基于蚁群优化最小二乘支持向量回归机的河蟹养殖溶解氧预测模型

养殖池塘溶解氧是河蟹赖以生存的重要指标,及时准确地掌握溶解氧浓度变化趋势是确保高密度河蟹健康养殖的关键。为提高溶解氧预测精度和效率,该文提出了蚁群算法(ACA)优化最小二乘支持向量回归机(LSSVR)的河蟹养殖溶解氧预测方法。采用蚁群算法对最小二乘支持向量回归机的模型参数进行优化,并以自动获取的最佳参数组合构建溶解氧与其影响因子间非线性预测模型。利用该模型对江苏宜兴市2010年7月20日～7月28日期间高密度养殖池塘溶解氧进行预测。研究表明,该预测模型取得较好的预测效果,与支持向量回归机和BP神经网络相比,模型评价指标均方根误差、相对均方误差均值、平均绝对误差和和决定系数和运行时间分别为0.0328、0.0016、0.0448、0.9916和3.3275s均优于其他预测方法,ACA-LSSVR模型不仅计算复杂度低、收敛速度快、预测精度高、泛化能力强,还能满足实际高密度河蟹养殖溶解氧管理的需要,为其他领域的水质预测提供参考。     

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。     

基于遗传算法最小二乘支持向量机的耕地变化预测

针对耕地变化内部规律与模拟方法进行研究,提出最小二乘支持向量机耕地变化预测方法,有效构建耕地变化与耕地变化影响因子之间复杂的非线性关系模型。利用遗传算法全局寻优功能优化最小二乘支持向量机内部参数,提高最小二乘支持向量机耕地变化预测模型精度。利用该模型对江苏无锡市1987－2000年期间耕地变化进行预测,并与多元回归、GM(1,1)、BP网络、支持向量机（SVM）耕地预测模型和实际调查耕地变化数据进行比较分析。预测精度评价结果证实,该方法耕地预测精度远高于多元回归、GM(1,1),BP网络模型,略高于SVM模型,但算法复杂度和计算效率远优于SVM预测模型,是一种有效的耕地变化预测方法。     

主成分分析和长短时记忆神经网络预测水产养殖水体溶解氧

为了提高水产养殖溶解氧预测的精度,提出了基于主成分分析(principal component analysis,PCA)和长短时记忆神经网络(long short-term memory,LSTM)的水产养殖溶解氧预测模型。首先通过主成分分析提取水产养殖溶解氧的关键影响因子,消除了原始变量之间的相关性,降低了模型输入向量维度;然后,在Tensorflow深度学习框架的基础上建立LSTM神经网络的水产养殖溶解氧预测模型;最后,利用该模型对浙江省淡水水产养殖研究所综合实验基地某池塘溶解氧进行验证。试验结果表明:该模型与BP神经网络等其他浅层模型相比,模型评价指标平均绝对误差、均方根误差和平均绝对误差分别为0.274、0.089和0.147,均优于传统的预测方法;该模型具有良好的预测性能和泛化能力,能够满足水产养殖溶解氧精确预测的实际需要,可以为水产养殖水质精准调控提供参考。     

基于高光谱的柑橘叶片钾含量快速诊断模型

及时准确地监测柑橘树体钾营养状况,有助于科学施肥,提高柑橘果实的品质和产量。试验对采集的W·默科特叶片钾含量及叶片光谱信息进行相关性分析,利用主成分分析和连续投影算法进行降维处理,同时结合偏最小二乘回归和最小二乘支持向量机回归分别建立了叶片钾含量预测模型。结果显示,柑橘叶片钾含量特征波长主要集中在450～600 nm、700 nm左右、980～1030 nm区域;最小二乘支持向量机回归模型的预测效果明显优于偏最小二乘回归模型,预测集相关系数达0.91。结果表明,利用高光谱成像技术结合最小二乘支持向量机回归可实现对柑橘叶片钾含量的快速诊断。     

