The accurate identification of oceanic basalts is essential for understanding geological evolution. Traditional discriminant diagrams based on two- or three-element ratios often exhibit indistinct boundaries and limited sample coverage. Utilizing the GEOROC and PetDB databases, we compiled 950 MORB, OIB, and IAB samples. PCA shows that PC1 is mainly associated with enriched elements such as Nb, whereas PC2 corresponds to SiO2 and Al2O3; together, they explain over 60

The East Kunlun Orogenic Belt (EKOB), one of the most important magmatic belts on the Tibetan Plateau, experienced a multicyclic tectonic evolution. In this paper, we present geochemical and geochronological data, especially Fe isotopes for the Triassic granitoids exposed in the EKOB. The granitoids are characterized by relative enrichment of Rb, Pb, U and K and depletion in Nb, Ta and Ti; The granitoid samples show remarkably variable δ56FeIRMM014 values, ranging from – 0.055 ± 0.07 to 0.116 ± 0.03‰, which are among the highest values reported from felsic rocks. These values do not correlate with bulk-rock geochemical indicators of fluid exsolution (e.g., Zr/Hf, Nb/Ta, K/Rb and Rb/La ratios), qualitatively indicating that fluid exsolution has an insignificant effect on Fe isotopic fractionation. The most likely mechanism responsible for the heavy Fe isotopic compositions in the granitoids can be narrowed down to fractional crystallization processes. The combination of Fe isotope and mineral composition suggests that the variation in Fe isotopes in our siliciclastic melts during magmatic evolution is primarily attributed to the removal of isotopically light Fe-bearing minerals (i.e., ilmenite, biotite, amphibole, orthopyroxene and clinopyroxene). Additionally, the zircon U–Pb dating of these granitoids reveals their ages to be approximately 250 Ma. In conjunction with the field observations, petrologic and geochronologic features, we assert that the closure of the A’nyemaqen Paleo-Tethys Ocean occurred during the Triassic period (250 Ma) through the formation of syncollisional granitoids in the EKOB, which represents a snapshot of the continental crustal growth.

Deposition of the Liantuo Formation is closely associated with the evolutionary history of the Rodinia supercontinent, as indicated by the breakup of the Yangtze Craton in South China. In this paper, we also carried out a detailed U-Pb zircon examination of the Liantuo Formation. Radiometric dating of sandstone within the Liantuo Formation suggested that it was deposited ca. 790 Ma, which coordinated with the age-paleopole contradictions in the Liantuo Formation for exploring the evolutionary history of the Yangtze Block during the breakup of the Rodinia supercontinent. All the Liantuo sandstones and shales have variable Sr isotopic compositions, with initial Sr isotope ratios ranging from 0.6920 to 0.7217, which support significant fluvial contributions during the deposition of the Liantuo Formation. Samples of the Liantuo Formation show distinct variations in Nd-Hf isotopic compositions, suggesting that the Nantuo Formation received relatively juvenile materials (e.g., the newly formed Neoproterozoic rocks from the northern margin of the Yangtze Block), whereas the Liantuo Formation received relatively mature inputs (e.g., the Huangling granitoids and/or Kongling complex). The samples from the Liantuo Formation also contain various Pb isotopes (206Pb/204Pb = 17.56-17.76, 207Pb/204Pb = 15.05-15.43 and 208Pb/204Pb = 35.51-36.79). These values are also close to the Pb isotopic compositions of the Kongling complex, which suggest that the sedimentary rocks were enriched (the Kongling complex) and are consistent with the Nd-Hf isotope data. That is, the major provenance of the Liantuo Formation is from the South China Block basement, which is the local Kongling complex. In contrast, the Luoquan diamictite can represent the well-mixed composition of the upper continental crust (UCC) in the North China Block during the Neoproterozoic.

