Multi-sectoral Participatory Urban Forestry Development in Philippines Metropolitan Manila

The Luntiang Kamaynilaan Project (Metro ManilaGreening Project) launched in 1988 planted trees inmajor thoroughfares, center islands, school premisesand other idle public lands, was basically a governmenteffort. When the funds ran out, the project also fizzledout. In both projects however, it is evident that the keyfactor is peoples participation.Gaining lessons from the past two projects, thegovernment established a collaborative effort ofgovernment and non-government organizations. TheCl…     

不同粘度矿物油助剂对除草剂活性的影响

室内及温室内测定了10种不同粘度矿物油助剂对除草剂防除苘麻和稗草药效的影响及对玉米苗期的安全性。结果表明,10种矿物油助剂均不同程度地增加了氰草津和烟嘧磺隆防除两种杂草的活性。其中粘度为46 mm2/s (40℃)的矿物油乳剂(MOC46)对供试除草剂药效的增强作用最为明显,其次为粘度32 mm2/s (40℃)的矿物油乳剂。10种助剂对氰草津药效的增强作用大于对烟嘧磺隆。MOC46对除草剂活性的增加由高到低依次为:莠去津、氰草津＞莠去津+氰草津、莠去津+烟嘧磺隆、氰草津+烟嘧磺隆＞烟嘧磺隆;对玉米苗期安全性依次为:莠去津、烟嘧磺隆、莠去津+烟嘧磺隆＞莠去津+氰草津、氰草津+烟嘧磺隆＞氰草津。氰草津与MOC46混用对玉米苗期药害较重。     

Pest Management in Traditional Tropical Agroecosystems: Lessons for Pest Prevention Research and Extension

Based on current agroecological theory and IPM practices, this review explores the role of traditional practices, involving site selection, soil management, timing of planting and harvesting, crop resistance, intercropping, weed management, harvest residue management, post-harvest management, natural enemies management, mechanical control, repellents and traps in the natural regulation of potential pests. In synthesis, the literature suggests that although pest management professionals focus their efforts on pest control, the preventative approach taken by traditional farmers is more effective. Potential constraints to the implementation of this preventive pest management approach include:(1) lack of integration of ecological theory and pest management, (2) lack of cooperation among social and biological scientists, and (3) lack of real efforts to work with farmers as equals and support mechanisms that protect their knowledge. This revised version was published online in July 2006 with corrections to the Cover Date.     

Feed preference and growth response of juvenile Litopenaeus vannamei to supplementation of marine chemoattractants in a fishmeal‐challenged diet

This study compared the feed preference and growth response of Litopenaeus vannamei to chemoattractants. A diet with 3% fishmeal was supplemented with either 3% salmon meal (POS), 3% soy protein concentrate (NEG), 3% krill meal (KRM), 3% squid meal (SQM), 3% shrimp head meal (SHM), 3% shrimp meal (SM), 3% squid liver meal (SLM), or 5% liquid sardine hydrolysate (SAH). Shrimp with a body weight (BW) of 0.99 ± 0.08 g were stocked at 100 animals/m² in 56 tanks of 1 m³ and fed 10 times daily for 74 days. Feed preference was evaluated by feeding shrimp of 10.87 ± 1.82 g in excess twice a day for 10 days in two separate feeding trays allocated in 50 tanks of 0.5 m³. Survival reached 93.3 ± 5.80% and was unaffected by supplementation. Final BW was the highest for shrimp fed the KRM‐supplemented diet (11.97 ± 0.93 g), followed by POS (11.11 ± 0.77 g) and SQM (11.01 ± 1.17 g). Diets SHM, SM, SLM, and NEG showed a lower shrimp BW than POS, but were not statistically different among them. Shrimp fed the SAH diet achieved the lowest BW (10.06 ± 1.02 g). The highest gained yield was obtained with diets KRM and POS. No statistical difference was observed in shrimp yield among other diets. The lowest feed conversion ratio (FCR) was achieved with shrimp fed KRM (1.31 ± 0.05) when compared to diets SHM (1.47 ± 0.05), SAH (1.47 ± 0.07), and SLM (1.45 ± 0.17). Two‐by‐two comparisons indicated that shrimp preferred SHM and KRM, except when these were compared to SQM and SLM. No difference in feed preference was found between diets with SQM and SLM. SAH was the least preferred raw material in all comparisons. Results indicated that KRM acts as a powerful feeding effector and growth enhancer in fishmeal‐challenged diets for whiteleg shrimp. A dietary supplementation with 3% KRM is more effective than the same dose of any other chemoattractant evaluated.     