东北地区稻谷储藏期间脂肪酸含量的预测模型

粮食储备是保障国家粮食安全的重要物质基础,谷物中脂肪酸含量是粮食储藏过程中品质变化的敏感性指标。为了实现绿色储粮安全管理,该文采用多元线性回归(multiple linear regression,MLR)、人工神经网络(artificial neural network, ANN)、支持向量回归(support vector regression, SVR)、最小二乘支持向量回归(least square support vector regression,LSSVR)等机器学习算法模型,对东北地区稻谷储藏过程中的脂肪酸含量(以KOH计)进行预测。通过主成分分析(principal component analysis,PCA)方法筛选稻谷关键储藏参数,得到4个影响稻谷脂肪酸含量的关键因子,分别为稻谷入仓水分、入仓脂肪酸含量、储藏有效积温、检测粮温。然后,将得到的关键因子进行归一化处理,再分别输入到MLR、ANN、SVR、LSSVR模型,采用决定系数R2、平均绝对误差(MAE)、平均绝对百分比误差(MAPE)、均方根误差(RMSE)等评价指标对不同模型的预测性能进行对比,探讨稻谷脂肪酸含量预测的最优模型算法。研究结果表明,LSSVR模型的决定系数R2、MAE、MAPE、RMSE分别为0.911、0.275 mg/100 g、1.604%、0.348 mg/100 g,预测效果略优于MLR,明显优于ANN和SVR,LSSVR和MLR模型可作为稻谷储藏期间脂肪酸含量预测的方法。该研究实现了稻谷脂肪酸含量的预测,为科学储粮、安全绿色储粮提供参考。     

基于自适应进化相关向量机的耕地面积预测模型

为解决耕地面积预测模型建立过程中的非线性、稀疏化及结果可靠性评价等问题,该文将相关向量机与差分进化优化算法进行融合及改进,提出基于自适应进化相关向量机的耕地面积预测模型。该文以黄石市为例,建立基于自适应进化相关向量机的短期、中期耕地预测模型,并与多元线性回归、BP神经网络、支持向量机算法在精度、计算效率及可靠性方面进行对比分析。试验验数据表明,自适应进化相关向量机的预测精度大约是其余3种方法的2倍以上;模型的计算效率是多元线性回归方法的2倍,比BP神经网络、支持向量机高出2个数量级;测试数据的实际耕地面积均在自适应进化相关向量机估计的95%置信度的置信区间内,并且由后验差比、小误差概率判定模型等级属于"好"。基于以上数据,证实该模型是一种精度高、计算快、可靠性强的耕地预测新方法。     

基于集合经验模态分解和人工蜂群算法的工厂化养殖pH值预测

针对单一预测模型预测养殖pH值精度低等问题,提出集合经验模态分解(ensemble empirical mode decomposition,EEMD)和改进人工蜂群算法(improve artificial bee colony,IABC)相结合的南美白对虾工厂化养殖pH值组合预测模型。在建模过程中,利用EEMD算法对原始pH值时间序列进行多尺度分解,得到一组平稳、互不耦合的子序列;根据各子序列变化特征选择适宜的单项预测方法并建模,通过改进人工蜂群(IABC)算法优化复杂非线性组合预测模型目标函数权重系数,构建了工厂化养殖pH值非线性组合预测模型。利用该模型对广东省湛江市2014年9月8日-2014年9月15日期间工厂化养殖pH值进行预测,结果表明,该预测模型取得了较好的预测效果,与模拟退火优化BP神经网络(simulated Annealing-BP neural network,SA-BPNN)和遗传算法优化最小二乘支持向量回归机(genetic algorithm-least square support vector regression,GA-LSSVR)对比分析,模型评价指标平均绝对百分比误差MAPE、均方根误差、平均绝对误差MAE和相关系数R2分别为0.0035、0.0274、0.0224和0.9923,均表明该文提出的组合预测模型具有更高预测精度,能够满足实际南美白对虾工厂化养殖pH值精细化管理需要,也为其他领域pH值预测提供参考。     