SignificanceThe scientific dataset of agricultural pests and diseases is the foundation for monitoring and warning of agricultural pests and diseases. It is of great significance for the development of agricultural pest control, and is an important component of developing smart agriculture. The quality of the dataset affecting the effectiveness of image recognition algorithms, with the discovery of the importance of deep learning technology in intelligent monitoring of agricultural pests and diseases. The construction of high-quality agricultural pest and disease datasets is gradually attracting attention from scholars in this field. In the task of image recognition, on one hand, the recognition effect depends on the improvement strategy of the algorithm, and on the other hand, it depends on the quality of the dataset. The same recognition algorithm learns different features in different quality datasets, so its recognition performance also varies. In order to propose a dataset evaluation index to measure the quality of agricultural pest and disease datasets, this article analyzes the existing datasets and takes the challenges faced in constructing agricultural pest and disease image datasets as the starting point to review the construction of agricultural pest and disease datasets.ProgressFirstly, disease and pest datasets are divided into two categories: private datasets and public datasets. Private datasets have the characteristics of high annotation quality, high image quality, and a large number of inter class samples that are not publicly available. Public datasets have the characteristics of multiple types, low image quality, and poor annotation quality. Secondly, the problems faced in the construction process of datasets are summarized, including imbalanced categories at the dataset level, difficulty in feature extraction at the dataset sample level, and difficulty in measuring the dataset size at the usage level. These include imbalanced inter class and intra class samples, selection bias, multi-scale targets, dense targets, uneven data distribution, uneven image quality, insufficient dataset size, and dataset availability. The main reasons for the problem are analyzed by two key aspects of image acquisition and annotation methods in dataset construction, and the improvement strategies and suggestions for the algorithm to address the above issues are summarized. The collection devices of the dataset can be divided into handheld devices, drone platforms, and fixed collection devices. The collection method of handheld devices is flexible and convenient, but it is inefficient and requires high photography skills. The drone platform acquisition method is suitable for data collection in contiguous areas, but the detailed features captured are not clear enough. The fixed device acquisition method has higher efficiency, but the shooting scene is often relatively fixed. The annotation of image data is divided into rectangular annotation and polygonal annotation. In image recognition and detection, rectangular annotation is generally used more frequently. It is difficult to label images that are difficult to separate the target and background. Improper annotation can lead to the introduction of more noise or incomplete algorithm feature extraction. In response to the problems in the above three aspects, the evaluation methods are summarized for data distribution consistency, dataset size, and image annotation quality at the end of the article.Conclusions and ProspectsThe future research and development suggestions for constructing high-quality agricultural pest and disease image datasets based are proposed on the actual needs of agricultural pest and disease image recognition:(1) Construct agricultural pest and disease datasets combined with practical usage scenarios. In order to enable the algorithm to extract richer target features, image data can be collected from multiple perspectives and environments to construct a dataset. According to actual needs, data categories can be scientifically and reasonably divided from the perspective of algorithm feature extraction, avoiding unreasonable inter class and intra class distances, and thus constructing a dataset that meets task requirements for classification and balanced feature distribution. (2) Balancing the relationship between datasets and algorithms. When improving algorithms, consider the more sufficient distribution of categories and features in the dataset, as well as the size of the dataset that matches the model, to improve algorithm accuracy, robustness, and practicality. It ensures that comparative experiments are conducted on algorithm improvement under the same evaluation standard dataset, and improved the pest and disease image recognition algorithm. Research the correlation between the scale of agricultural pest and disease image data and algorithm performance, study the relationship between data annotation methods and algorithms that are difficult to annotate pest and disease images, integrate recognition algorithms for fuzzy, dense, occluded targets, and propose evaluation indicators for agricultural pest and disease datasets. (3) Enhancing the use value of datasets. Datasets can not only be used for research on image recognition, but also for research on other business needs. The identification, collection, and annotation of target images is a challenging task in the construction process of pest and disease datasets. In the process of collecting image data, in addition to collecting images, attention can be paid to the collection of surrounding environmental information and host information. This method is used to construct a multimodal agricultural pest and disease dataset, fully leveraging the value of the dataset. In order to focus researchers on business innovation research, it is necessary to innovate the organizational form of data collection, develop a big data platform for agricultural diseases and pests, explore the correlation between multimodal data, improve the accessibility and convenience of data, and provide efficient services for application implementation and business innovation.

