Hepatoprotective and neuroprotective tocopherol analogues isolated from the peels of Citrus unshiu Marcovich

Three tocopherol analogues methoxytocopherol (1), α-tocopherol (2) and γ-tocopherol (3) were isolated from the peels of Citrus unshiu Marcovich. The protective effects of the isolated compounds against tert-butyl hydroperoxide-induced hepatotoxicity in human liver-derived HepG2 cells and glutamate-induced oxidative stress in HT22-immortalised hippocampal cells were evaluated. Compounds 1–3 were significantly protective in HepG2 cells with EC₅₀ values of 21.22 ± 2.01, 25.21 ± 2.11 and 25.25 ± 1.21 μM, respectively, and in HT22 cells, compounds 1–3 had EC₅₀ values of 20.62 ± 1.36, 6.44 ± 1.65 and 9.52 ± 1.54 μM, respectively.     

植被叶片叶绿素含量反演的光谱尺度效应研究

目前光谱指数方法已被广泛地应用于植被叶绿素含量的反演中,考虑到不同传感器的光谱响应存在差异,研究了光谱尺度效应对光谱指数反演植被叶片叶绿素含量的影响。基于PROSPECT模型模拟了不同叶绿素含量(5～80 μg·cm-2)下的5 nm叶片光谱反射率数据,并利用高斯光谱响应函数将其分别模拟成10～35 nm六种波段宽的光谱数据,再分析评价5～35 nm波段宽下光谱指数与叶片叶绿素含量的相关性、对叶片叶绿素含量变化及对波段宽变化的敏感性。最后,利用波段宽为40～65 nm的反射率数据对光谱指数反演植被叶绿素含量的光谱尺度效应进行验证。结果表明,通用光谱指数(vegetation index based on universal pattern decomposition method, VIUPD)反演叶绿素含量的精度最高,反演值与真实值拟合程度最好;归一化差值植被指数(normalized difference vegetation index, NDVI)和简单比值指数(simple ratio index, SRI)其次,虽然其决定系数R2高达0.89以上,但反演的叶绿素含量值小于真实值;其他光谱指数的反演结果较差。VIUPD对叶绿素含量具有较好的相关性和敏感性,受光谱尺度效应影响较小,具有较好的反演能力,这一结论恰好验证了其“独立于传感器”的特性,同时证明了VIUPD在多源遥感数据反演植被理化参量的研究中具有更好的应用前景。     

柑橘叶片叶绿素含量拉曼光谱定量分析方法研究

柑橘叶片叶绿素含量的准确检测对柑橘营养状况和生长态势具有极其重要的意义。研究了快速无损诊断柑橘叶片中叶绿素含量的方法,以期为拉曼光谱检测技术用于柑橘叶片叶绿素含量检测提供参考。采集不同冠层高度和不同地理分布的柑橘叶片120片,拭去叶片表面的灰尘,用去离子水对其清洗、晾干装入密封袋中并用标签分类标注。然后对柑橘叶片进行拉曼光谱采集,参数设置如下：分辨率为3 cm-1,积分时间为15 s;激光功率为50 mW。分别采用BaselineWavelet、迭代限制最小二乘（IRLS）和不对称最小二乘(ALS)三种算法对柑橘叶片的拉曼光谱背景进行扣除,使用偏最小二乘（PLS）方法建立定量模型;四种光谱预处理方法归一化(Normalization),Savitzky-Golay卷积平滑(SG smoothing, SG平滑)、多元散射校正(MSC)和Savitzky-Golay一阶导数(SG 1st Der)对扣除背景后的光谱进行进一步的优化处理。结果表明：采用原始光谱、BaselineWavelet、IRLS、ALS背景扣除处理后的光谱建立PLS模型,模型的相关系数r分别为0.858,0.828,0.885和0.862,交互验证均方根误差(RMSECV)分别为5.392,5.870,4.934和5.336,最佳因子数分别为8,3,8和8;IRLS背景扣除处理后的PLS模型的RMSECV最小,相关系数最高,建模效果最好。分别采用SG平滑、归一化、MSC和SG 1st Der预处理方法对IRLS背景扣除后光谱进行预处理并建立PLS模型,结果表明：IRLS光谱及其结合SG平滑、归一化、MSC和SG 1st Der四种预处理方法的PLS模型的R分别为0.885,0.897,0.852,0.863和0.888,RMSECV分别为4.934,4.715,5.595,5.182和4.962;最佳因子数分别为8,8,8,8和5;IRLS-SG平滑后PLS模型的RMSECV最小,模型效果最优。对IRLS-SG平滑预处理后的PLS模型展开验证,预测相关系数r为0.844,预测均方根误差(RMSEP)为5.29,预测精确度较高。采用拉曼光谱结合三种光谱背景扣除方法和四种预处理方法对柑橘叶片叶绿素含量进行定量分析表明：采用IRLS背景扣除结合SG平滑预处理后的PLS模型最优,建模集r为0.897,RMSECV为4.715;预测集r为0.844,RMSEP为5.29,预测精度较高。拉曼光谱结合背景扣除方法可以为柑橘叶片叶绿素含量的定量分析提供一种快速简便的分析方法。     

