夏施~(15)N-尿素在鸭梨树体内的吸收分配规律及其去向的研究

1988～1989年,在田间微区内,研究了夏施~(15)N—尿素在鸭梨树体内的吸收分配规律及其去向。两年结果基本一致。树体吸收~(15)N很快,施肥后仅42d肥料利用率高达8.54％,但向上运转缓慢;当年果实速长期树体中35.9％的肥料氮(NDFF)分配在粗根中,分配到新生器官的仅有29.8％,果实的NDFF浓度为0.087mg/g.dw,比其他器官低得多;在果实生长后期NDFF仍在向果实中运转,长枝的NDFF分配率也持续不降。当年落叶休眠期,树体内的NDFF主要贮藏在多年生枝和粗根中,次年调运到新生器官,用于开花座果及枝叶生长。到次年果实速长期,历经十三个半月,新生器官NDFF的分配率和浓度仍较高。夏施氮肥损失率高达70％以上,微区内土壤残留率低,土壤中残留的NDFF可以上下移动,植株吸收利用率最高仅为8.47％(1988年处理)和14.60％(1989年处理)。     

响应面法优化醋酸菌在梨渣中的发酵条件研究

测定不同温度、转速、酒精浓度、接种量条件下醋酸菌在梨渣为主的半固体培养基中的产酸量,观察菌种的生长情况.采用响应面法优化醋酸菌生长条件.结果表明:醋酸菌较佳发酵条件为转速136 r.min-1,温度32℃,梨渣量28%,乙醇体积分数3.6%,接种量4.0%.     

田间黄花梨糖度的可见/近红外光谱检测方法

提出了一种可克服背景光对田间光谱测量影响的方法。采集田间水果光谱时,环境背景光的干扰强,难以获取样品有效光谱信息。在田间采用套袋方式遮挡现场光线能得到较理想的结果,但检测效率低,仪器暗场校正和参考光谱校正等方法有利于减小模型误差,但不能有效消除环境光照的干扰。通过在测量探头前加装快门,打开快门时测得样品在仪器光源和背景光共同作用下的现场光谱,关闭快门时测得样品仅在现场环境光线作用下的背景光谱,将背景光谱从现场光谱中扣除进行背景光校正。利用偏最二乘法建立田间(背景光校正前、后)以及室内样品光谱建立黄花梨糖度预测模型,预测值与真实值的相关系数分别为0.1,0.69,0.92,均方根误差分别为0.89。Brix,0.42。Brix,0.27。Brix,预测集的RPD分别为0.79,1.69,2.58,结果表明实验所采用的背景光校正方法可有效减小田间环境光照对黄花梨可见/近红外光谱采集的影响,可用于田间水果的近红外光谱采集,有利于充分发挥可见/近红外光谱技术在果实采收前的田间管理、采收成熟度检测等方面的潜力。     

Bioactive Betalain Extracts from Cactus Pear Fruit Pulp,Beetroot Tubers,and Amaranth Leaves

Natural food items and the additional benefits they provide have received considerable attention in recent years. Betalains are nutritious pigments which have valuable biological properties, e.g., antioxidant and free radical scavenging activity. In this study, aqueous betalain extracts were obtained from different coloured cactus pears (purple, red/pink, and orange), amaranth, and beetroot, with and without the addition of ascorbic acid, microwave-heated, and freeze-dried and subsequently analysed by thin layer chromatography (TLC). Beetroot samples without the addition of ascorbic acid (AA) had lower phenols, flavonoids, and ascorbic acid content than beetroot samples extracted with the addition of AA. Amaranth had significantly higher contents of antioxidants than all the other plants. Results for phenolic compounds showed that there were no significant differences between cactus pear cultivars, however, significant differences were seen between the two beetroot samples (microwave-heated with and without AA) as well as amaranth. For flavonoid compounds, amaranth had significantly higher values than all other samples. The lowest flavonoid content was found in beetroot without AA (0.49 mgCE/g). For ascorbic acid, significant differences were noticed between amaranth (71.71 mg/100 g) and samples from cactus pear and beetroot. TLC results showed that purple and red cactus pear samples had the most vivid colours, a reflection of the high betacyanin and betaxanthin contents in the cultivars. Moreover, extracts from cactus pear, beetroot, and amaranth were classified according to a decision tree which was designed by the Code of Federal Regulations/Food Additives Regulation of the EU. The classification of betalain pigment extracts as colouring foods was achieved through enrichment factor calculations and the colourant decision tree. The results showed that the betalain pigment extraction method used is inexpensive, time-saving, energy-saving, non-toxic, and chemical solvent free and yields high concentrations of betalains.     

