Fox Hunting in Wild Apples: Searching for Novel Genes in Malus Sieversii

Malus sieversii is considered the progenitor of modern apple (Malus pumila) cultivars and to represent a valuable source of genetic diversity. Despite the importance of M. sieversii as a source of disease resistance, stress tolerance, and novel fruit traits, little is known about gene function and diversity in M. sieversii. Notably, a publicly annotated genome sequence for this species is not available. In the current study, the FOX (Full-length cDNA OvereXpressing) gene hunting system was used to construct a library of transgenic lines of Arabidopsis in which each transgenic line overexpresses a full-length gene obtained from a cDNA library of the PI619283 accession of M. sieversii. The cDNA library was constructed from mRNA obtained from bark tissues collected in late fall–early winter, a time at which many abiotic stress-adaptative genes are expressed. Over 4000 apple FOX Arabidopsis lines have been established from the pool of transgenic seeds and cDNA inserts corresponding to various Gene Ontology (GO) categories have been identified. A total of 160 inserts appear to be novel, with no or limited homology to M. pumila, Arabidopsis, or poplar. Over 1300 lines have also been screened for freezing resistance. The constructed library of transgenic lines provides a valuable genetic resource for exploring gene function and diversity in Malus sieversii. Notably, no such library of t-DNA lines currently exists for any Malus species.     

基于聚类分析的浓缩苹果汁风味品质分析与评价

通过对浓缩苹果汁主要风味物质进行分析,建立其风味品质的客观评价方法,为生产者合理调整工艺提供参考。分别选取风味较好和风味较差的浓缩苹果汁样品,对其挥发性风味物质、有机酸、氨基酸、糖类等主要风味物质进行分析,采用主成分分析、因子分析综合打分、聚类分析等方法筛选出能够有效区分不同风味品质浓缩苹果汁样品的主要风味化合物。选取12批次浓缩苹果汁样品,检测样品中39种主要挥发性风味物质、14种主要氨基酸、6种主要有机酸以及4种主要的糖类等风味物质。根据因子分析综合打分结果,从29种组合中,筛选出能够区分浓缩苹果汁风味的5种主要风味物质,分别为天冬氨酸、丝氨酸、蛋氨酸、果糖和葡萄糖。利用不同年份的8个批次浓缩苹果汁样品对该结果进行了验证,结果表明,这5种风味物质能够有效区分A、B两类浓缩苹果汁。利用筛选出的5种主要风味物质,能够对浓缩苹果汁风味品质进行客观、准确的判别。     

苹果酒品质检测中电子鼻和电子舌检测参数的优化

以不同产地相同品种的苹果（陕西长富二号、甘肃长富二号、山东长富二号）为原料酿造苹果酒，采用电子鼻和电子舌技术对3种不同苹果酒的挥发性气味和滋味成分进行检测和分析。从样品稀释倍数、顶空进样体积、顶空生成时间和载气流速4个实验参数研究检测条件对电子鼻传感器响应信号的影响，选取传感器信号峰值和稳定值，通过单因素方差分析和主成分分析（PCA），获得电子鼻的最佳检测参数为：样品稀释30倍、顶空进样体积5 mL、顶空生成时间5.0 min、载气流速300 mL/min。从样品稀释倍数研究检测条件对电子舌传感器响应信号的影响，通过主成分分析，获得电子舌的最佳检测参数为样品稀释30倍。应用优化后的参数采用电子鼻和电子舌对3种不同苹果酒的检测，区分效果较好，能够从挥发性气味、滋味等实现苹果酒的检测和鉴别。     

益生菌发酵对苹果汁主要营养成分及挥发性物质的影响

以红富士苹果汁为原料，研究益生菌混菌发酵对苹果汁挥发性物质及主要营养成分的影响。结果表明，苹果汁经混合益生菌发酵后，琥珀酸、苹果酸含量明显下降，而乳酸、柠檬酸、酒石酸、奎宁酸、莽草酸与丙酮酸的含量均明显上升；总酚含量呈先上升后下降趋势；儿茶素、表儿茶素、槲皮素、根皮苷和芦丁含量分别上升了5.57%、5.65%、5.83%、19.2%和4.52%，绿原酸含量下降了14.9%。发酵后的苹果汁共检出37种挥发性物质，与发酵前相比，增加了10种。其中，醇类增加5种、含量增加106.9%，酯类增加8种、含量增加84.5%；酮类种类不变，含量增加171.7%；醛类减少3种、含量降低了80.9%。     

果蔬土壤中重金属元素Zn,Hg,Cu含量的测定

以甘肃省天水市麦积区花牛镇花牛村苹果种植地区土壤为研究对象采用火焰原子吸收光谱仪对土壤中的重金属元素Zn,Hg,Cu的含量进行了测定,各重金属元素的平均含量分别为:Zn的平均含量为26.27 mg/kg、Hg的平均含量为0.617 mg/kg、Cu的平均含量为11.67 mg/kg。结果表明,该地区的土壤可以安全的进行农业生产,土壤中的重金属不会通过食物链的作用对人类健康形成威胁和危害。     

沙果果酒发酵工艺优化及抗氧化活性的研究

以新鲜沙果为原料酿造果酒，考察发酵时间、发酵温度、初始糖度和初始pH对沙果果酒品质的影响，并通过正交试验优化发酵工艺条件。结果表明，沙果果酒的最佳发酵工艺为发酵时间12 d、发酵温度24 ℃、初始糖度22 °Bx、初始pH值4.0。在此优化工艺条件下，酿得的果酒色泽呈浅黄色、澄清透亮，滋味清爽，有浓郁的沙果果香和醇厚的酒香，酒精度为11.8%vol，感官评分为95.1分。DPPH自由基清除率测定结果表明沙果果酒具有较好的抗氧化活性。     

蒸汽爆破技术对苹果果胶乳化特性的影响

明确蒸汽爆破处理对苹果果胶乳化性的影响。对苹果果胶进行蒸汽爆破处理,研究汽爆压力和汽爆时间对果胶乳化活性和乳化稳定性的影响,并比较汽爆前后果胶粒径和果胶表观黏度,通过显微镜观察乳化液的微观结构。结果表明,果胶乳化活性和乳化稳定性随着爆破压力和爆破时间的增加而增加,与未汽爆处理的果胶相比,在0.6 MPa/120 s处理条件下,果胶乳化活性由21.05 m2/g增加至43.61 m2/g;乳化稳定性由89.60 min增加到125.92 min;乳化液平均粒径由143.1 μm减少为100 μm;乳化液表观黏度显著上升,显微观察显示汽爆后的苹果果胶乳化液滴更加均匀细密。蒸汽爆破处理苹果果胶提高了乳化性,使果胶乳化性整体改善。     

Feasibility of non-destructive evaluation for apple crispness based on portable acoustic signal

In this paper, apple crispness was evaluated by sensory evaluation and compared with non-destructive measurements of portable acoustic signal to discuss the feasibility of non-destructive evaluation for apple crispness based on portable acoustic signal. Acoustic eigenvalues from the acoustic signal were processed by time domain and Hilbert–Huang transform (HHT), followed by analysing the correlations with apple crispness that had been evaluated via sensory evaluation. Multiple linear regression (MLR) and artificial neural network (ANN) were applied to predict apple crispness. The results proved that crispness correlates significantly (P < 0.01) with four acoustic eigenvalues, including waveform index, sound intensity, energy of low frequency and energy of high frequency. The average relative error of apple crispness predicted by ANN was 1.42 ± 1.9%, remarkably lower (P < 0.01) that of MLR (6.79 ± 5.64%), implying that the model predicted by ANN is more accurate than that of MLR.