Studies on Productivity and Characterization of Polygalacturonase from <Emphasis Type="Italic">Aspergillus giganteus</Emphasis> Submerged Culture Using Citrus Pectin and Orange Waste

Polygalacturonases are part of the group of enzymes involved in pectin degradation. The aim of this work was to investigate some of the factors affecting polygalacturonase production by an Aspergillus giganteus strain and to characterize this pectinolytic activity. Several carbon sources, both pure substances and natural substrates, were tested in standing cultures, and the best results were obtained with orange bagasse and purified citrus pectin. On citrus pectin as sole carbon source, the highest extracellular activity (9.5 U/ml and 40.6 U/mg protein) was obtained in 4.5-day-old cultures shaken at 120 rpm, pH 3.5 and 30°C, while on orange bagasse, the highest extracellular activity (48.5 U/ml and 78.3 U/mg protein) was obtained in 3.5-day-old cultures shaken at 120 rpm, pH 6.0 and 30°C. Optimal polygalacturonase activity was observed in assays conducted at pH 5.5–6.5 and 55–60°C. The activity showed good thermal stability, with half-lives of 90 and 30 min when incubated at 55 and 60°C, respectively. High stability was observed from pH 4.5 to 8.5; more than 90% of the activity remained after 24 h in this pH range.     

Novel Method for Selective Spectrophotometric Determination of Titanium(IV) with Water Extract of Slippery Elm Leaf as a New Reagent

Abstract

A novel spectrophotometric method for the determination of titanium(IV) by using a new reagent, water extract of slippery elm leaf is developed. In 0.05 M hydrochloric acid, titanium(IV) reacts with this reagent to form a yellow product. The formed product shows maximum absorbance at 415 nm with a molar absorptivity value of 0.68×10⁴ l mol^–1 cm^–1 and the method was linear in the 0.2–6 µg ml^?1 concentration range. The detection limit value was found to be 0.0131 µg ml^?1. The proposed method was simple, low cost, selective, and sensitive. It was applied to the analytic samples with satisfactory results.     

Finding the Most Significant Elements for the Classification of Organic Orange Leaves: A Data Mining Approach

Brazil is the world’s largest producer of oranges. The Brazilian conventional citrus crop requires repeated application of agrochemicals to achieve satisfactory levels of productivity. The organic citriculture is an alternative production system, which is environmentally friendly and offers a safe food to consumers. However, it is difficult to determine if a food or plant was cultivated in organic or conventional system by just common observation, which makes the customers of organic food market vulnerable against fraudulent entrepreneurs. In this study, we present a data mining approach for the study of Brazilian organic citrus leaves which can aid in the certification of authenticity of the citrus leaves. The elemental composition is determined by inductively coupled plasma-mass spectrometry (ICP-MS). We developed classification models based on support vector machines and artificial neural networks capable of predicting whether a citrus leaf is organic or conventional through analysis of the concentration levels of the 14 chemical elements (Al, Ba, Co, Cr, Cs, Cu, Fe, Mg, Mn, Ni, Rb, Si, Sr, and V) found in both types of leaves. Feature selection filter methods are used to determine the most relevant elements for the classification process. Our best model obtained was a support vector machine with approximately 88% prediction accuracy. The elements Mn, Mg, and Rb were evaluated as the most significant for the classification decision. This is the first paper which addresses the problem of classification of organic orange leaves based on chemical composition. The presented methodology is useful for attesting authenticity of organic citrus leaves and can be adapted for other organic food or substances.     

