基于改进极限学习机的水体溶解氧预测方法

为了有效地指导水产养殖生产，提高溶解氧浓度预测的精度，提出了基于因子筛选和改进极限学习机（Extreme Learning Machine，ELM）的水产养殖溶解氧预测模型。首先，利用皮尔森相关系数法计算各影响因子与溶解氧浓度间的相关系数，提取强关联因子，降低预测模型的输入量维度；采用偏最小二乘算法（Partial Least Square, PLS）优化传统ELM神经网络，避免网络中隐含层共线性问题，保障输出权值的稳定性；然后，结合新型激活函数，构建水体溶解氧浓度预测模型。最后，将SPLS-ELM（Selection Based Partial Least Square Optimized Extreme Learning Machine）预测模型应用到江苏省无锡市南泉基地某试验池塘的水体溶解氧预测中。试验结果表明：该模型的预测均方根误差为0.3232，与最小二乘支持向量机（Least Square Support Vector Machine，LSSVM）、BP神经网络、粒子群（Particle Swarm Optimization，PSO）优化LSSVM和遗传算法（Genetic Algorithm, GA）优化BP神经网络相比分别降低40.98%、44.48%、34.73%和44.18%。且该模型的运行时间仅0.6231s，预测精度和运行效率明显优于其他模型。该模型的溶解氧预测曲线接近真实溶解氧变化曲线，能够满足水产养殖实际生产对水体溶解氧预测的要求。     

Root architecture of sorghum genotypes differing in root angles under different water regimes

Plant root architecture offers the potential for increasing soil water accessibility, particularly under water-limited conditions. The objectives of this study were to evaluate the root architecture in two genotypes of sorghum (Sorghum bicolor (L.) Moench) differing in root angles and to assess the influence of different deficit irrigation regimes on root architecture. The response of two sorghum genotypes, ‘Early Hegari-Sart’ (EH; steep root angle) and ‘Bk7’ (shallow root angle) to four irrigation treatments was investigated in two replicated outdoor studies using large pots. The results indicated that EH possessed steeper brace and crown root angles, fewer brace roots, greater root biomass, and root length density than Bk7 at deeper soil depths (i.e., 15–30 and 30–45 cm) compared with a shallower depth (i.e., 0–15 cm). Across the soil profile, EH had greater root length density and length of roots of small diameter (<1 mm) than Bk7. Accordingly, EH showed more rapid soil-water capture than Bk7. Different levels of irrigation input greatly affected root architecture. Severe deficit irrigation (25% of full crop transpiration throughout the season) increased the angle and number of crown roots, root biomass, and root length density compared with 75 and 100% of full crop transpiration treatments. Consequently, root system architecture can be effectively manipulated through both genotypic selection and irrigation management to ensure optimal performance under different levels of soil available water.     

福建南平市竹产业标准体系实施、评价与改进建议

推动竹产业高质量发展，标准化工作任重道远，推进标准体系有效实施、开展标准体系评价、动态优化标准体系必不可少。本文以南平市竹产业为例，探索竹产业标准体系实施、评价与改进的方法，以期逐步建立福建省竹产业标准体系实施与评价体系。     

绿色合成纳米铁对污染土壤中砷的钝化效果

为实现对砷(As)污染土壤的高效修复,利用桉树叶提取液合成纳米铁颗粒悬浊液(EL-nFe),分析其对溶液中As(Ⅲ)、As(Ⅴ)的吸附性能,在此基础上利用化学法重点评估其对重度As污染土壤的钝化效果。结果表明,EL-nFe对As(Ⅲ)、As(Ⅴ)的吸附过程符合准一级动力学和Langmuir等温吸附模型,其对As(Ⅲ)、As(Ⅴ)的最大吸附量分别为8.08和24.68 mg/g。施加EL-nFe后的土壤As的浸出性和生物有效性显著降低,SPLP-As和KH_2PO_4提取的生物有效性As分别下降33.26%～52.42%和6.57%～14.21%,同时土壤连续提取的结果显示,EL-nFe促使土壤易溶态As向生物利用率较低的残渣态As转变,提高了土壤As的稳定化程度。因此,EL-nFe对土壤As具有良好的钝化效果,且成本较低,可作为一种良好的修复重度As污染土壤的钝化剂。     

拮抗农业致病菌放线菌G5发酵条件的优化

微生物的发酵过程十分复杂,培养基配方的组成以及培养条件的变化都会对菌体的代谢造成很大的影响。为了使抗生素的产量达到最大化,试验运用了Plackett-Burman试验设计、最陡爬坡试验、BoxBehnken试验设计对放线菌(Actinomycetes)G5进行了发酵条件优化。利用Plackett-Burman试验设计对影响放线菌G5发酵的诸多相关因素进行评估并筛选出3个主要因素,即碳源含量、培养温度和培养时间;之后根据3个主要因素的作用大小和方向进行了最陡爬坡试验;最后运用Box-Behnken试验设计确定最优值,得出其最优培养条件为淀粉含量21.66 g/L、培养温度27.70℃、培养时间7.75 d。在此条件下,抗生素对苹果轮纹病菌的抑菌圈直径为23.00 mm,与模型预测值基本一致。     

