Detection of Ecballium elaterium in hedgerow olive orchards using a low-cost uncrewed aerial vehicle and open-source algorithms

BACKGROUND

Ecballium elaterium (common name: squirting cucumber) is an emerging weed problem in hedgerow or superintensive olive groves under no tillage. It colonizes the inter-row area infesting the natural or sown cover crops, and is considered a hard-to-control weed. Research in other woody crops has shown E. elaterium has a patchy distribution, which makes this weed susceptible to design a site-specific control strategy only addressed to E. elaterium patches. Therefore, the aim of this work was to develop a methodology based on the analysis of imagery acquired with an uncrewed aerial vehicle (UAV) to detect and map E. elaterium infestations in hedgerow olive orchards.

RESULTS

The study was conducted in two superintensive olive orchards, and the images were taken using a UAV equipped with an RGB sensor. Flights were conducted on two dates: in May, when there were various weeds infesting the orchard, and in September, when E. elaterium was the only infesting weed. UAV-orthomosaics in the first scenario were classified using random forest models, and the orthomosaics from September with E. elaterium as the only weed, were analyzed using an unsupervised algorithm. In both cases, the overall accuracies were over 0.85, and the producer's accuracies for E. elaterium ranged between 0.74 and 1.00.

CONCLUSION

These results allow the design of a site-specific and efficient herbicide control protocol which would represent a step forward in sustainable weed management. The development of these algorithms in free and open-source software fosters their application in small and medium farms. © 2022 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.     

Genetic evaluation using random regression models with different covariance functions for test‐day milk yield in an admixture population of Thailand goats

The objectives of this study were to compare covariance functions (CF) and estimate the heritability of milk yield from test‐day records among exotic (Saanen, Anglo‐Nubian, Toggenburg and Alpine) and crossbred goats (Thai native and exotic breed), using a random regression model. A total of 1472 records of test‐day milk yield were used, collected from 112 does between 2003 and 2006. CF of the study were Wilmink function, second‐ and third‐order Legendre polynomials, and linear splines 4 knots located at 5, 25, 90 and 155 days in milk (SP25–90) and 5, 35, 95 and 155 of days in milk (SP35–95). Variance components were estimated by restricted maximum likelihood method (REML). Goodness of fit, Akaike information criterion (AIC), percentage of squared bias (PSB), mean square error (MSE), and empirical correlation (RHO) between the observed and predicted values were used to compare models. The results showed that CF had an impact on (co)variance estimation in random regression models (RRM). The RRM with splines 4 knots located at 5, 25, 90 and 155 of days in milk had the lowest AIC, PSB and MSE, and the highest RHO. The heritability estimated throughout lactation obtained with this model ranged from 0.13 to 0.23.     

Genetic analysis of fat‐to‐protein ratio,milk yield and somatic cell score of Holstein cows in Japan in the first three lactations by using a random regression model

We estimated the genetic parameters of fat‐to‐protein ratio (FPR) and the genetic correlations between FPR and milk yield or somatic cell score in the first three lactations in dairy cows. Data included 3 079 517 test‐day records of 201 138 Holstein cows in Japan from 2006 to 2011. Genetic parameters were estimated with a multiple‐trait random regression model in which the records within and between parities were treated as separate traits. The phenotypic values of FPR increased soon after parturition and peaked at 10 to 20 days in milk, then decreased slowly in mid‐ and late lactation. Heritability estimates for FPR yielded moderate values. Genetic correlations of FPR among parities were low in early lactation. Genetic correlations between FPR and milk yield were positive and low in early lactation, but only in the first lactation. Genetic correlations between FPR and somatic cell score were positive in early lactation and decreased to become negative in mid‐ to late lactation. By using these results for genetic evaluation it should be possible to improve energy balance in dairy cows.     