非土壤因素对茶叶铅污染的影响

通过对18个茶叶生产厂家的分析调查发现,精制茶的生产工艺对茶叶的铅含量在总体上有降低作用,而粗制茶的加工工艺却有增加的趋势,因此茶叶生产工艺对茶叶的铅含量影响很大。通过用水清洗鲜叶发现,茶叶表面有相当一部分的铅可以洗脱下来,这说明在茶叶的种植过程中,大气中粉尘沉降对茶叶也有铅污染的作用。据此提出了一些建议和改进措施。     

滞尘影响下的茶树叶片水分高光谱估算

减少叶面滞尘对茶树叶片水分有效光谱信息提取的干扰,有利于建立更加稳健的茶树叶片水分高光谱估算模型。以“舒茶早”为研究对象,通过田间随机采集鲜叶样品,测定叶片原始光谱反射率、含水量以及滞尘率。比较分析滞尘对茶树叶片原始光谱的影响,分别基于归一化计算与比值计算方法构建新波段植被指数,并利用相关系数法筛选叶片水分含量相关性最高的新波段植被指数,结合相对变率分析获取滞尘对叶片水分估算影响不敏感的待选指数。通过分析不同滞尘条件下新建植被指数和已有水分指数与滞尘的响应关系,筛选出滞尘影响下茶树叶片水分估算的最优植被指数,最终构建茶树叶片水分估算的高精度模型。结果表明：（1）位于711~1 378 nm波段范围的叶片光谱反射率受滞尘影响呈现显著降低的趋势,随着滞尘率增大光谱反射率减小,且无尘叶片反射率与有尘状态反射率具有明显聚类现象,相同状态下的不同叶片反射率差异性极显著。（2）新波段植被指数、已有水分指数与茶树叶片含水量之间的相关性以及基于该指数构建的茶树叶片水分估算模型的精度,在滞尘影响下均呈现明显的下降趋势。（3）在滞尘混合状态下,以1 298和1 325 nm为中心波段的新建比值植被指数对滞尘敏感性最低,且与叶片含水量相关性高,为最优植被指数,其建立的茶树叶片水分高光谱估算模型具有较高的预测精度（y=0.245x-0.241,R2=0.854,RMSE=0.001）,并且实测值与预测值具有较好的一致性。因此,该研究可为茶树的水分精细化管理提供依据,并可为基于高光谱信息构建复杂环境条件下的水分估算高精度模型提供新思路。     

光谱图像技术结合SAM算法识别自然场景下的成熟柑橘

为了实现采摘机器人在复杂的自然场景下正确识别树上果实,来完成果实采摘,研究了不同环境下柑橘的识别方法.针对复杂的自然环境的影响及传统方法的局限性,在可见光和近红外区域择选5个特征波长滤波片,采集得到5幅滤波后的图像,并利用光谱角分类算法完成柑橘识别.试验结果表明,在光照角度、光照强度等不同条件下,柑橘的识别准确度达到96%.研究表明,滤波片光谱图像技术结合光谱角分类算法可以有效地识别自然场景下的成熟柑橘.     

Nature-inspired Three-dimensional Au/Spinach as a Binder-free and Self-standing Cathode for High-performance Li-O2 Batteries

Design and fabrication of functional porous air cathode materials with superior catalytic activity is still the key point for non-aqueous lithium-oxygen(Li-O₂) batteries. Herein, inspired by the self-standing three-dimensional(3D) structure of the natural spinach leaves, a unique binder-free and self-standing porous Au/spinach cathode for high-performance Li-O₂ batteries has been developed. The carbonized spinach leaves serve as a superconductive current collector and an ideal porous host for accommodating catalysts. The Au/spinach cathode could offer enough spaces for accommodating the discharge products, shorten the distance of the oxygen and electrolyte diffusion, and promote the oxygen reduction reaction(ORR) and oxygen evolution reaction (OER) processes. This optimized Au/spinach cathode achieved a high specific area capacity of 7.23 mA‧h/cm² at a current density of 0.05 mA/cm² and exhibited excellent stability(280 cycles at 0.05 mA/cm² with a fixed capacity of 0.2 mA‧h/cm²). The superior performance encourages the construction of more advanced cathode architectures by the use of bio-composites for Li-O₂ batteries.