As a tectonic block of the Qinling Orogenic Belt, Central China, the South Qinling Orogen is generally believed to have had a tight affinity with the Yangtze Block during the Precambrian. Knowledge on the South Qinling Orogen is important to constrain the tectonic evolution of the northern margin of the Yangtze Block basement. Previous studies mainly focused on the east segment of the South Qinling Orogen. This paper presented petrological, geochronological, and geochemical studies on the amphibolite-facies rocks newly discovered in the middle section of the South Qinling Orogen. Geochemical studies indicate that the protolith of these amphibolites is calc-alkaline island arc basalt, which was formed during the reconstruction of the Paleo-Middle Archean crust on the northern margin of the Yangtze Block 2,362 ± 100 Ma ago (equivalent to metamorphic rocks of the Yudongzi group). Later, these arc basalts experienced amphibolite-facies metamorphism at 1,500–1,800 Ma, which is consistent with the metamorphism identified in the Yangtze Block, confirming the association of the South Qinling Orogen with the Yangtze Block basement. Subsequently, these amphibolite-facies rocks further experienced three stages of metamorphism at c. 800 Ma, 440 Ma, and 200 Ma in the context of the northward subduction of the Yangtze Block.

Anqing six-end-white pig is a native breed in Anhui Province. The pigs have the disadvantages of a slow growth rate, low proportion of lean meat, and thick back fat, but feature the advantages of strong stress resistance and excellent meat quality. Duroc pig is an introduced pig breed with a fast growth rate and high proportion of lean meat. With the latter breed featuring superior growth characteristics but inferior meat quality traits, the underlying molecular mechanism that causes these phenotypic differences between Chinese and foreign pigs is still unclear. In this study, copy number variation (CNV) detection was performed using the re-sequencing data of Anqing Six-end-white pigs and Duroc pigs, A total of 65,701 CNVs were obtained. After merging the CNVs with overlapping genomic positions, 881 CNV regions (CNVRs) were obtained. Based on the obtained CNVR information combined with their positions on the 18 chromosomes, a whole-genome map of the pig CNVs was drawn. GO analysis of the genes in the CNVRs showed that they were primarily involved in the cellular processes of proliferation, differentiation, and adhesion, and primarily involved in the biological processes of fat metabolism, reproductive traits, and immune processes. The difference analysis of the CNVs between the Chinese and foreign pig breeds showed that the CNV of the Anqing six-end-white pig genome was higher than that of the introduced pig breed Duroc. Six genes related to fat metabolism, reproductive performance, and stress resistance were found in genome-wide CNVRs (DPF3, LEPR, MAP2K6, PPARA, TRAF6, NLRP4).

蚜虫的发生是影响农作物产量和质量的重要原因之一.对蚜虫进行检测和计数是对虫害早发现、早治理的重要环节.随着信息技术的发展,已经有专家学者利用计算机视觉感知技术对农业害虫进行识别研究,并取得了 一定的进展.高质量、大规模的基础数据对计算机视觉的发展往往能够起到决定性作用,缺少高质量、大规模的基础图像数据是蚜虫精准识别研究面临的难题.蚜虫是一类重要的农业害虫,具有尺寸微小、密集分布、虫间遮挡和同种多形态等特征,这些特征对于蚜虫的检测与计数又是一项严峻的挑战.本文提供了包括桃粉蚜、桃蚜、棉蚜、禾谷缢管蚜等13种农业蚜虫数据集,共6287张高清原始图像.这些蚜虫图像是利用单反相机在自然大田环境中采集、以文件夹形式进行存储、经过从事图像数据管理的专业人员清洗和整理、并由植保专家对其进行鉴定和分类的,保障了数据的高质量和可靠性.该数据集可为蚜虫的识别、检测计数和分类提供数据基础.

The Chinese Loess Plateau (CLP) is the largest loess deposit on Earth with expansive surface-exposed source rocks of varying origins, ages, and history. Here, we present abundances of elements on representative loess and palaeosol samples from seven classic sections of the CLP. Most elements, including soluble elements (e.g. Rb and Cs), show significant correlations with La or Al2O3. These correlations indicate that these elements are hosted or absorbed in particle minerals during weathering, transport, and deposition (e.g. mica, K-feldspar, and clay minerals). These new observations allow the use of La/X (‘X’ being the element of interest) and the estimated La abundance of 31 ppm in the model upper continental crust (UCC) to estimate the abundances of other elements. The results show higher Cs (Cs = 6.7 ± 1.2 ppm), lower transition metals, Ba, and Ga. Given the high CaO and presence of carbonate in UCC rocks of both vast western China (the primary source for the CLP) and eastern China, we propose that these updates on the element abundances represent a refined model for the carbonate-bearing UCC.