2CZD-1型段茎式甘蔗种植机设计与试验

研制了2CZD-1型段茎式甘蔗种植机,可一次性完成甘蔗种植的开沟、施肥、自动取种、自动排种、覆土和覆膜等工序,适用于宽窄行甘蔗种植。设计了机架、取送种机构、转盘施肥机构、旋耕覆土机构、覆膜机构和液压传动系统等结构,其中取送种机构采用排冗结构实现均匀排种。利用有限元分析软件ANSYS对甘蔗种植机的机架进行模态分析,并通过田间试验获得甘蔗种植机的覆土厚度合格率、种植密度、伤芽率、漏植率及总排肥量稳定性变异系数等性能参数。模拟结果表明,当激励频率为8~80 Hz时,机架容易发生共振,且最大位移可达28.12 mm。田间试验表明,该种植机的种植密度为142325芽/hm^2,覆土厚度合格率为93.6%,伤芽率为2.8%,漏植率为4.7%,种植深度合格率为89.3%,总排肥量稳定性变异系数为5.8%,工作生产率为0.32 hm2/h,符合甘蔗种植机的设计要求,能够显著提高甘蔗种植的效率。     

122份栽培桃品种（系）黄白肉性状的分子标记辅助鉴定

【目的】 类胡萝卜素裂解双脱氧酶基因（Carotenoid Cleavage Dioxygenases 4,CCD4）控制桃果肉颜色（白/黄）,CCD4存在3种等位基因。本研究利用Indel、SSR荧光标记毛细管电泳及SNP鉴定等基因分型技术分析我国主要桃黄白肉品种（系）中CCD4等位基因的差异,为主要黄/白肉品种（系）的基因型鉴定、亲本选配和选择相应的分子标记对不同来源子代的果肉颜色进行鉴定奠定基础。【方法】利用已经报道的桃不同果肉颜色中CCD4等位基因3种突变类型,合成不同引物进行PCR扩增,LTR反转录转座子插入突变经1%的琼脂糖凝胶电泳检测,CT单元重复的PCR产物在ABI3730XL测序仪上进行SSR荧光标记毛细管电泳检测,SNP标记经Sanger测序后利用ContigExpress软件分析CCD4等位基因的碱基替换（A→T）。综合以上结果,统计每份材料中CCD4等位基因的突变类型与果肉颜色的一致性。【结果】通过对不同来源的122份桃品种（系）材料进行基因型分析,发现CCD4发生LTR反转录转座子插入突变材料的基因型共有31份,占总材料的25.4%,其中纯合插入突变材料的片段扩增长度为729 bp,共有8份,占总突变的25.8%;CCD4发生微卫星重复序列突变材料存在2 bp的插入,扩增片段长度为179 bp,该类型共有68份,占总材料的55.7%,其中纯合插入材料25份,占总突变的36.8%;CCD4发生A→T碱基替换突变的材料较少,仅有1份,占总材料的0.82%,实际应用中可以不考虑该种类型。CT和LTR插入的两种突变类型的黄肉品种（系）有7份,占总材料的5.7%。研究结果表明,LTR反转录转座子插入突变和微卫星序列重复突变是黄肉桃中CCD4等位基因的主要突变类型。其中CCD4发生一种纯合突变或两种杂合突变桃品种（系）为黄肉类型,分子标记鉴定结果与调查的122份桃品种（系）黄白肉表型性状完全一致,准确率为100%。【结论】采用分子标记明确了122个桃品种（系）黄/白肉性状的基因型,为不同亲本组合子代表型鉴定的标记类型选择提供了技术支撑,为建立桃种质材料黄/白性状的分子辅助育种体系和黄肉桃的选育奠定了基础。     

As contamination alters rhizosphere microbial community composition with soil type dependency during the rice growing season

Rhizosphere microbes play a cardinal role in transformation and crop uptake of arsenic (As), thereby relieving or intensifying the risk of As contamination in the food webs. How rhizosphere microbiomes respond to As contamination in different paddy soils and rice growth stages is still unclear. Here, we conducted a rice pot experiment to address the effects of rice developmental stage and As contamination on the rhizosphere microbial communities in two contrast paddy soils, a yellow clayey paddy soil (YP, pH 5.1, soil organic matter 20.8 g/kg) and red paddy soil (RP, pH 6.2, soil organic matter 46.1 g/kg). The rhizosphere microbial communities were investigated using phospholipid fatty acids analysis at tillering, panicle initiation, and maturity stages. The results showed that rice growing in YP soil accumulated 2-10 times higher contents of As in root than that in RP soil. There was a significant effect of rice growing stage, independent of soil types and As treatment, on rhizosphere microbial community composition in both YP and RP soils as depicted by canonical correspondence analysis. As contamination significantly altered rhizosphere microbial community composition only in YP soil, which showed the soil type dependency of the As contamination effect. In RP soil, the higher content of soil organic matter reduced the impact of As contamination. Soil pH explained more percentage of variation in microbial community composition than soil DOC and DON did. These influences of soil physiochemical properties on heavy metal available and rhizosphere microbial community may lay the foundation for exploration of bioremediation potential.