景电灌区农田防护林衰败及优化模式

景电灌区农田防护林网是景电灌区防护林体系的重要组成部分,通过调查景电灌区农田防护林衰败现状,分析退化原因,提出优化改造模式,为景电灌区农田防护林更新改造从而发挥可持续效益提供技术支撑。结果表明,1)以杨树为主要树种的景电灌区农田防护林网目前呈严重衰败状态,尤其在个人管护的区域,残缺断代现象严重,部分地方甚至基本消失;2)病虫危害,耗水、胁地严重而被砍伐,耕地次生盐渍化导致树木生长不良、枯死,树种单一、结构不合理,管理不到位等是造成农田防护林衰败的主要原因;3)三倍体毛白杨(Populus tomentosa)、廊坊(P.langfanggensis)、樟子松(Pinus sylvestris)、刺槐(Robinia pseucdoacacia)、白蜡(Fraxinus chinensis)、鸣山大枣(Jujube minshan)等树种为该地区农田防护林建设的适宜树种,可采用农田防护林杨树优势树种轮换、针叶常绿树种优化改造、生态经济型防护林网营造等模式对景电灌区农田防护林网进行更新改造。农田防护林网的改造,将对完善防护林体系,保障景泰绿洲的安全产生重要意义。     

华北刺槐林与自然恢复植被土壤微生物量碳、氮含量四季动态

【目的】土壤微生物量碳、氮是植被所需碳、氮的重要“源”或“库”,是公认的综合评价土壤质量或肥力的重要指标,也是土壤生态系统变化的预警及敏感指标,研究其动态变化,可为退耕还林及后期管理决策提供科学依据,并为深入研究林地碳氮循环及温室气体排放提供参考。【方法】以农田( FL)为对照,研究华北土石山区10年生刺槐林、43年生刺槐林、自然恢复植被( NRV)土壤微生物量碳、氮的四季动态变化,并对各样地微生物量碳、氮对土壤营养库的贡献率进行对比研究。【结果】各样地微生物量碳、氮随土层加深而逐渐下降,其季节动态变化差异显著;农田、自然恢复植被、10和43年生刺槐林地0～20 cm 土层微生物量碳、氮含量四季均值分别为251.94,290.68,150.66,197.34 mg·kg －1和30.95,46.46,36.55,45.27 mg·kg －1。其中：自然恢复植被的微生物量碳、氮含量四季均值最高,其微生物量碳含量分别是农田、10和43年生刺槐林的1.15,1.93和1.47倍,微生物量氮含量分别是它们的1.50,1.27和1.03倍;土壤微生物量碳、氮含量随刺槐树龄增大而升高,43年生刺槐林0～20 cm 土层的微生物量碳、氮含量是10年生刺槐林的1.31和1.24倍。各植被样地不同层次土壤微生物量碳氮比季节差异明显,农田、自然恢复植被、10年和43年生刺槐林 0～20 cm 土层碳氮比四季均值分别为8.64,6.26,4.12 和4.36;10,43年生刺槐林碳氮比分别是农田的0.48和0.50倍,是自然恢复植被的0.66和0.70倍。在 0～20 cm 土层中,农田、自然恢复植被、10和43年生刺槐林地微生物量碳对土壤有机碳平均贡献率分别为1.88%,2.00%,1.54%和1.24%,土壤微生物量氮对土壤全氮的平均贡献率分别为1.21%,5.44%,3.55%和2.26%。【结论】各样地土壤微生物量碳、氮之间显著相关,它们与土壤全氮、有机质和速效钾含量均显著相关;除此之外,土壤微生物量碳还与土壤硝态氮含量显著相关。随着树龄的增加刺槐林土壤微生物量尤其是微生物量氮含量显著提高,因而土壤的生物肥力也显著提高;由土壤微生物量碳、氮含量及其对土壤营养库的贡献率可知,自然恢复植被更利于土壤微生物结构、功能的恢复和生物活性的改善。     