基于最小二乘向量机土壤水分动态模拟与分析

土壤水分动态的模拟对水分循环与农业生产中水分的合理利用与管理具有重要的意义.应用最小二乘支持向量机对加入气象因子随机变量的红壤中土壤水分动态变化进行了训练、检验及模拟.结果表明,最小二乘支持向量机相比与神经网络方法不论是模拟性能指标还是建模的数学意义都有更好的可靠性和优越性;本研究应用最小二乘支持向量机对土壤水分动态日变化进行了模拟,并采用bior 3.3小波函数5层分解提取日变化趋势图进而把该研究区土壤水分日变化划分为4个阶段,其结果可为研究区水分合理利用和土壤墒情的预测预报提供科学依据.     

基于游程检测法重构集合经验模态的养殖水质溶解氧预测

为了提高水产养殖中溶解氧的预测精度,该文提出了基于集合经验模态(ensemble empirical mode decomposition,EEMD)分解、游程检测法重构、适宜的单项预测算法建模和BP神经网络非线性叠加的组合预测模型。该模型首先将溶解氧原始序列用EEMD分解法进行分解,得到了多个分量;其次,用游程检测法将这些分量重构成高频分量、中频分量和低频分量等3个分量;接着,针对高频分量波动性大且复杂、中频分量呈现周期性、低频分量几乎呈线性的特点,采用粒子群(particle swarm optimization,PSO)优化的最小二乘支持向量机(least square support vector machine,LSSVM)对高频项进行预测,采用极限学习机(extreme learning machine,ELM)对中频项预测,采用非线性回归(nonlinear regression method,NRM)对低频项预测;最后,将3个分量预测的结果用BP神经网络进行重构得到最终的预测结果。将该模型应用于江苏省溧阳市埭头黄家荡特种水产养殖场的溶解氧预测中,试验表明,该种以游程检测法重构EEMD为基础的混合预测模型的预测精度高于PSO-LSSVM和单一的ELM预测模型。在预测未来48 h的溶解氧值时,该模型的预测值与实测值的均方根误差RMSE为0.099 2、平均相对误差均值MAPE为0.078、平均绝对误差MAE为0.015 5,R~2为0.995 5。表明该模型有较好的预测精度和泛化能力,能够满足现代化水产养殖业对溶解氧精细化管理的高要求。     

低氮和干旱胁迫对富士和秦冠生长及氮素利用的影响

【目的】以富士（Fuji）、 秦冠（Qinguan）嫁接在平邑甜茶（Malus hupehensis Rehd.）上的当年生盆栽苗为试验材料,采用砂培方法,研究了缺氮胁迫和干旱对富士和秦冠生长情况、 光合参数、 植株各部位氮磷钾含量及氮素利用效率的影响,分析比较了低氮干旱条件下富士和秦冠生长及氮素利用的差异,以期为果树生产高效肥水利用提供理论指导。【方法】试验共设四个处理: 正常氮正常水（ZZ）、 低氮正常水（DZ）、 正常氮干旱（ZG）、 低氮干旱（DG）。氮素和水分均设置两个水平,分别为正常氮（6 mmol/L NO-3-N）、 低氮（0.3 mmol/LNO-3-N）、 正常供水（保持盆中砂子相对含水量为饱和含水量的80%~85%）、 干旱处理（保持盆中砂子相对含水量为饱和含水量的60%~65%）。【结果】富士和秦冠的生物量（茎和叶）、 株高茎粗等生长指标以及光合速率、 气孔导度、 蒸腾速率均为正常氮正常水（ZZ）＞低氮正常水（DZ）＞正常氮干旱（ZG）＞低氮干旱（DG）,并且相对应处理下秦冠的以上指标均高于富士;正常供水下,缺氮处理使富士、 秦冠的根冠比比正常氮处理均有所增加,富士提高了2.05%,秦冠提高了22.40%。富士和秦冠的氮、 磷、 钾含量均表现出正常氮正常水（ZZ）＞低氮正常水（DZ）＞正常氮干旱（ZG）＞低氮干旱（DG）; 氮、 钾元素含量在植株各部位的分布顺序依次是叶＞根＞茎,磷元素则是根＞叶＞茎;光合氮素利用效率（PNUE）和氮素利用效率表现为秦冠处理之间差异极显著,富士处理之间差异不显著;秦冠的PNUE和NUE明显高于富士,在低氮正常水（DZ）处理下,秦冠氮肥利用率比富士高42.07%,在低氮干旱（DG）处理下高64.14%;低氮胁迫下富士和秦冠的NUE显著提高,并且秦冠提高的幅度高于富士。【结论】施用氮肥能够显著提高富士与秦冠的干物质量,同等水肥条件下,秦冠生长优于富士;水分亏缺会减少叶片对氮的吸收,干旱条件下适度增施氮肥,可提高果树的抗旱能力;低氮干旱胁迫下秦冠的生长指标、 光合指标及氮素利用效率指标均优于富士,表现出较强的抗低氮干旱胁迫的能力。     

