人工林伐区木材运输作业模式选优

对南方人工林伐区的常用4种木材运输作业模式进行综合效益分析与评价.结果表明:在相同的作业条件下,不同木材运输作业模式,其经济效益、生态效益和社会效益以及综合效益均不同.建议林业生产决策部门在选择人工林伐区运材作业模式时应综合考虑其经济、生态和社会效益,在有水路运输条件的伐区,应优先选择船运木材或排运木材;在无水路运输条件的伐区,则应优先选择农用车运材.     

黑龙江省国有林区林业产业结构调整与优化研究

黑龙江省国有林区林业曾为我国经济与社会建设做出过突出贡献,尽管目前该区域已形成了较完整的林业产业体系,但林业产业结构的诸多弊端表现得愈发突出,致使林业产业效益低下.随着环境的变化,黑龙江省国有林区林业产业结构的调整与优化显得越来越必要和迫切.黑龙江省国有林区林业产业结构的调整与优化必须依据相关理论,根据林业产业发展的特点和规律,遵循相关的经济政策进行.同时根据产业结构调整优化的目标,形成科学合理的产业发展模式,并采取有效的措施,达到黑龙江省国有林区产业结构合理化和高度化的目的.     

基于YOLOv5s改进模型的小白菜虫害识别方法

小白菜是中国种植面积较广、深受大众喜爱的蔬菜,但真实菜地环境中虫害往往出现在叶片的特定区域,且受环境因素如光照和背景干扰较大,影响对其的智能检测。为提高小白菜虫害的检测效率和准确率,该研究提出一种基于YOLOv5s网络框架改进的YOLOPC小白菜虫害识别模型。首先,引入CBAM（Convolutional Block Attention Module）注意力机制,将其放在CBS（卷积层Convolution+归一化层Batch normalization+激活函数层SILU）的输入端构成CBAM-CBS的结构,动态调整特征图中各个通道和空间位置的权重;使用上采样和1×1卷积操作来调整特征图的尺寸和通道数,实现不同层次特征的融合,增强模型的特征表示能力。同时,改进损失函数,使其更适合边界框回归的准确性需求;利用空洞卷积的优势提高网络的感受野范围,使模型能够更好地理解图像的上下文信息。试验结果表明,与改进前的YOLOv5s模型相比,YOLOPC模型对小白菜小菜蛾和潜叶蝇虫害检测的平均精度（mean Average Precision, mAP）达到91.40%,提高了12.9个百分点;每秒传输帧数（Frame Per Second, FPS）为58.82帧/s,增加了11.2帧/s,增加幅度达23.53个百分点;参数量仅为14.4 MB,降低了25.78个百分点。与经典的目标检测算法SSD、Faster R-CNN、YOLOv3、YOLOv7和YOLOv8相比,YOLOPC模型的平均精度分别高出20.1、24.6、14、13.4和13.3个百分点,此外,其准确率、召回率、帧速率和参数量均展现出显著优势。该模型可为复杂背景下小白菜虫害的快速准确检测提供技术支持。     

基于遥感信息和产量形成过程的小麦估产模型

为提高小麦遥感估产的精确性和机理性,在广域环境条件下进行了多品种小麦的种植试验,并基于遥感信息获取的瞬时性与广域性,结合小麦产量形成的生理生态过程及其与气候环境的相互关系,建立了较为简化的小麦估产模型.通过组件化的设计方法实现了遥感信息和估产模型的耦合,即利用抽穗期遥感影像反演的LAI和生物量及时替换小麦估产模型对应参数变量,进而实现对小麦产量的估测.通过试验验证,小麦产量的预测值与实测值较为一致,预测小麦产量的RMSE为354.18 kg·ha-1,利用小麦估产模型可以对不同年份、不同区域的小麦产量形成情况进行监测预报.     

进水流速对圆形循环水养殖池流场特性影响的数值模拟

通过对工厂化循环水养殖进水流速的智能调控,可降低饵料残留,避免水质恶化。为此,本研究采用数值模拟方法探究了进水流速对工厂化循环水养殖池流场特性的影响,并基于该研究设计出一套确定进水流速调控的实验方法。首先,通过对比Standard k-ε、RNG k-ε和Realizable k-ε 3种湍流模型及多种壁面函数的仿真效果,确定RNG k-ε模型和标准壁面函数作为仿真配置。同时,针对多相流模型,对欧拉多相流模型和DPM离散相模型进行对比,为提高计算准确性选用DPM离散相模型,并基于上述模型进行网格无关性验证、制定网格划分方案。其次,以大菱鲆(Scophthalmus maximus)养殖为例,模拟不同进水流速下养殖池流场、排污和水温调节的效果。最后,针对仿真结果提出进水流速调控方案。结果显示,日常采用1.0 m/s的进水流速,可有效提高适宜流速区面积并控制水处理成本;投饵前,采用0.2 m/s的进水流速可以解决循环水养殖中存在的饵料浪费问题;进食结束后,采用1.2 m/s的进水流速可快速排出残饵避免水质恶化;水温异常时,采用15 ℃的水、以1.2 m/s的进水流速注水230 s,可使20 ℃的水下降到正常水平,精准化控制水温。采用本研究提出的方法,可针对不同养殖生物和养殖环境设计进水流速智能调控策略,可用于解决循环水养殖过程中饵料浪费、水质变差和水温异常等问题。     

绿色经济体系下饲料企业经济模式转变研究

近年来,绿色经济成为席卷全球的潮流.绿色经济带给经济社会的改变将是全面而深刻的,饲料行业也不会例外.绿色经济既会给饲料行业带来落后产能淘汰、产业结构升级的机遇,也会带来利润下降、承包上升的短期阵痛.饲料企业想要抓住机遇、迎接挑战,就必须尽快转变当前的经济模式,建立绿色企业文化,加大研发投入,调整生产模式,加强上下游产业...     