Turbidity‐induced changes in emergent effects of multiple predators with different foraging strategies

Abstract – In natural systems, prey frequently interact with multiple predators and the outcome often cannot be predicted by summing the effects of individual predator species. Multiple predator interactions can create emergent effects for prey, but how those change across environmental gradients is poorly understood. Turbidity is an environmental factor in aquatic systems that may influence multiple predator effects on prey. Interactions between a cruising predator (largemouth bass Micropterus salmoides) and an ambush predator (muskellunge Esox masquinongy) and their combination foraging on a shared prey (bluegill Lepomis macrochirus) were examined across a turbidity gradient. Turbidity modified multiple predator effects on prey. In clear water, combined predators consumed in total more prey than expected from individual predator treatments, suggesting risk enhancement for prey. In moderately turbid water, the predators consumed fewer prey together than expected, suggesting a risk reduction for prey. At high turbidity, there were no apparent emergent effects; however, the cruising predator consumed more prey than the ambush predator, suggesting an advantage for this predator. Understanding multiple predator traits across a gradient of turbidity increases our understanding of how complex natural systems function.     

采用组合增强的YOLOX-ViT协同识别温室内番茄花果

番茄花果的协同识别是温室生产管理调控的重要决策依据,针对温室番茄栽培密度大,植株遮挡、重叠等因素导致的现有识别算法精度不足问题,该研究提出一种基于级联深度学习的番茄花果协同识别方法,引入图像组合增强与前端ViT分类网络,以提高模型对于小目标与密集图像检测性能。同时,通过先分类识别、再进行目标检测的级联网络,解决了传统检测模型因为图像压缩而导致的小目标模糊、有效信息丢失问题。最后,引入了包括大果和串果在内的不同类型番茄品种数据集,验证了该方法的可行性与有效性。经测试,研究提出的目标检测模型的平均识别率均值（mean average precision,m AP）为92.30%,检测速度为28.46帧/s,其中对小花、成熟番茄和未成熟番茄识别平均准确率分别为87.92%、92.35%和96.62%。通过消融试验表明,与YOLOX、组合增强YOLOX相比,改进后的模型m AP提高了2.38～6.11个百分点,相比于现有YOLOV3、YOLOV4、YOLOV5主流检测模型,m AP提高了16.56～23.30个百分点。可视化结果表明,改进模型实现了对小目标的零漏检和对密集对象的无误检,从而达到...     

基于MSRCR-YOLOv4-tiny的田间玉米杂草检测模型

为实现田间环境下对玉米苗和杂草的高精度实时检测,本文提出一种融合带色彩恢复的多尺度视网膜(Multi-scale retinex with color restoration, MSRCR)增强算法的改进YOLOv4-tiny模型。首先,针对田间环境的图像特点采用MSRCR算法进行图像特征增强预处理,提高图像的对比度和细节质量;然后使用Mosaic在线数据增强方式,丰富目标检测背景,提高训练效率和小目标的检测精度;最后对YOLOv4-tiny模型使用K-means++聚类算法进行先验框聚类分析和通道剪枝处理。改进和简化后的模型总参数量降低了45.3%,模型占用内存减少了45.8%,平均精度均值(Mean average precision, mAP)提高了2.5个百分点,在Jetson Nano嵌入式平台上平均检测帧耗时减少了22.4%。本文提出的Prune-YOLOv4-tiny模型与Faster RCNN、YOLOv3-tiny、YOLOv4 3种常用的目标检测模型进行比较,结果表明：Prune-YOLOv4-tiny的mAP为96.6%,分别比Faster RCNN和YOLOv3...