Data in Brief最新文献_第2页

Image dataset: Optimizing growth of nonembryogenic citrus tissue cultures using response surface methodology 图像数据集：利用响应面方法优化非胚胎柑橘组织培养物的生长

IF 1 Q3 MULTIDISCIPLINARY SCIENCES

Data in Brief

Pub Date : 2024-10-30 DOI: 10.1016/j.dib.2024.111091

Randall P. Niedz, Eldridge T. Wynn

The data are images of Valencia sweet orange nonembryogenic tissue grown on different culture media that varied in the composition of the mineral nutrients from three experiments. Experiment 1 was a 5-factor d-optimal response surface design of five groupings of the component salts that make up Murashige and Skoog (MS) basal salt medium. Experiment 2 was a 3-factor d-optimal response surface design of extended ranges of factors 1, 2, and 3 from Experiment 1. Experiment 3 was thirteen formulations that were predicted using the prediction model generated from the 5-factor RSM from Experiment 1. The predictions were for two types of growth. One, points were predicted where growth was equal to MS medium (the standard), and two, points predicted with growth greater than MS medium by a minimum of 25%. An image representative of each formulation in each of the experiments makes up the dataset. The data will be useful for 1) visualizing the effects of the diverse mineral nutrient compositions, effects that may not be fully captured with single measure metrics; 2) development of image analysis applications via computer vision and segmentation algorithms for additional insight or for more rapid and possibly accurate assessment of tissue growth and quality; and 3) as an educational resource to learn how to use multifactor experimental designs to assess in vitro growth.

这些数据是巴伦西亚甜橙非胚胎组织在不同培养基上生长的图像，这些培养基的矿物质营养成分在三次实验中各不相同。实验 1 是对组成 Murashige 和 Skoog（MS）基础盐培养基的五组盐进行 5 因子 d 最佳响应面设计。实验 2 是对实验 1 中因子 1、2 和 3 的扩展范围进行的 3 因子 d 最佳响应面设计。实验 3 是利用实验 1 的 5 因子 RSM 生成的预测模型预测出的 13 种配方。预测结果有两种类型。第一种是预测生长量等于 MS 培养基（标准）的点，第二种是预测生长量至少比 MS 培养基高 25% 的点。每个实验中每种配方的代表图像构成了数据集。这些数据将有助于：1）直观显示不同矿物质营养成分的影响，单一测量指标可能无法完全捕捉这些影响；2）通过计算机视觉和分割算法开发图像分析应用程序，以获得更多洞察力，或更快速、更准确地评估组织生长和质量；3）作为教育资源，学习如何使用多因素实验设计来评估体外生长。

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引用次数: 0

Whole genome sequence data of Erwinia amilovora strain E22, from Kazakhstan 来自哈萨克斯坦的 Erwinia amilovora 菌株 E22 的全基因组序列数据

IF 1 Q3 MULTIDISCIPLINARY SCIENCES

Data in Brief

Pub Date : 2024-10-28 DOI: 10.1016/j.dib.2024.111090

Amankeldi Sadanov, Elvira Ismailova, Madina Alexyuk, Olga Shemshura, Gul Baimakhanova, Baiken Baimakhanova, Zere Turlybaeva, Assel Molzhigitova, Akmeiir Yelubayeva, Diana Tleubekova, Andrey Bogoyavlenskiy

Erwinia amilovora is the causative agent of bacterial blight of rosaceae plants. The disease affects ornamental species of this family and fruit trees of great economic importance, such as apple and pear. In the presented research, sequencing of the Erwinia amilovora strain E22 isolated in Kazakhstan, was performed on the Illumina MiSeq platform, followed by bioinformatics processing and gene annotation using SPAdes, RAST, antiSMASH and CARD programs and databases. The size of the assembled genome is 3,799,623 bp. Annotation of the Erwinia amilovora genome assembly identified 3462 genes, including 3251 protein-coding genes and 117 RNA genes. This genome will be helpful to further understand the evolution of Erwinia amilovora and can be useful for obtaining control agents.

Erwinia amilovora 是玫瑰科植物细菌性枯萎病的病原体。这种病会影响该科的观赏植物和具有重要经济价值的果树，如苹果和梨。本研究在 Illumina MiSeq 平台上对在哈萨克斯坦分离到的 Erwinia amilovora 菌株 E22 进行了测序，随后使用 SPAdes、RAST、antiSMASH 和 CARD 程序和数据库进行了生物信息学处理和基因注释。组装的基因组大小为 3,799,623 bp。对 Erwinia amilovora 基因组的注释确定了 3462 个基因，包括 3251 个蛋白编码基因和 117 个 RNA 基因。该基因组将有助于进一步了解 Erwinia amilovora 的进化过程，并有助于获得防治药剂。

引用次数: 0

A novel dataset of annotated oyster mushroom images with environmental context for machine learning applications 用于机器学习应用的带有环境背景的杏鲍菇图像注释新数据集

IF 1 Q3 MULTIDISCIPLINARY SCIENCES

Data in Brief

Pub Date : 2024-10-28 DOI: 10.1016/j.dib.2024.111074

Sonay Duman , Abdullah Elewi , Abdulsalam Hajhamed , Rasheed Khankan , Amina Souag , Asma Ahmed