为了避免因人工测量生猪体重给生猪带来较严重的应激反应,影响生猪身体健康,严重时导致生猪死亡.综述了计算机视觉技术在生猪体重智能估测方面的研究进展,通过相机获取生猪2D或3D图像数据,提取生猪体长、体高、腹围宽、胸围宽和背部面积,基于线性函数、偏最小二乘法函数、RBF、MLP等非线性函数,对生猪体重自动预测模型进行研究,实现非接触式生猪体重估测,能及时、快速且无伤害地获取生猪体重信息.对比分析各项相关研究报道可知:线性预测模型的准确率明显低于非线性预测模型,且基于非线性函数构建的体重估测模型的平均误差小于5％,与实际体重的平均相关性约0.97,说明生猪非接触式体重估测方法的可行性,为生猪的精准饲养管理提供了一种有效的监测手段,减少人力资源损耗,提高生猪养殖福利.

Calculating the temperatures of magmas from which granitoid rocks solidify is a key task of studying their petrogenesis, but few geothermometers are satisfactory. Zircon saturation thermometry has been the most widely used because it is conceptually simple and practically convenient, and because it is based on experimental calibrations with significant correlation of the calculated zircon saturation temperature (TZr) with zirconium (Zr) content in the granitic melt (i.e., TZr ∝ ZrMELT). However, application of this thermometry to natural rocks can be misleading, resulting in the calculated TZr having no geological significance. This thermometry requires Zr content and a compound bulk compositional parameter M of the melt as input variables. As the Zr and M information of the melt is not available, petrologists simply use bulk-rock Zr content (ZrBULK-ROCK) and M to calculate TZr. In the experimental calibration, TZr shows no correlation with M, thus the calculated TZr is only a function of ZrMELT. Because granitoid rocks represent cumulates or mixtures of melt with crystals before magma solidification and because significant amount Zr in the bulk-rock sample reside in zircon crystals of varying origin (liquidus, captured or inherited crystals) with unknown modal abundance, ZrBULK-ROCK cannot be equated with ZrMELT that is unknown. Hence, the calculated magma temperatures TZr using ZrBULK-ROCK have no significance in both theory and practice. As an alternative, we propose to use the empirical equation $$T_{SiO_{2}}$$  (°C) = -14.16 × SiO2 + 1723 for granitoid studies, not to rely on exact values for individual samples but focus on the similarities and differences between samples and sample suites for comparison. This simple and robust thermometry is based on experimentally determined phase equilibria with T ∝ 1/SiO2.

The East Kunlun Orogenic Belt (EKOB), which is in the northern part of the Greater Tibetan Plateau, contains voluminous Late Triassic intermediate-felsic volcanic rocks. In the east end of the EKOB, we identified highly differentiated peralkaline-like Xiangride rhyolites (~209 Ma) that differ from the widespread andesitic-rhyolitic Elashan volcanics (~232–225 Ma) in terms of their field occurrences and mineral assemblages. The older, more common calc-alkaline felsic Elashan volcanics may have originated from partial melting of the underthrust Paleo-Tethys oceanic crust under amphibolite facies conditions associated with continental collision. The felsic Elashan volcanics and syn-collisional granitoids of the EKOB are different products of the same magmatic event related to continental collision. The Xiangride rhyolites are characterized by elevated abundances of high field strength elements, especially the very high Nb and Ta contents, the very low Ba, Sr, Eu, P, and Ti contents; and the variably high 87Sr/86Sr ratios (up to 0.96), exhibiting remarkable similarities to the characteristic peralkaline rhyolites. The primitive magmas parental to the Xiangride rhyolites were most likely alkali basaltic magmas that underwent protracted fractional crystallization with continental crust contamination. The rock associations from the early granitoids and calc-alkaline volcanic rocks to the late alkaline basaltic dikes and peralkaline-like rhyolites in the Triassic provide important information about the tectonic evolution of the EKOB from syn-collisional to post-collisional. We infer that the transition from collisional compression to post-collisional extension occurred at about 220 Ma.

水稻病害是影响水稻产量的重要因素之一,使用传统机器学习方法识别农作物病虫害效果并不理想,因此该研究使用深度学习技术结合迁移学习方法识别常见水稻病害.使用当前深度学习领域经典网络模型VGG、ResNet、DenseNet、InceptionResNet、Xception模型作为预训练模型,通过比较不同模型在新任务上的表现,选取性能最好且最稳定的Xception模型作为最终模型.试验结果显示,DenseNet、InceptionResNet、Xception的识别准确率可以达到97％,尤其是Xception模型不仅可以达到98.50％的最高识别准确率而且是最稳定的.该研究通过试验探讨了适用于常见水稻病害智能识别的最佳模型,同时表明了使用迁移学习方法解决新任务的有效性.

