基于土地利用变化的河北省坝上地区景观生态风险评价

[目的]对河北省坝上地区近40 a来的土地利用动态变化和生态风险进行分析评价并对未来趋势作出预测,为该地区生态建设和治理、可持续发展提供科学依据。[方法]基于坝上地区1980—2018年5期土地利用数据以及通过土地转移矩阵、空间相关性分析等方法揭示和预测该区1980—2026年的土地利用变化特征并评估该区生态风险水平。[结果](1)整个研究期间,坝上地区土地利用类型以耕地为主,所占比例近50%,其中,1980—2018年,耕地、林地扩张面积均超过300 km~2,草地减少近616.60 km~2,水域面积缩减36.04%,其中耕地、林地、草地之间的互相流转程度较为剧烈,空间变化上表现为各地类的重心在2000—2010年明显迁移。(2)1980—2026年,坝上地区6个时期内生态风险值全局空间自相关Moran’s I指数均在0.500左右,其空间分布表现出较高的趋同集聚性。(3)近40 a来,坝上生态风险水平升至为高风险级,其区域增加了123.22 km~2,较高风险区域分布在城镇地区,据CA-Markov模型预测,未来坝上地区中等及中等以上风险区域持续扩张,丰宁县和围场县将分别出现小规模高风险区和较高风险区。[结论](1)近40 a来坝上地区草地退化严重,水域面积显著减少,原因系安固里淖干涸所致。(2)该区生态风险水平与土地格局分布具有较强相关性,且在未来会继续升高。     

河北坝上农田垄向对土壤风蚀的影响

在河北省坝上选择试验区 ,利用移动式风洞研究了农田起垄方向对土壤风蚀的影响。结果表明 ,农田起垄方向对土壤风蚀具有影响作用 :垄向与风向成 0°时风蚀量最大 ,90°时风蚀量最小 ;在 15m·s-1风速和 3cm表土含水率为 4 5 %的条件下 ,垄向与风向成 0°时的风蚀量为 90°时的 4 8倍。为减轻土壤风蚀危害 ,在河北坝上地区农田起垄的方向宜采用与自然风向NW (西北风向 ,315°)成 90°,即东北方向 4 5°。     

河北坝上地区可持续发展的创新思路

坝上地区可持续发展应充分考虑我国经济发展的现状和其所处的大北京地区的重要区位,以全球变化为背景,以持续发展理论为先导,大胆更新观念,形成一套创新制度:建设“人控环境”,实施“大范围搞生态重建,小区域搞集约生产”制度;城市化与产业化相结合,采取“鼓励农业人口转化为非农业人口,以产业化带动城市化”的积极的城市化制度;沙漠化防治与治贫治愚相结合,采取“治愚-治沙-产权-受益”制度;确立产权制度和相应利益分配机制,对口支援与生态效益转移收费制度;生物技术与工程技术相结合,制定鼓励科技创新制度。     

Prediction of chemical composition and peroxide value in unground pet foods by near‐infrared spectroscopy

The massive development of the pet food industry in recent years has lead to the formulation of hundreds of canine and feline complete extruded foods with the objective of meeting both the needs of the animals and numerous demands from pet owners. In the meantime, highly variable raw material compositions and the industry's new production techniques oblige manufacturers to monitor all phases of the extrusion process closely in order to ensure the targeted composition and quality of the products. This study aimed at evaluating the potential of infrared technology (visible and near‐infrared spectrophotometer; 570–1842 nm) in predicting the chemical composition and peroxide value (PV) of unground commercial extruded dog foods. Six hundred and forty‐nine commercial extruded dog foods were collected. For each product, an unground aliquot was analysed by infrared instrument while a second aliquot was sent to a laboratory for proximate analysis and PV quantification. The wide range of extruded dog food typologies included in the study was responsible for the wide variability observed within each nutritional trait, especially crude fibre and ash. The mean value of the 208 pet foods sampled for PV quantification was 17.49 mEq O₂/kg fat (min 2.2 and max 94.10 mEq O₂/kg fat). The coefficients of determination in cross‐validation of NIRS prediction models were 0.77, 0.97, 0.83, 0.86, 0.78 and 0.94 for moisture, crude protein, crude fat, crude fibre, ash and nitrogen‐free extract (NFE) respectively. PV prediction was less precise, as demonstrated by the coefficient of determination in cross‐validation (0.66). The results demonstrated the potential of NIRS in predicting chemical composition in unground samples, with lower accuracy for moisture and ash, while PV prediction models suggest use for screening purposes only.     

