessing daily personal PM2.5 exposure for large cohort populations. The promising model framework can improve PM2.5 exposure assessment accuracy for future environmental health studies of large populations

Novel Method for in Situ Monitoring of Organophosphorus Flame Retardants in Waters

Widespread use of organophosphorus flame retardants (OPFRs) and their ubiquity in water results in the need for a robust and reliable monitoring technique to better understand their fate and environmental impact. In situ passive sampling using the diffusive gradients in thin-films (DGT) technique provides time-integrated data and is developed for measuring OPFRs here. Ultrasonic extraction of binding gels in methanol provided reliable recoveries for all tested OPFRs. Diffusion coefficients of TCEP, TCPP, TDCPP, TPrP, TBP, and TBEP in the agarose diffusive gel (25 °C) were obtained. The capacity of an HLB binding gel for OPFRs was >115 μg per disc, and the binding performance did not deteriorate with time up to 131 days. DGT performance is independent of typical environmental ranges of pH (3.12-9.71), ionic strength (0.1-500 mmol L -1 ), and dissolved organic matter (0-20 mg L -1 ), and also of diffusive layer thickness (0.64-2.14 mm) and deployment time (3-168 h). Negligible competition effects between OPFRs was found. DGT-measured concentrations of OPFRs in a wastewater treatment plant (WWTP) effluent (12-16 days) were comparable to those obtained by grab sampling, further verifying DGT's reliability for measuring OPFRs in waters