为了实现自然场景下水稻害虫实时精准被识别,构建基于VGG-16卷积神经网络的水稻害虫智能识别模型.该模型采用VGG-16卷积神经网络为核心网络结构,根据水稻害虫的个体特征和自然场景,对VGG-16网络的卷积层局部调整,优化主要模型参数,实现水稻害虫的智能识别,其识别的平均准确率是90.7％,实现对沙叶蝉、大螟、斑须蝽、点蜂缘蝽和白背飞虱的准确识别.研究结果显示,采用卷积神经网络技术可以实现自然场景下害虫图像的精准识别,代替人工辨认,提高水稻害虫防治率,实现实时、精准防治的目标.

The Triassic granitoids are widespread in the eastern section of the East Kunlun Orogenic Belt (EKOB) on the northern Tibetan Plateau. These granitoids well record the evolution of the Paleo-Tethys oceans (named as A'nyemagen Ocean in the EKOB). Our new zircon U-Pb data together with ages in literature show that these granitoids represent long-lasting magmatism from the early (T-1,similar to-251-248 Ma), middle (T-2 similar to 247-238 Ma) to late (T-3, similar to 234-214 Ma) Triassic. The Triassic granitoids display talc-alkaline I-type granite affinities and hybrid mantle-crust geochemical signatures. The T-1 granitoids possess andesitic to felsic bulk continental crust (BCC)-like chemical composition (e.g., enriched in Rb, K and Pb, depleted in Nb, Ta, Sr, P and Ti), coupled with high I-Sr (0.7067-0.7148), negative epsilon(Nd(t)) (-732 to -1.66) and negative to positive epsilon(Hf(t)) (-5.11 to 3.59) as well as (Dy/Yb)(N) = 1.1, suggesting that the T-1 granitoids were formed by melting of the subducted A'nyemagen oceanic crust with terrigenous sediments under the amphibolite facies conditions in a syn-collisional setting. The T-2 and T-3 granitoids may be originated from a relatively homogeneous source with almost consistent mean values of I-Sr (0.7136 [T-2], 0.7094 [T-3]), epsilon(Nd(t)) (-5.83 [T-2] -5.97 [T-3]) and epsilon(Hf(t)) (-3.52 [T-2], -3.58 [T-3]). They present garnet signature of adakitic rocks and can be explained by partial melting of the juvenile mafic lower continental crust and mixing with upper crustal components during magma ascent. This process is considered to be associated with post-collisional extension which induced by asthenosphere upwelling and mantle melting, providing heat for mafic lower crust melting to form T-2 and T-3 granitoids. The T-1 granitoids with mantle signatures (e.g. epsilon(Hf(t)) > 0) as well as BCC-like compositions represent a net flux of juvenile dioritic to granitic materials adding to the continental crust, in support of the hypothesis of "continental collision zones are primary sites for net continental crust growth" along the EKOB. The genetic link between T-2 and T-3 granitoids means the EKOB had transformed to post-collisional setting since the middle Triassic (similar to 247 Ma). All these hypotheses are conceptually important for understanding the origin of the juvenile crust and continental crustal growth through magmatism from syn-collisional to post-collisional settings. (C) 2020 Elsevier B.V. All rights reserved.

