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يتضمن الكتاب مجموعة مقالات تتحدث عن زراعة الشاي وثقافته الذي يعكس روحا للشعب الصيني فهو ليس قيمة مادية فقط بل قيمة روحية أيضا على مدلولات ثقافية فريدة تميز الصينيين. إن عملية فهم ثقافة الشاي الصينية هي في الوقت ذاته عملية فهم التاريخ الصيني والثقافة الصينية وروح الشعب الصيني إلى حد ما. يقدم إلينا وانغ شو فينغ في هذا الكتاب العديد من رجال الشاي وكان من بينهم شينونغ مع قرون الثور في الأزمنة القديمة وتشانغ داي الذي أشبع اشتهاءه للشاي بواسطة شم رائحته في مملكتي مينغ وتشينغ ولويو الذي كان يلقب للشاي وإذا كان باستطاعه المرء زيارة إحدى بقديس الشاي في أيام مملكة تانغ ووو جو نونغ والذي كان قديسا معاصرا حدائق الشاي فإنه سوف يكتشف رجال الشاي والذين دعموه بكل قواهم.

Climate change and human activities have already caused degradation in a large fraction of vegetation on the Qinghai‐Tibetan Plateau (QTP). Many studies report that climate variability instead of overgrazing has been the primary cause for large‐scale vegetation cover changes on the QTP, for example, Lehnert et al., 2016, https://doi.org/10.1038/srep24367. However, it remains unclear how human activities (mainly livestock grazing) regulate vegetation dynamics under climate change. This paper takes the AVHRR/GIMMS Normalized Difference Vegetation Index (NDVI) as an indicator to analyze the growth status of vegetation zones in the QTP, which has highly sensitive to climate change. The spatiotemporal dynamics of vegetation growth between 1981 and 2015 were analyzed. The dual effects of climate change and human activities were examined by correlation analyses of data from 87 meteorological stations and economic statistical data of the QTP. Results show that: (a) The vegetation in central and southwestern QTP with high altitudes was improving due to the warm‐humid climate trend. An increase in temperature and a reduction in the harsh frigid climate at high altitudes due to global warming has resulted in expansions of the vegetated areas, with the NDVI showing a concordant increase. (b) The degraded areas were mainly confined to the northern and eastern QTP, which have high human and livestock population densities. In comparison to gently changing climate regimes, anthropogenic activities such as chronic concentration of population and livestock in the valleys with a less harsh climate exerts a much stronger pressure on vegetation. The study indicates that the anthropogenic pressures are much more intensive than the impact of climate change and are critical for the conservation and sustainable management of the QTP vegetation. Plain Language Summary Vegetation dynamics and its type are considered to be critical indicators of different climate regimes and have received significant attention from ecologists and climatologists. However, studies on the shift in vegetation toward higher altitudes and higher latitudes with climate warming from the vegetation zone redistribution perspective are relatively scarce. Our results suggest that the degraded areas of vegetation were mainly confined to the northern and eastern Qinghai‐Tibetan Plateau (QTP), which have high human and livestock population densities. In comparison to gently changing climate regimes, anthropogenic activities such as chronic concentration of population and livestock in the relatively less harsh valleys exerts a much stronger pressure on vegetation. Anthropogenic pressures were therefore found to be far more intensive than the impact of climate change and they were the big threats to the sustainability of the QTP. Key Points The vegetation with high altitudes was improving due to the warm‐humid climate trend The degraded vegetation areas were mainly confined to high human and livestock population densities Anthropogenic activities such as chronic concentration of population and livestock exerts a much stronger pressure on vegetation

This volume provides the most recent technology for sensing and automation in apple production cycle in terms of bagging robotics, flower pollination robotics, pruning robotics, and harvest robotics. It does not only summarise the development of technology progress, but also discuss the future trend for unmanned apple production cycle. Though apple production still mainly relies on manual labour, a huge number of innovative technologies emerge during the past years, which pave the road for unmanned apple orchard management.

Maize (Zea mays subsp mays) was domesticated from its wild ancestor, teosinte (Zea mays subsp parviglumis). Maize’s distinct morphology and adaptation to diverse environments required coordinated changes in various metabolic pathways. However, how the metabolome was reshaped since domestication remains poorly understood. Here, we report a comprehensive assessment of divergence in the seedling metabolome between maize and teosinte. In total, 461 metabolites exhibited significant divergence due to selection. Interestingly, teosinte and tropical and temperate maize, representing major stages of maize evolution, targeted distinct sets of metabolites. Alkaloids, terpenoids, and lipids were specifically targeted in the divergence between teosinte and tropical maize, while benzoxazinoids were specifically targeted in the divergence between tropical and temperate maize. To identify genetic factors controlling metabolic divergence, we assayed the seedling metabolome of a large maize-by-teosinte cross population. We show that the recent metabolic divergence between tropical and temperate maize tended to have simpler genetic architecture than the divergence between teosinte and tropical maize. Through integrating transcriptome data, we identified candidate genes contributing to metabolic divergence, many of which were under selection at the nucleotide and transcript levels. Through overexpression or mutant analysis, we verified the roles of Flavanone 3-hydroxylase1, Purple aleurone1, and maize terpene synthase1 in the divergence of their related biosynthesis pathways. Our findings not only provide important insights into domestication-associated changes in the metabolism but also highlight the power of combining omics data for trait dissection.