Pasture Vegetation Elemental Analysis by Laser-Induced Breakdown Spectroscopy

Laser-induced breakdown spectroscopy (LIBS) is a new technique for the analysis of plant material. This study investigates the application of LIBS to pasture-based plant samples. The LIBS measurements were obtained from pelletized pasture samples (100 samples) that had been also analyzed by inductively coupled plasma–optical emission spectroscopy (ICP-OES) following microwave digestion for calibration and comparison purposes. Comparisons for elements sodium (Na), potassium (K), magnesium (Mg), calcium (Ca), manganese (Mn), iron (Fe), copper (Cu), zinc (Zn), boron (B), phosphorus (P), and sulfur (S) showed that LIBS could be used for almost all the standard profile total elements with concentrations down to low mg/kg levels (observed error of Na: 0.024 percent, K: 0.18 percent, Mg: 0.016 percent, Ca: 0.073 percent, P: 0.017 percent, Mn: 31 mg/kg, Fe: 150 mg/kg, Zn: 6.6 mg/kg, and B: 1.1 mg/kg). Elemental analysis at less than mg/kg levels was not possible using LIBS. The elements S and Cu were particularly difficult to analyze with reliability using LIBS at the concentration levels found in the plant samples. Replacing microwave digestion and subsequent ICP analysis with a direct analysis of dried plant samples using LIBS has the potential to improve the productivity and reduce the cost of testing.     

Faculty positions:Center for Agricultural Resources Research,Chinese Academy of Sciences

正The Center for Agricultural Resources Research(CARR),the Institute of Genetics and Developmental Biology(IGDB),Chinese Academy of Sciences,invites applicants for several research group leader positions.CARR is one of the research organizations in Chinese Academy of Sciences(CAS).We seek nominations and applications from individuals who have expertise and a record of accomplishment in research areas related to ecology,agro-hydrology,     

Biodiversity and ecogeography of wild Lactuca spp. in some European countries

Staff members of the Department of Botany of Palacký University in Olomouc and Gene Bank Department – Workplace Olomouc, Research Institute of Crop Production in Prague, Czech Republic, conducted an expedition in seven European countries (Austria, Czech Republic, France, Germany, Italy, the Netherlands, Switzerland) in August/September 1999 to collect wild Lactuca spp. germplasm and study its geographic distribution, ecology and biodiversity. During the mission, more than 600 locations were visited resulting in the collection of 602 seed samples (accessions) of wild Lactuca species and 13 seed samples of related genera (Chondrilla and Mycelis). Lactuca serriola f. serriola, L. serriola f. integrifolia, L. saligna and L. viminea subsp. chondrilliflora were prevalent in southern Europe (Italy, France), however, only L. serriola was common in central and western Europe (Austria, Czech Republic, Germany, Netherlands, Switzerland). The greatest diversity of Lactuca species was found in France, where also the most seed samples (165) were collected. The most characteristic habitats with a high density of Lactuca spp. populations were observed along roads and highways, grassy ditches, ruderal communities, and dust-heaps. Natural infections by powdery mildew (Erysiphe cichoracearum) and downy mildew (Bremia lactucae) on some wild Lactuca spp. were observed. Recent observations concerning the geographic distribution, population structure, habitats, and natural occurrence of diseases of Lactuca spp. are discussed. This assemblage of genetic resources of Lactuca spp. can serve as the basis of future studies of species diversification, spatial population structure, plant microevolution, domestication processes, and genetic variability of host-parasite interactions.     