Continentalcollision zones have been proposed as primary sites of net continental crustal growth. Therefore, studies on syn-collisional granitoids with mafic magmatic enclaves (MMEs) are essential for testing this hypothesis. The Baojishan (BJS) and Qumushan (QMS) syn-collisional plutons in the North Qilian Orogen (NQO) on the northern margin of the Tibetan Plateau have abundant MMEs in sharp contact with host granitoids, sharing similar constituent minerals but with higher modal abundances of mafic minerals in MMEs. The QMS host granitoids have high Sr/Y and La/Yb ratios, showing adakitic compositions, which are differentfrom the BJS granitoids. Based on bulkrock compositions and zircon U-Pb age-dating, recent studies on these two plutons proposed that MMEs represent cumulates crystallized early from the same magmatic system as their host granitoids, and their parental melts are best understood as andesitic magmas produced by partial melting of the underthrusting upper ocean crust upon collision with some terrigenous sediments under amphibolite facies. Here, we focus on the trace-element geochemistry of the constituent mineral phases of both MMEs and their host granitoids of the QMS and BJS plutons. Weshow that different mineral phases preferentially host different trace elements; for example, most rare earth elements (REEs and Y) reside in titanite (only found in the QMS pluton), amphibole, apatite, epidote and zircon (mostly heavy-REEs); and high-field-strength elements (HFSEs) reside in biotite, titanite, amphibole and zircon. Based on the mineral chemical data, we show that for these two plutons, MMEs are of similar cumulate origin, crystallized from primitive andesitic melts in the early stage of granitoid magmatism. The primitive andesitic melts for these syn-collisional granitoids are most likely produced by the partial melting of the oceanic crust, supporting the hypothesis of continental crustal growth considering the syn-collisional granitoids represent juvenile continental crust. As evidenced by distinct mineral compositions, the two plutons have different parental magma compositions, for example higher TiO2 content and higher Sr/Y and La/Yb ratios in the QMS parental magmas, a signature best understood as being inherited from the source. The higher TiO2 content of the parental magma for the QMS pluton leads to the common presence of titanite in the QMS pluton (absent in the BJS pluton), crystallization of which in turn controls the trace-element (REE, Y, Nb, Ta and others) systematics in the residual melts towards an adakitic signature. Therefore, parental magmas with high TiO2 content and high Sr/Y and La/Yb ratios, as well as their further fractionation of titanite, are important factors in the development of adakitic compositions, as represented by the QMS host granitoids. This model offers a new perspective on the petrogenesis of adakitic rocks. The present study further demonstrates that, in general, mineral chemistry holds essential information for revealing the petrogenesis of granitoid rocks.

为了实现农作物病虫害有效预防和及时控制的突出需求,提出基于Android的植保服务平台.该平台包括病虫害自动识别、地理信息可视化、典型病虫害及植保机构查询、病虫害防治方法科普等功能,平台设计了量大面广的农作物病虫害图文数据库,便于农户查阅资料.该平台在安徽省舒城县推广试用,测试显示各功能模块均达到了理想的运行效果,用户通过平台可以及时掌握当地病虫害的发生信息及防治方法,该平台实现了"互联网+"植保新模式.

The West Qinling Orogenic Belt (WQOB) is a major portion of the Qinling‐Dabie‐Sulu Orogen and holds essential information for understanding the protracted evolution of the north‐eastern branch of the Paleo‐Tethys in East Asia. In this study, we report our petrological, geochemical, and geochronological study on the five Triassic granitoid plutons of West Qinling with emphasis on the poorly studied Jiaochangba pluton with zircon U–Pb ages of 217.5 ± 1.6 Ma and 215.2 ± 1.2 Ma. The new data and the existing data on the other four plutons support the view that the West Qinling granitoids represent a magmatic response to the continental collision of the Yangtze Block (YB) with the North China Craton (NCC) in the Triassic. Like the other four plutons, the Jiaochangba pluton shows strong light rare earth element (REE) enrichment and weak heavy REE depletion ([La/Sm] N ≈ 7.14 ± 1.89; [Sm/Yb] N ≈ 4.63 ± 1.85) with varying negative Eu anomalies (Eu/Eu* ≈ 0.65 ± 0.20). In the N‐MORB normalized diagram, all the samples show relative enrichment in Rb, Pb, U, and K with negative Nb, Ta, P, and Ti anomalies, resembling those of the model continental crust. The Jiaochangba pluton has relatively lower ( 87 Sr/ 86 Sr) i (0.7062 to 0.7081), higher ε Nd (t) (−6.91 to −2.09), and ε Hf (t) (−5.57 to −0.14) than mature continental crust, which are consistent with their source being dominated by lower crust with significant mantle contributions. Mantle‐derived melt, which formed from partial melting of mantle wedge peridotite facilitated by dehydration of the subducted/subducting Mianlue ocean crust, provide the required heat for the crustal melting while also contributing to the compositions of these granitoids. Evolution of such parental magmas in open system crustal magma chambers with continued evolution/replenishment and crustal contamination and assimilation give rise to the observed petrological and geochemical characteristics of these granitoids.