基于KNN方法的大兴安岭地区森林地上碳储量遥感估算

【目的】采用 KNN方法进行碳储量估测,并对估测后的数据进行各种校正处理,绘制森林地上碳储量的空间分布图,为我国森林碳储量和固碳潜力的研究提供基础数据和科学依据。【方法】以黑龙江省大兴安岭为研究区(50°05'—53°33'N,121°11'—127°01'E),基于2010年森林资源连续清查固定样地和同年 Landsat5 TM 影像数据,利用 k－邻近法( KNN)在像素级水平上对森林地上碳储量进行估算。采用多准则方法分东、南、北和中4个区域对样地坐标和其对应的影像光谱值进行坐标重配准,并根据实测样地数据对坐标重配置前后不同林分类型地上碳储量估测精度进行评价;针对 KNN方法像素级估测结果存在明显的高值区域低估和低值区域高估现象,应用直方图匹配方法对估测结果进行变动范围调整;并根据样地实测碳储量和 KNN 估测值间的回归关系对调整后的结果分区域进行进一步匹配校正后处理,绘制森林碳储量的空间分布图。【结果】总体来说,本研究区域像元尺度KNN估测的欧式距离优于马氏距离,均方根误差随着最邻近值 k的增大而降低,当 k大于6时变化缓慢,并逐渐趋于稳定;坐标误差校正后,各林分类型森林地上碳储量的估测精度均显著提高,平均均方根误差由17.23降低到14.3 t·hm －2;直方图匹配后,各区域样地点高值区域低估和低值区域高估现象均有很大程度改善,实测值和估测值间的相关关系明显增强,然而高值地区(碳储量大于20 t·hm －2)出现过高估计现象;经匹配校正后处理的均值、标准差、直方图和累积频率分布图更接近样地实测值,均方根误差也明显降低,高值地区过高估计现象得到很好校正。【结论】森林资源清查数据、遥感数据及 KNN方法相结合逐渐成为区域尺度森林参数空间连续估测的重要手段。同利用光谱值和森林参数建立的回归模型相比,KNN方法能够更多地考虑到森林参数同光谱值之间的非线性依赖关系;但 KNN估测方法除了受距离度量标准、最邻近值 k的大小以及影像波段的选取等因素影响外,还存在如样地坐标和对应的影像光谱值匹配误差、像素级估测结果多呈明显集中分布趋势等问题,使得该方法的应用受到一定限制。本文的研究表明,对这些因素进行合理的校正,将更有利于区域尺度森林参数的精确估计和反演。     

基于改进端元提纯模型的MODIS森林类型识别研究

MODIS遥感数据具有很高的光谱辐射精度,以及成本低、覆盖面积广、获取容易、周期短等数据特征,可以实现全覆盖大尺度区域森林类型信息快速提取,但由于其空间分辨率较低,遥感数据中存在混合像元。利用混合像元分解模型进行分解可得到较好的分类结果,但混合像元分解的端元组分直接影响分类的精度。利用决策树分类模型改进端元提纯,分析各地物的MODIS时间序列植被指数变化规律及物候变化规律,利用决策树模型分类的结果进行端元组分的提纯,最后进行混合像元分解。研究结果表明:分类精度最高的是线性混合像元分解,其次是最大似然分类,最差的是非线性混合像元分解,其中带约束和不带约束的线性分解模型的精度相差不大。     

论继续推进沿海防护林体系工程建设的必要性

全国沿海防护林体系二期工程建设规划将于2015年完成,通过二期规划建设,工程取得了巨大成就,但依然存在较大增长空间和发展潜力,为了贯彻落实生态文明建设总体要求,进一步推动沿海防护林持续快速发展,充分发挥其生态、经济和社会效益,从八个方面对继续推进沿海防护林体系工程建设的必要性进行了论述,以期引起各级政府部门的高度重视和全社会关注,并尽早出台沿海防护林体系工程后期有关建设规划。     

生态景观林带在城乡宜居建设中的作用

面对伴随着城市现代化进程所带来的环境问题,宜居城乡建设是改善居住环境问题的重要举措;生态景观林带是以改善破碎化的森林斑块和绿化带、以增强森林为主体的自然生态空间的连通性、以观赏性为目的和以点、线、面相结合的景观廊道网络。生态景观林带在城乡宜居建设中发挥着改善自然环境与人文环境的双重作用,促进了城市与乡村的耦合,是城乡宜居建设的有效途径。     

长沙黑麋峰国家森林公园现状分析与发展对策探讨

通过系统地分析与评价黑麋峰近郊型国家森林公园的旅游资源、生态环境质量与开发利用条件,重点从功能分区、发展定位、景观品质提升、形象品牌塑造等方面提出了建设与发展对策,以期为我国城市近郊型森林公园的建设与发展提供借鉴。