Feasibility analysis of NIR for detecting sweet corn seeds vigor

This paper explores the feasibility of particle-based detection and grading of seed vigor based on a self-built seed single-granulation device using near infrared spectroscopy (NIRS). Sweet corn with uniform kernel size was used for this study. The seed samples were divided into three types, they were normal seeds, artificially aged seeds and heat-damaged seeds. A 2-part spectral acquisition of each seed were performed, one for the collection of seeds that fall into the detection zone within the separation pipe, another was on the static platform, whose collection was performed on 5 faces of each seed. Partial least squares discriminant analysis (PLS-DA) was used to classify the original data of the seeds. In the 2 parts, the discriminant results of the unprocessed normal seeds and the artificial accelerated aging seeds, the untreated normal seeds and the heat-damaged seeds showed that classification accuracy was higher than 98%. The research indicates that the spectral data of different positions of seeds can reflect their activity information, and it is feasible to detect and classify seeds in real time in the detection area of the separation pipeline.     

近红外光谱分析技术应用于植物叶片研究综述

近红外光谱技术（Near Infrared Spectroscopy，NIRS）作为 20 世纪 80 年代后期迅速发展起来 的一项检测技术，已被广泛应用于许多植物的各个组织和各种成分的分析。文章综述了该技术在植物叶 片研究上的应用进展，包括基于叶片特征的植物种类鉴别、植物叶片病虫害诊断、育种材料选择、叶片 内含物质含量测定等 4 个方面，并对近红外光谱检测技术的应用于植物叶片研究前景进行了展望。     

基于近红外光谱的沼液挥发性脂肪酸含量快速检测

挥发性脂肪酸（Volatile Fatty Acids，VFA）作为厌氧发酵过程的重要中间产物，其在厌氧反应器中的累积能够反映出产甲烷菌的不活跃状态或厌氧发酵条件的恶化。为了实现对农牧废弃物厌氧发酵进行过程分析和状态监控，将近红外光谱（Near Infrared Spectroscopy，NIRS）与偏最小二乘（Partial Least Squares，PLS）相结合构建玉米秸秆和畜禽粪便厌氧发酵液乙酸、丙酸和总酸含量快速检测模型。将竞争自适应重加权采样法（Competitive Adaptive Reweighted Sampling，CARS）与遗传模拟退火算法（Genetic Simulated Annealing algorithm，GSA）相结合构建CARS-GSA算法对沼液中的乙酸、丙酸和总酸进行特征波长优选，原始光谱数据1 557个波长点经预处理和波长优选后，得到乙酸、丙酸和总酸特征波长变量分别为135、101和245个，建立的回归模型验证决定系数分别为0.988、0.923和0.886，预测均方根误差（Root Mean Squared Error of Prediction，RMSEP）分别为0.111、0.120和0.727，相对分析误差分别为9.685、3.685和3.484，与全谱建模相比RMSEP分别减少了17.78%、15.49%和1.22%，能够满足农牧废弃物厌氧发酵过程发酵液中乙酸和丙酸含量的快速检测需求，基本满足总酸的检测需求。结果表明，通过构建CARS-GSA算法优选乙酸、丙酸和总酸的敏感波长变量，参与建模的波长点数量显著减少，有效降低了变量维度和模型复杂度，提升了回归模型检测精度和预测能力，为快速准确检测沼液VFA提供了新途径。     

风电开发对坝上地区生态环境的影响研究

在分析坝上地区生态环境现状的基础上,对坝上地区风力发电的优势进行了相关研究,并提出了开发风电的思路。     

近红外光谱技术在水果内部品质无损检测中的应用

针对近红外光谱分析技术在水果内部品质无损检测的应用问题，简单介绍了近红外光谱的基本原理；描述了国内外近红外光谱分析技术无损检测水果内部品质的最新研究进展；并指出当今国内外研究中存在的问题和今后进一步的研究设想。