We sampled 22 Mesozoic dykes in eastern continental China and carried out a detailed study on these samples, including K-Ar and zircon U-Pb geochronology, and elemental and Sr-Nd-Pb-Hf isotope geochemistry. Their K-Ar and zircon ages of 130-110 Ma are broadly consistent with the timing of the lithosphere thinning and the emplacement ages of widespread granitoids in the vast region, explicitly pointing to a common cause in space and time. The dykes represent evolved alkaline basaltic melts intruding the Mesozoic granitoids. Their rare earth element (REE) and multi-element patterns differ from the present-day ocean island basalts (OIB), but show strong arc-like signatures (e.g., enrichment in Rb and Pb and depletion in Nb, Ta and Ti). They show high (Sr-87/Sr-86)(i), (0.7048 to 0.7103), low epsilon(Nd)(t) (-12.3 to -5.7), low epsilon(Hf)(t) (-16.5 to -8.0) and low (Pb-206/Pb-204)(i) (18.79-18.85). These Mesozoic dykes are best understood as resulting from melting of geochemically enriched subcontinental lithospheric mantle (SCLM), whose geochemical enrichment is consistent with prior metasomatism with the agent being hydrous melt coming from subduction of the Paleo-Pacific plate at similar to 120 Ma or earlier. Similar to the present-day situation, the paleo-Pacific slab may have also existed stagnant in the mantle transition zone in the Mesozoic. The slab dehydrated and released water in the form of hydrous melt that percolated through and metasomatized the mantle lithosphere, and weakened the base of the lithosphere while producing basaltic melts that evolved to intermediate-felsic compositions of these dykes. The basaltic magmas that underplated and melted the lower crust to generate the widespread Mesozoic granitoids in eastern continental China. (C) 2019 Elsevier B.V. All rights reserved.

Jurassic-Cretaceous granitoids are widespread in eastern continental China and have been considered by many as resulting from paleo-Pacific subduction. However, the actual mechanism of their petrogenesis remains speculative. In order to address this important problem and on the basis of our regional study, we hypothesized that the coastal granitoids may result directly from the paleo-Pacific plate subduction, whereas the widespread granitoids in the continental interiors ultimately result from dehydration of the paleo-Pacific slab stagnated in the mantle transition zone (Niu et at., 2015). Here, we present the very first study testing this hypothesis. We sampled 18 Jurassic-Cretaceous granitoid plutons along a similar to 1300 km long traverse parallel to the inferred paleo-Pacific subduction from the southeast coastline to the Xiaoqinling in the continental interiors and carried out a detailed study on these plutonic samples, including zircon U-Pb geochronology, bulk-rock major and trace element compositions and Sr-Nd-Pb-Hf isotopic characteristics. These plutons give varying zircon crystallization ages of similar to 146 to 100 Ma. They are mostly granitic and minor granodioritic, quartz monzonitic and syenitic in composition, enriched in large ion lithophile elements (LILEs), depleted in high field-strength elements (HFSEs) and have varying negative Sr and Eu anomalies. The plutons in the continental interiors show significant positive correlations of Nd (epsilon(Nd) (t) = -25.5 to -10.9) and Hf (epsilon(Hf) (t) = -31.5 to -11.3) isotopes with Pb isotopes (Pb-206/Pb-204 (t) = 15.827 to 17.622), with the enriched endmember characterized by low epsilon(N)(d) (t), epsilon(Hf) (t) and Pb-206/Pb-204 (t). The plutons towards the coastal region have relatively high epsilon(N)(d) (t) (-9.0 to -5.2), epsilon(Hf) (t) (-11.2 to -4.1) and Pb-206/Pb-204 (t) (18.051 to 18.349). The coastal granitoids are best explained as resulting directly from subduction slab dehydration induced mantle wedge melting and resultant crustal anatexis, whereas the interior granitoids are best interpreted as resulting from mature crustal anataxis caused by basaltic magmatism associated with mantle lithosphere thinning, ultimately triggered by dehydration of paleo-Pacific slab stagnant in the mantle transition zone. (C) 2018 Elsevier B.V. All rights reserved.

大数据是新型战略资源,应用在农业领域前景广阔,不仅能挖掘出农业资源间的发展潜力,发挥耦合效应,还可以实现精准生产和销售,提升决策水平.相比较其他产业,农业大数据的发展相对滞后.阐述了大数据思维3个方面特征,以此为指标反观我国农业大数据的发展现状,并提出了建议.