The Qilian Mountain ecosystems play an irreplaceable role in maintaining ecological security in western China. Vegetation, as an important part of the ecosystem, has undergone considerable changes in recent decades in this area, but few studies have focused on the process of vegetation change. A long normalized difference vegetation index (NDVI) time series dataset based on remote sensing is an effective tool to investigate large-scale vegetation change dynamics. The MODerate resolution Imaging Spectroradiometer (MODIS) NDVI dataset has provided very detailed regional to global information on the state of vegetation since 2000. The aim of this study was to explore the spatial-temporal characteristics of abrupt vegetation changes and detect their potential drivers in the Qilian Mountain area using MODIS NDVI data with 1 km resolution from 2000 to 2017. The Breaks for Additive Season and Trend (BFAST) algorithm was adopted to detect vegetation breakpoint change times and magnitudes from satellite observations. Our results indicated that approximately 80.1% of vegetation areas experienced at least one abrupt change from 2000 to 2017, and most of these areas were distributed in the southern and northern parts of the study area, especially the area surrounding Qinghai Lake. The abrupt browning changes were much more widespread than the abrupt greening changes for most years of the study period. Environmental factors and anthropogenic activities mainly drove the abrupt vegetation changes. Long-term overgrazing is likely the main cause of the abrupt browning changes. In addition, our results indicate that national ecological protection policies have achieved positive effects in the study area.

The Qilian Mountains (QLM) are an important ecological barrier in western China. High-precision land cover data products are the basic data for accurately detecting and evaluating the ecological service functions of the QLM. In order to study the land cover in the QLM and performance of different remote sensing classification algorithms for land cover mapping based on the Google Earth Engine (GEE) cloud platform, the higher spatial resolution remote sensing images of Sentinel-1 and Sentinel-2; digital elevation data; and three remote sensing classification algorithms, including the support vector machine (SVM), the classification regression tree (CART), and the random forest (RF) algorithms, were used to perform supervised classification of Sentinel-2 images of the QLM. Furthermore, the results obtained from the classification process were compared and analyzed by using different remote sensing classification algorithms and feature-variable combinations. The results indicated that: (1) the accuracy of the classification results acquired by using different remote sensing classification algorithms were different, and the RF had the highest classification accuracy, followed by the CART and the SVM; (2) the different feature variable combinations had different effects on the overall accuracy (OA) of the classification results and the performance of the identification and classification of the different land cover types; and (3) compared with the existing land cover products for the QLM, the land cover maps obtained in this study had a higher spatial resolution and overall accuracy.

Phenology plays a fundamental role in regulating photosynthesis, evapotranspiration, and surface energy fluxes and is sensitive to climate change. The global mean surface air temperature data indicate a global warming hiatus between 1998 and 2012, while its impacts on global phenology remains unclear. Here we use long-term satellite and FLUXNET records to examine phenology trends in the northern hemisphere before and during the warming hiatus. Our results based on the satellite record show that the phenology change rate slowed down during the warming hiatus. The analysis of the long-term FLUXNET measurements, mainly within the warming hiatus, shows that there were no widespread advancing (or delaying) trends in spring (or autumn) phenology. The lack of widespread phenology trends partly led to the lack of widespread trends in spring and autumn carbon fluxes. Our findings have significant implications for understanding the responses of phenology to climate change and the climate-carbon feedbacks. A global warming hiatus occurred during 1998 and 2012 but its effects on phenology are unclear. Here the authors examine the trends in spring and autumn phenology in the northern hemisphere and the effects of the warming hiatus and show that phenology change rate in the northern hemisphere slowed down during the warming hiatus.

