Green nanotechnology is an emerging field of science that focuses on the production of nanoparticles by living cells through biological pathways. This topic plays an extremely imperative responsibility in various fields, including pharmaceuticals, nuclear energy, fuel and energy, electronics, and bioengineering. Biological processes by green synthesis tools are more suitable to develop nanoparticles ranging from 1 to 100 nm compared to other related methods, owing to their safety, eco-friendliness, non-toxicity, and cost-effectiveness. In particular, the metal nanoparticles are synthesized by top-down and bottom-up approaches through various techniques like physical, chemical, and biological methods. Their characterization is very vital and the confirmation of nanoparticle traits is done by various instrumentation analyses such as UV-Vis spectrophotometry (UV-Vis), Fourier transform infrared spectroscopy (FT-IR), scanning electron microscope (SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD), atomic force microscopy (AFM), annular dark-field imaging (HAADF), and intracranial pressure (ICP). In this review, we provide especially information on green synthesized metal nanoparticles, which are helpful to improve biomedical and environmental applications. In particular, the methods and conditions of plant-based synthesis, characterization techniques, and applications of green silver, gold, iron, selenium, and copper nanoparticles are overviewed.

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Background Predicting a list of plant taxa most likely to be observed at a given geographical location and time is useful for many scenarios in biodiversity informatics. Since efficient plant species identification is impeded mainly by the large number of possible candidate species, providing a shortlist of likely candidates can help significantly expedite the task. Whereas species distribution models heavily rely on geo-referenced occurrence data, such information still remains largely unused for plant taxa identification tools. Results In this paper, we conduct a study on the feasibility of computing a ranked shortlist of plant taxa likely to be encountered by an observer in the field. We use the territory of Germany as case study with a total of 7.62M records of freely available plant presence-absence data and occurrence records for 2.7k plant taxa. We systematically study achievable recommendation quality based on two types of source data: binary presence-absence data and individual occurrence records. Furthermore, we study strategies for aggregating records into a taxa recommendation based on location and date of an observation. Conclusion We evaluate recommendations using 28k geo-referenced and taxa-labeled plant images hosted on the Flickr website as an independent test dataset. Relying on location information from presence-absence data alone results in an average recall of 82%. However, we find that occurrence records are complementary to presence-absence data and using both in combination yields considerably higher recall of 96% along with improved ranking metrics. Ultimately, by reducing the list of candidate taxa by an average of 62%, a spatio-temporal prior can substantially expedite the overall identification problem.

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Diosgenin, a steroidal sapogenin, occurs abundantly in plants such as Dioscorea alata , Smilax China, and Trigonella foenum graecum . This bioactive phytochemical not only is used as an important starting material for the preparation of several steroidal drugs in the pharmaceutical industry, but has revealed also high potential and interest in the treatment of various types of disorders such as cancer, hypercholesterolemia, inflammation, and several types of infections. Due to its pharmacological and industrial importance, several extraction and analytical procedures have been developed and applied over the years to isolate, detect, and quantify diosgenin, not only in its natural sources and pharmaceutical compositions, but also in animal matrices for pharmacodynamic, pharmacokinetic, and toxicological studies. Within these, HPLC technique coupled to different detectors is the most commonly analytical procedure described for this compound. However, other alternative methods were also published. Thus, the present review aims to provide collective information on the most recent pharmacological data on diosgenin and on the most relevant analytical techniques used to isolate, detect, and quantify this compound as well.

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The plant hormone auxin drives plant growth and morphogenesis. The levels and distribution of the active auxin indole-3-acetic acid (IAA) are tightly controlled through synthesis, inactivation, and transport. Many auxin precursors and modified auxin forms, used to regulate auxin homeostasis, have been identified; however, very little is known about the integration of multiple auxin biosynthesis and inactivation pathways. This review discusses the many ways auxin levels are regulated through biosynthesis, storage forms, and inactivation, and the potential roles modified auxins play in regulating the bioactive pool of auxin to affect plant growth and development.

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Background The nuclear DNA amount in an unreplicated haploid chromosome complement (1C-value) is a key diversity character with many uses. Angiosperm C-values have been listed for reference purposes since 1976, and pooled in an electronic database since 1997 (http://www.kew.org/cval/homepage). Such lists are cited frequently and provide data for many comparative studies. The last compilation was published in 2000, so a further supplementary list is timely to monitor progress against targets set at the first plant genome size workshop in 1997 and to facilitate new goal setting. Scope The present work lists DNA C-values for 804 species including first values for 628 species from 88 original sources, not included in any previous compilation, plus additional values for 176 species included in a previous compilation. Conclusions 1998-2002 saw striking progress in our knowledge of angiosperm C-values. At least 1700 first values for species were measured (the most in any five-year period) and familial representation rose from 30 % to 50 %. The loss of many densitometers used to measure DNA C-values proved less serious than feared, owing to the development of relatively inexpensive flow cytometers and computer-based image analysis systems. New uses of the term genome (e.g. in 'complete' genome sequencing) can cause confusion. The Arabidopsis Genome Initiative C-value for Arabidopsis thaliana (125 Mb) was a gross underestimate, and an exact C-value based on genome sequencing alone is unlikely to be obtained soon for any angiosperm. Lack of this expected benchmark poses a quandary as to what to use as the basal calibration standard for angiosperms. The next decade offers exciting prospects for angiosperm genome size research. The database (http://www.kew.org/cval/homepage) should become sufficiently representative of the global flora to answer most questions without needing new estimations. DNA amount variation will remain a key interest as an integrated strand of holistic genomics.

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