“试验设计与数据处理”教学改革探讨——基于本科生毕业论文常见问题的分析

“试验设计与数据处理”是食品类专业的一门重要课程。在分析毕业论文存在问题的基础上,找出这些问题存在的原因并寻求解决办法,为提高“试验设计与数据处理”课程的教学质量和教学效果提供参考和依据。     

日本农副产品加工产业分析及对于我国的启示姜丽 渭南师范学院 陕西渭南714099

本文以日本农副产品加工产品的发展历程为切入点,利用SWOT分析法对日本农副产品加工产业的优势与劣势、机遇与挑战进行了较为深入的分析,并最终根据分析结构提出了部分我国相关产业发展的启迪。      

大数据背景下的信息化育种

信息化是育种的主流趋势和必然选择。为促进作物育种信息化建设,从种质资源管理、数据采集、系谱分析、试验设计、参试进程管理、遗传解析和生理学解析、品种产业化推广等方面探讨了大数据背景下信息化在育种中的应用。指出了信息化育种实施步骤和要点,以河南省新乡市农业科学院为例,规划了软件应用、科研管理、人才培养、硬件更新、信息共享等实施信息化育种的重点步骤。认为信息化育种存在的主要问题有不被育种家广泛接受、技术有待完善和数据共享存在障碍等3个方面,并展望了其应用前景。     

山西谷子品种主要农艺性状的相关和主成分分析

为了明确山西谷子品种主要农艺性状间的关系,采用相关分析和主成分分析方法对11个山西谷子品种的10个农艺性状进行分析。结果表明：农艺性状的变异范围为1.94%~13.39%,各农艺性状的变异程度由大到小依次为单穗重、穗粒重、产量、穗长、株高、千粒重、出苗期—抽穗期天数、抽穗期—成熟期天数、出谷率、生育期。抽穗期—成熟期天数、单穗重、穗粒重、千粒重、出谷率等5个性状指标与产量呈正相关,其中,抽穗期—成熟期天数与产量呈显著正相关(P<0.05),出苗期—抽穗期天数与抽穗期—成熟期天数呈极显著负相关(P<0.01),出苗期—抽穗期天数与生育期呈极显著正相关(P<0.01)。在所有的主成分分析中,主要集中在前3个主成分,其累积贡献率达75.20%。在对高产品种综合性状评价和选育过程中,穗粒重是提高产量的关键,但同时也应注重对其他性状的综合考虑,注重选择单穗重偏高、株高偏低、生育期、穗长和出谷率适中的材料。     

利用重组自交系高密度遗传图谱定位水稻芽期耐冷QTL

为定位水稻芽期耐冷QTL,本实验以双季超级稻品种‘五丰优T025’的双亲‘五丰B’和‘昌恢T025’杂交衍生的重组自交系(recombinant inbred lines, RILs)群体为材料,对10℃低温处理的水稻幼芽的存活率、根数、根长和芽长进行了测定。利用QTL Icimapping v4.2软件,共检测到3个控制芽期耐冷性QTL：qRL1、qRL2和qBL6,分别位于第1、2、6染色体上,LOD值分别为2.98,2.51和5.26,分别解释表型变异的10.54%,8.67%和14.04%,其增效等位基因均来自于亲本‘昌恢T025’。这些QTL定位在6.75k~40.05 kb染色体区间,为后续利用这些QTL进行分子标记辅助,选育芽期耐冷籼稻新品种奠定了基础。此外,检测到13对影响水稻芽期耐冷上位性互作QTL,分布在所有12条染色体,其中第3染色体与第8染色体之间互作位点可解释的表型变异率达到21.77%,表明上位性互作QTL在调控水稻芽期耐冷过程中也发挥了重要作用。     