Coal mines in Pingdingshan mining area, Henan province, China, are commonly mined at a great depth up to 1000 m, and inevitably reside in high temperature, high pressure, high permeability, strong mining disturbance, and strong time effect environment. Support structures of the mines in the area are vulnerable to failure and destruction while roadway stability has been a long-standing issue in the region. Based on the specimens collected from the roof of the return-air rise at Pingdingshan No.1 coal mine, here, we investigated the creep characteristics of sandy mudstone under triaxial conditions and developed a constitutive relationship to predict the creep behavior. Parameter identification and sensitivity analysis were performed to determine the influential factors of creep deformation. We showed that the creep deformation and steady-state creep rate at Pingdingshan coal region grow as axial stress is elevated while descend with increased confining pressure. However, the maximum creep deformation of sandy mudstone increases with a higher confining pressure. Thereby, stress difference, elastic modulus and coefficient of viscosity are the major parameters controlling creep deformation. Hence, it is important to enhance the support strength and mechanical properties of the surrounding rock, to better the roadway stability. In addition, numerical simulation was also conducted for simple excavation geometries to analyze different support structures. On this basis, the “cable bolts steel arch, deep and shallow reinjection, floor pressure relief and local reinforcement” scheme was proposed and field practice showed promising results. The findings in this study can be used to guide the support design for the deep soft rock roadway (DSRR).

Permafrost, widely distributed in the Northern Hemisphere, plays a vital role in regulating heat and moisture cycles within ecosystems. In the last four decades, due to global warming, permafrost degradation has accelerated significantly in high latitudes and altitudes. However, the impact of permafrost degradation on vegetation remains poorly understood to date. Based on active layer thickness (ALT) monitoring data, meteorological data and normalized difference vegetation index (NDVI) data, we found that most ALT‐monitored sites in the Northern Hemisphere show an increasing trend in NDVI and ALT. This suggests an overall increase in NDVI from 1980 to 2021 while permafrost degradation has been occurring. Permafrost degradation positively influences NDVI growth, with the intensity of the effects varying across land cover types and permafrost regions. Furthermore, based on Mann‐Kendall trend test, we detected abrupt changes in NDVI and environmental factors, further confirming that there is a strong consistency between the abrupt changes of ALT and NDVI, and the consistency between the abrupt change events of ALT and NDVI is stronger than that of air temperature and precipitation. These findings work toward a better comprehending of permafrost effects on vegetation growth in the context of climate change. Plain Language Summary Our research focuses on the influence of permafrost degradation on vegetation in high‐latitude and high‐altitude regions of the Northern Hemisphere. By analyzing permafrost monitoring and vegetation data, we have observed a widespread occurrence of permafrost degradation and vegetation greening in recent years across the Northern Hemisphere. Our analysis has revealed a strong connection between permafrost degradation and vegetation greening in permafrost areas, and the impact varies with different vegetation and permafrost types. In addition, we further investigated the consistency of abrupt changes in the vegetation growth with various environmental factors. It can be seen that despite the significant influence of air temperature changes on vegetation growth in permafrost regions of the Northern Hemisphere, the abrupt change of vegetation growth is consistent with the abrupt change in the process of permafrost degradation, indicating that vegetation growth displays a heightened sensitivity to permafrost degradation. These findings provide valuable insights into the ecological consequences of permafrost changes in high‐latitude and high‐altitude areas under the influence of climate change. Key Points Vegetation in the Northern Hemisphere shows a greening trend, and permafrost shows a degradation trend Permafrost degradation positively influences vegetation growth, with the intensity of the effects varying by vegetation and permafrost types Abrupt changes in vegetation growth are more consistent with abrupt permafrost degradation than with meteorological factors

Vegetation dynamics are critical to the terrestrial carbon and water cycle, with China recognized as one of the largest contributors to global greening due to significant variations in forest coverage. However, distinguishing the effects of vegetation changes from those of climate factors on vegetation productivity remains challenging. This study conducted a comprehensive analysis of vegetation productivity in Northwest China over the past two decades, focusing on the spatiotemporal patterns and drivers of gross primary production (GPP) within ecological restoration areas. Using trend analysis and ridge regression models, we assessed the relative contributions of climate factors and vegetation coverage changes to GPP dynamics. The results revealed a significant increase in both the GPP and vegetation coverage in Northern China from 2001 to 2020, with GPP rising by 6.7 g C m−2 yr−1 and forest coverage increasing by 0.08% per year. A strong positive correlation (r = 0.9) was observed between vegetation coverage changes and GPP. The increase in GPP was driven by both climate factors and changes in forest coverage, with climate factors contributing 61.0% and vegetation coverage changes contributing 39.0%. Among the climate factors, radiation, temperature, and precipitation contributed 15.4%, 6.4%, and 39.2%, respectively. The study highlights the critical role of ecological restoration efforts, particular in regions like the Less Plateau and Inner Mongolian Plateau, in enhancing vegetation productivity. These findings provide valuable insights for addressing desertification and inform strategies for ecological restoration and sustainable development in Northern China.