Macroinvertebrates in North American tallgrass prairie soils: effects of fire, mowing, and fertilization on density and biomass

The responses of tallgrass prairie plant communities and ecosystem processes to fire and grazing are well characterized. However, responses of invertebrate consumer groups, and particularly soil-dwelling organisms, to these disturbances are not well known. At Konza Prairie Biological Station, we sampled soil macroinvertebrates in 1994 and 1999 as part of a long-term experiment designed to examine the effects and interactions of annual fire, mowing, and fertilization (N and P) on prairie soil communities and processes. For nearly all taxa, in both years, responses were characterized by significant treatment interactions, but some general patterns were evident. Introduced European earthworms (Aporrectodea spp. and Octolasion spp.) were most abundant in plots where fire was excluded, and the proportion of the total earthworm community consisting of introduced earthworms was greater in unburned, unmowed, and fertilized plots. Nymphs of two Cicada genera were collected (Cicadetta spp. and Tibicen spp.). Cicadetta nymphs were more abundant in burned plots, but mowing reduced their abundance. Tibicen nymphs were collected almost exclusively from unburned plots. Treatment effects on herbivorous beetle larvae (Scarabaeidae, Elateridae, and Curculionidae) were variable, but nutrient additions (N or P) usually resulted in greater densities, whereas mowing usually resulted in lower densities. Our results suggest that departures from historical disturbance regimes (i.e. frequent fire and grazing) may render soils more susceptible to increased numbers of European earthworms, and that interactions between fire, aboveground biomass removal, and vegetation responses affect the structure and composition of invertebrate communities in tallgrass prairie soils.     

Properties of anaerobically digested and composted municipal solid waste assessed by linking soil mesofauna dynamics and nitrogen modelling

We have studied the effect of anaerobically digested (ADMSW) and composted municipal solid waste (CMSW) on mineralization and foodweb dynamics to verify the hypothesis that ADMSW would immobilize N right after addition to soil in contrast to addition with CMSW. Another hypothesis was that the mesofauna (enchytraeids and microarthropods) would stimulate N release from the decomposer community. We measured excretion of -N and urea-N from the mesofauna and hypothesized that enchytraeids would release urea. ADMSW and CMSW were amended to pots with sandy loam and barley. The pots were divided into treatments with or without mesofauna. Mesofauna, plant N and biomass, soil N and ergosterol (fungal biomass) were measured over a 113-day period of four equidistant samplings. Soil respiration, N mineralization and N release by the mesofauna were modelled from concurrent studies. ADMSW- and CMSW-treated soils initially (<20 days) immobilized N. The amendments did not increase plant growth substantially, and this was probably due to N-limitation in the early stages of plant growth. Enchytraeid abundance was about three times higher in ADMSW- than CMSW-treated soils, indicating that ADMSW contained more labile compounds, bacteria, and microfauna. The mesofauna did not affect N-content, but the cumulated -N excreted by the mesofauna was estimated to be substantial and about one-fifth of total plant N in ADMSW. An explanation for this discrepancy might be that in the absence of the mesofauna, other members of the detrivore and microbivore community performed the mesofauna’s function. Neither enchytraeids nor microarthropods excreted urea.     