不结球白菜维生素C和可溶性糖含量的遗传分析

采用主基因—多基因混合遗传模型分析方法,对不结球白菜乌塌菜×矮脚黄、雪克青×矮脚黄两个组合的维生素Ｃ、可溶性糖含量进行单世代和联合世代遗传分析。结果表明,两组合中维生素Ｃ含量遗传符合一个主基因和多基因的混合遗传模型,主基因遗传率为５２６８％～７４１２％。可溶性糖在雪克青×矮脚黄组合中也符合主基因—多基因遗传模型,主基因遗传率为８９７３％～８９７９％。维生素Ｃ和可溶性糖主基因效应均以加性效应为主,在乌塌菜×矮脚黄组合中,两性状主基因有较明显的负向显性效应,在雪克青×矮脚黄组合中,显性效应不明显。育种实践中应注重对主基因加性效应的利用。     

Model uncertainty in the ecosystem approach to fisheries

Fisheries scientists habitually consider uncertainty in parameter values, but often neglect uncertainty about model structure, an issue of increasing importance as ecosystem models are devised to support the move to an ecosystem approach to fisheries (EAF). This paper sets out pragmatic approaches with which to account for uncertainties in model structure and we review current ways of dealing with this issue in fisheries and other disciplines. All involve considering a set of alternative models representing different structural assumptions, but differ in how those models are used. The models can be asked to identify bounds on possible outcomes, find management actions that will perform adequately irrespective of the true model, find management actions that best achieve one or more objectives given weights assigned to each model, or formalize hypotheses for evaluation through experimentation. Data availability is likely to limit the use of approaches that involve weighting alternative models in an ecosystem setting, and the cost of experimentation is likely to limit its use. Practical implementation of an EAF should therefore be based on management approaches that acknowledge the uncertainty inherent in model predictions and are robust to it. Model results must be presented in ways that represent the risks and trade‐offs associated with alternative actions and the degree of uncertainty in predictions. This presentation should not disguise the fact that, in many cases, estimates of model uncertainty may be based on subjective criteria. The problem of model uncertainty is far from unique to fisheries, and a dialogue among fisheries modellers and modellers from other scientific communities will therefore be helpful.     

Temperature-dependent stock-recruitment model for walleye pollock (Theragra chalcogramma) around northern Japan

Changes in fish year‐class strength have been attributed to year‐to‐year variability in environmental conditions and spawning stock biomass (SSB). In particular, sea temperature has been shown to be linked to fish recruitment. In the present study, I examined the relationship between sea surface temperature (SST), SSB and recruitment for two stocks of walleye pollock (Theragra chalcogramma) around northern Japan [Japanese Pacific stock (JPS) and northern Japan Sea stock (JSS)] using a temperature‐dependent stock‐recruitment model (TDSRM). The recruitment fluctuation of JPS was successfully reproduced by the TDSRM with February and April SSTs, and February SST was a better environmental predictor than April SST. In addition, the JPS recruitment was positively related to February SST and negatively to April SST. The JSS recruitment modeled by the TDSRM incorporating February SST was also consistent with the observation, whereas the relationship between recruitment and February SST was negative, that is the opposite trend to JPS. These findings suggest that SST in February is important as a predictor of recruitment for both stocks, and that higher and lower SSTs in February act favorably on the recruitment of JPS and JSS respectively. Furthermore, Ricker‐type TDSRM was not selected for either of the stocks, suggesting that the strong density‐dependent effect as in the Ricker model does not exist for JPS and JSS. I formulate hypotheses to explain the links between SST and recruitment, and note that these relationships should be considered in any future attempts to understand the recruitment dynamics of JPS and JSS.     

全子叶生物活性豆腐凝胶特性的研究

通过因子筛选实验,确定了接种量、微生物转谷氨酰胺酶(MTG)用量和水豆比是影响全子叶生物活性豆腐凝胶特性的关键因子。在此基础上,采用响应曲面法(Response SurfaceMethodology,RSM)分别建立了豆腐硬度和持水率的二次多项数学模型,验证了模型的有效性并探讨了上述3个因子的交互作用。从产品成本和凝胶特性综合考虑,选择出最佳配比,即乳酸菌接种量为105cfu/mL,MTG用量为347 U/L,水豆比为8.5,其硬度和持水率实测值分别为44.8g和89.2%,可生产出富含乳酸菌和几乎全部大豆营养的健康豆腐。