一种新型卷积神经网络植物叶片识别方法

为提高植物叶片识别的准确率及减少计算代价,在Pytorch框架下提出一种融合了深度卷积生成式对抗网络(DCGAN)和迁移学习(TL)的新型卷积神经网络叶片识别方法。首先,对植物叶片图像进行预处理,通过DCGAN对样本数据库扩充;其次,利用迁移学习将Inception v3模型应用于图像数据处理上,以提高植物叶片识别的准确率;最后,通过对比实验对该方法的有效性进行验证。结果表明:该方法可以获得96.57%的植物叶片识别精度,同时参数训练的迭代次数由4000次缩短到560次。     

野生动物非法交易犯罪案件信息特征分析

对野生动物非法交易案件进行信息特征分析,可以把握案件的发生规律,提供决策者参考,以便有针对性预防和打击犯罪,更好地保护野生动物资源。本研究应用大数据分析的方法,对野生动物非法交易犯罪案件的文本数据进行结构化处理,建立了word2vec模型。从犯罪因素的角度统计分析了本类案件的信息特征,包括侵害人的特征、作案行为特征、侵害的动物或动物制品、侵害的时间和案件发生的地点等。在梳理基本特征的基础上应用关联算法构建了关联规则。根据特征分析和关联规则,提出了开展季节性防控、对特定群体和场所进行有针对性预防、对上游下游犯罪进行联动打击、与网管等多部门合作,运用现代科技成果进行打击和防范的对策建议。     

Management strategies for forage rape (Brassica napus L. cv Goliath): Impact on dry-matter yield,plant reserves,morphology and nutritive value

Limited information is available on the grazing management principles of forage rape (Brassica napus L.), particularly in relation to grazing height and intensity and the impact of these on dry-matter (DM) yield and nutritive value. A glasshouse study was undertaken to investigate the effect of three defoliation heights (plant height at harvest; DH: 40, 70 and 90 cm; L, M and H DH respectively) and three defoliation intensities (height at which plants were cut; DI: 5, 20 and 35 cm of residual height; H, M and L DI respectively) on forage rape (cv Goliath) yield and nutritive value at two harvests (harvest 1, H1 and harvest 2, H2), and the impact of nitrogen (N) and water soluble carbohydrate (WSC) reserves on regrowth. Increasing DH from L to H increased estimated total DM yield (H1 plus H2) from 0.5 to 4.6 t DM/ha but DI did not affect yield. Dry-matter yield was optimized at 90 cm DH, but greater nutritive value was achieved by harvesting at lower levels of DH. Despite high in vitro DM digestibility (IVDMD; 852–889 g/kg), harvesting at 90 cm DH could not meet the protein requirement of lactating dairy cows and harvesting at lower levels risks nitrate poisoning. Our results indicate the optimum DH may be between 70 and 90 cm DH, and 20 and 35 cm DI, which requires further studies.     

A stochastic surplus production model in continuous time

Surplus production modelling has a long history as a method for managing data‐limited fish stocks. Recent advancements have cast surplus production models as state‐space models that separate random variability of stock dynamics from error in observed indices of biomass. We present a stochastic surplus production model in continuous time (SPiCT), which in addition to stock dynamics also models the dynamics of the fisheries. This enables error in the catch process to be reflected in the uncertainty of estimated model parameters and management quantities. Benefits of the continuous‐time state‐space model formulation include the ability to provide estimates of exploitable biomass and fishing mortality at any point in time from data sampled at arbitrary and possibly irregular intervals. We show in a simulation that the ability to analyse subannual data can increase the effective sample size and improve estimation of reference points relative to discrete‐time analysis of aggregated annual data. Finally, subannual data from five North Sea stocks are analysed with particular focus on using residual analysis to diagnose model insufficiencies and identify necessary model extensions such as robust estimation and incorporation of seasonality. We argue that including all known sources of uncertainty, propagation of that uncertainty to reference points and checking of model assumptions using residuals are critical prerequisites to rigorous fish stock management based on surplus production models.     

基于产业发展的宁夏生态移民村庄规划探析

分析了宁夏生态移民安置模式与产业发展现状，提出了以产业发展规划为前提指导，融合于物质空间的村庄规划方法，并阐述了宁夏生态移民中以高效农业、加工业、观光农业为主导产业的村庄规划的具体内容与方法。