Faculty positions: Center for Agricultural Resources Research,Chinese Academy of Sciences

正The Center for Agricultural Resources Research(CARR),the Institute of Genetics and Developmental Biology(IGDB),Chinese Academy of Sciences,invites applicants for several research group leader positions.CARR is one of the research organizations in Chinese Academy of Sciences(CAS).We seek nominations and applications from individuals who have expertise and a record of accomplishment in research areas related to ecology,agro-hydrology,     

Faculty positions: Center for Agricultural Resources Research,Chinese Academy of Sciences

正The Center for Agricultural Resources Research(CARR),the Institute of Genetics and Developmental Biology(IGDB),Chinese Academy of Sciences,invites applicants for several research group leader positions.CARR is one of the research organizations in Chinese Academy of Sciences(CAS).We seek nominations and applications from individuals who have expertise and a record of accomplishment in research areas related to ecology,agro-hydrology,     

Variation in quality parameters between and within 14 Nordic tree fruit and berry species

Abstract

A 3-year study was carried out to investigate quality parameters in 14 tree fruit and berry species grown in southern Norway. The species were blueberry, apple, aronia, sour cherry, sweet cherry, red raspberry, strawberry, blackcurrant, gooseberry, red currant and elderberry, harvested along with wild bilberry, cloudberry and lingonberry. Significant differences between species were identified for all quality parameters. The coefficient of variation between species was lowest for pH (12.5%), dry matter (18.9%) and soluble solids (25.3%), followed by titratable acids (59.3%), total phenolics (83.8%), antioxidant capacity FRAP (85.7%) and antiradical power by the DPPH-assay (97.8%), total monomeric anthocyanins (132%) and ascorbic acid (137%). Average coefficient of variation within species were lower and ranged from 4 (pH) to 62% (ascorbic acid). Only the FRAP values were significantly affected by harvesting year with lower levels in 2004 than in 2005 and 2006. There were significant interactions between species and harvesting year for dry matter, soluble solids, pH, ascorbic acid and FRAP. The results indicate generic ranges in composition within species independent upon growing location and climate, and the composition of the tree fruits and berries is not likely to deviate from these ranges. It is concluded that desirable composition of tree fruits and berries and their products should primarily be achieved by selection among species rather than searching fors broadened variation within individual species.     

Potassium Fixation and Release Characteristics in Rhizosphere and Nonrhizosphere Soils for a Rapeseed–Rice Cropping Sequence

Potassium (K) fixation and release in soil are important factors in the long-term sustainability of a cropping system. Changes in K concentration and characteristics of K fixation and release in rhizosphere and nonrhizosphere soils in the rapeseed (Brassica napus L.)–rice (Oryza sativa L.) rotation were investigated using a rhizobox system. The concentrations of different forms of K in both rhizosphere and nonrhizosphere soils decreased with plants compared to without plants, regardless of K fertilizer application. Potassium uptake by crops mainly came from the rhizosphere soil. In the treatment without K fertilizer (–K), the main form of K supplied by the soil to the crops was 1.0 mol L^?1 nitric acid (HNO₃) nonextractable K, followed by nonexchangeable K, and then exchangeable K. In the treatment with K fertilizer (+K), the main K forms supplied by the soil to the crops were exchangeable K and nonexchangeable K. The amount and rate of K fixation after one cycle of the rapeseed–rice rotation was greater in rhizosphere soil than in nonrhizosphere soil. The amount and rate of K fixation of soil in the +K treatment were significantly less than in the –K treatment. The cumulative amounts of K released with 1.0 mol L^?1 ammonium acetate (NH₄OAc) and 1.0 mol L^?1 HNO₃ extraction increased with the increasing numbers of extractions, but the K-releasing power of soil by successive extraction decreased gradually and finally became almost constant. The release of K was less in rhizosphere soil than in nonrhizosphere soil. The release of K in the +K treatment was similar to that in the –K treatment in rhizosphere soil, but the K release in nonrhizosphere soil was greater with the +K than the –K treatment. Overall, the information obtained in this study will be helpful in formulating more precise K fertilizer recommendations for certain soils.