无籽梨与雪花梨果汁加工性能的比较

以雪花梨作为对照,主要从抗褐变能力、出汁率、澄清效果等方面研究无籽梨的果汁加工性能。结果表明,无籽梨和雪花梨切块护色时加入抗坏血酸,其最佳的质量浓度分别为0.6 g/L和0.8 g/L;最高出汁率酶解条件分别为:酶的质量浓度均为0.1 g/L,酶解温度为40℃,酶解时间为2.5 h与2 h,出汁率分别为85.2%和87.5%;无籽梨与雪花梨均以冷冻澄清效果最好。成品无籽梨果汁外观呈黄白色乳浊液,无沉淀,无变色现象;成品雪花梨果汁呈金黄色,清晰透明、晶亮、无混浊和沉淀。无籽梨果汁的出汁率比雪花梨低,并且不易澄清,所以并不是很适合加工澄清果汁,可以考虑加工成浑浊果汁或者带肉果汁。     

壳聚糖涂膜对黄花梨常温贮藏效果的影响

以黄花梨果实为试材,采用浓度0%,0.5%,1.0%,1.5%,2.0%壳聚糖溶液浸泡黄花梨果实1min,在室温下贮藏16d,研究了壳聚糖涂膜处理对黄花梨果实贮藏品质的影响.试验结果表明:与清水处理相比,4种壳聚糖涂膜处理均可不同程度降低果实的失重率和腐烂率,抑制果实贮藏后期可溶性固形物、可滴定酸和维生素C含量下降,保持果实较好的硬度,从而延缓了果实的成熟衰老.其中1.0%壳聚糖涂膜处理的果实贮藏16d,其腐烂率和失重率分别为12.8%和3.34%,而对照的分别是27.3%和6.46%,与对照的差异显著,果实品质好,保鲜效果最佳.     

高光谱技术结合CARS算法的库尔勒香梨可溶性固形物定量测定

由于高光谱数据量大、维数高,光谱噪声明显、散射严重等特征导致光谱建模时关键变量提取较为困难,同时,高光谱图像的获取会受非单色光、杂散光、温度等多种因素的影响,从而使高光谱数据与待测性质之间有一定非线性关系。为此,提出采用正自适应加权算法(CARS)对可见-近红外高光谱高维数据进行关键变量筛选,并与全光谱和经典变量提取方法SPA,MC-UVE,GA和GA-SPA方法进行比较。以200个库尔勒香梨为研究对象,采用SPXY方法将样本划分为校正集和预测集,校正集和预测集分别包含150个和50个样本。基于不同方法筛选的变量,分别建立线性PLS模型及非线性LS-SVM模型,r2,RMSEP和RPD用于模型性能的评估。综合比较发现,GA,GA-SPA和CARS变量筛选方法能够有效地筛选出原始高光谱数据中具有强信息且对外界影响因素不敏感的变量,适用于高光谱数据关键变量的提取,其中CARS变量筛选效果最佳,基于CARS获取的关键变量构建的非线性LS-SVM库尔勒香梨SSC含量预测模型获得了最优的预测结果,r2_pre,RMSEP和RPD分别为0.851 2,0.291 3和2.592 4。研究表明,CARS方法是一种有效的高光谱关键变量筛选方法,利用高光谱数据,非线性LS-SVM模型比线性PLS模型更适合于香梨品质的定量预测。     

近红外高光谱图像结合CARS算法对鸭梨SSC含量定量测定

高光谱数据量大、 维数高且原始光谱噪声明显、 散射严重等特征导致光谱建模时关键波长变量提取困难。 基于此,提出采用竞争性自适应重加权算法(CARS)对近红外高光谱数据进行关键变量选择。 鸭梨作为研究对象。 采用决定系数r2、 预测均方根误差RMSEP和验证集标准偏差和预测集标准偏差的比值RPD值进行模型性能评估。 基于选择的关键变量建立PLS模型(CARS-PLS)与全光谱变量建立的PLS模型进行比较发现CARS-PLS模型仅仅使用原始变量中15.6%的信息获得了比全变量PLS模型更好的鸭梨SSC含量预测结果,r2_pre,RMSEP和RPD分别为0.908 2,0.312 0和3.300 5。 进一步与基于蒙特卡罗无信息变量MC-UVE和遗传算法(GA)获得的特征变量建立的PLS模型比较发现,CARS不仅可以去除原始光谱数据中的无信息变量,同时也能够对共线性的变量进行压缩去除,该方法能够有效地用于高光谱数据变量的选择。 结果表明,近红外高光谱技术结合CARS-PLS模型能够用于鸭梨可溶性固形物SSC含量的定量预测。 从而为基于近红外高光谱技术预测水果内部品质的研究提供了参考。     

Nondestructive testing of external defects on Nanguo pear

In view of the common pests and diseases and irregularly shaped fruits of Nanguo pear, this paper fused the spectral information and image features to realize the rapid nondestructive testing and recognition of the external defects on Nanguo pear by hyperspectral imaging technology. Backpropagation neural network and support vector machine model was established to identify external defects, which are commonly used in classification and pattern recognition. The testing results show that recognition effect of support vector machine is better than backpropagation neural network. Among them, the recognition accuracy of fruits damaged by insects and rotten fruits of Nanguo pears reaches 100%. This study provides a theoretical basis for developing online grading system and quality detection of Nanguo pear based on multispectral imaging technique.     

福建省梨异常早期落叶初步调查与分析

初步调查和分析了福建梨异常早期落叶的原因,认为种质基因型是影响梨异常早期落叶最主要的因素,栽培管理模式、种植方向等也均有一定影响。同时,福建梨主栽品种中翠冠异常早期落叶较为严重,落叶率多在40%以上。