State-of-the-art technologies such as computer vision and machine learning, are revolutionizing the smart mushroom industry by addressing diverse challenges in yield prediction, growth analysis, mushroom classification, disease and deformation detection, and digital twinning. However, mushrooms have long presented a challenge to automated systems due to their varied sizes, shapes, and surface characteristics, limiting the effectiveness of technologies aimed at mushroom classification and growth analysis. Clean and well-labelled datasets are therefore a cornerstone for developing efficient machine-learning models. Bridging this gap in oyster mushroom cultivation, we present a novel dataset comprising 555 high-quality camera raw images, from which approximately 16.000 manually annotated images were extracted. These images capture mushrooms in various shapes, maturity stages, and conditions, photographed in a greenhouse using two cameras for comprehensive coverage. Alongside the images, we recorded key environmental parameters within the mushroom greenhouse, such as temperature, relative humidity, moisture, and air quality, for a holistic analysis. This dataset is unique in providing both visual and environmental time-point data, organized into four storage folders: “Raw Images”; “Mushroom Labelled Images and Annotation Files”; “Maturity Labelled Images and Annotation Files”; and “Sensor Data”, which includes time-stamped sensor readings in Excel files. This dataset can enable researchers to develop high-quality prediction and classification machine learning models for the intelligent cultivation of oyster mushrooms. Beyond mushroom cultivation, this dataset also has the potential to be utilized in the fields of computer vision, artificial intelligence, robotics, precision agriculture, and fungal studies in general.

计算机视觉和机器学习等先进技术正在彻底改变智能蘑菇行业，解决产量预测、生长分析、蘑菇分类、病害和变形检测以及数字孪生等方面的各种难题。然而，由于蘑菇的大小、形状和表面特征各不相同，长期以来一直是自动化系统面临的难题，限制了蘑菇分类和生长分析技术的有效性。因此，干净且标签齐全的数据集是开发高效机器学习模型的基石。为了弥补杏鲍菇栽培领域的这一差距，我们提出了一个由 555 张高质量相机原始图像组成的新型数据集，并从中提取了约 16000 张人工标注的图像。这些图像捕捉了不同形状、成熟阶段和条件下的蘑菇，在温室中使用两台相机进行拍摄，以实现全面覆盖。除了图像，我们还记录了蘑菇温室内的关键环境参数，如温度、相对湿度、湿度和空气质量，以便进行整体分析。该数据集独一无二，同时提供视觉和环境时间点数据，并分为四个存储文件夹："原始图像"、"蘑菇标签图像和注释文件"、"成熟度标签图像和注释文件 "以及 "传感器数据"，其中包括 Excel 文件中带有时间戳的传感器读数。该数据集可帮助研究人员为杏鲍菇的智能栽培开发高质量的预测和分类机器学习模型。除蘑菇栽培外，该数据集还有可能用于计算机视觉、人工智能、机器人、精准农业和真菌研究等领域。

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引用次数: 0

A fish fry dataset for stocking density control and health assessment based on computer vision 基于计算机视觉的鱼苗数据集，用于放养密度控制和健康评估

IF 1 Q3 MULTIDISCIPLINARY SCIENCES

Data in Brief

Pub Date : 2024-10-28 DOI: 10.1016/j.dib.2024.111075

Yuqiang Wu , Huanliang Xu , Bowen Liao , Jia Nie , Chengxi Xu , Ziao Zhang , Zhaoyu Zhai

Fish farming is a promising economic activity that promotes the social development, protects the ecological environment, and enhances the quality of human life. In recent years, various computer vision models have been established for assessing aquaculture density and monitoring fish health. However, existing datasets are generally characterised by larger fish sizes and low density, making them unsuitable for detecting small targets such as fish fry. This paper presents a dataset comprising 1101 images of largemouth bass (Micropterus salmoides) fry, specifically designed for small target detection in dense scenes. Each image contains a variable number of fish fries, ranging from 20 to 80 individuals. To facilitate health assessment in the aquaculture, a small number of dead fish fries are included in each image. The entire dataset is annotated with a total of 51,119 live fish fry and 3586 dead ones. Additionally, among the 80 images depicting high-density scenarios, there are complex situations such as overlap, occlusion, and adhesion, which pose challenges to the small target detection task. The dataset is annotated using the Labelimg tool and converted to the COCO format. It can be applied to a variety of scenarios, including seedling rearing, fry retailing, and survival assessments. It is also valuable for biomass estimation and aquaculture density control applications. In summary, this dataset provides an invaluable resource for the research community, advancing studies on fry counting and fish population health, thus contributing to the development of intelligent aquaculture.

养鱼业是一项前景广阔的经济活动，它促进了社会发展，保护了生态环境，提高了人类生活质量。近年来，人们建立了各种计算机视觉模型，用于评估水产养殖密度和监测鱼类健康状况。然而，现有的数据集一般都具有鱼体大、密度低的特点，因此不适合检测鱼苗等小目标。本文介绍了一个由 1101 幅大口鲈鱼（Micropterus salmoides）鱼苗图像组成的数据集，该数据集是专为在密集场景中检测小目标而设计的。每张图像包含数量不等的鱼苗，从 20 到 80 条不等。为了便于对水产养殖的健康状况进行评估，每张图像中都包含了少量死亡的鱼苗。整个数据集共标注了 51119 条活鱼苗和 3586 条死鱼苗。此外，在描绘高密度场景的 80 幅图像中，存在重叠、遮挡和粘连等复杂情况，这给小目标检测任务带来了挑战。该数据集使用 Labelimg 工具进行注释，并转换为 COCO 格式。它可应用于多种场景，包括育苗、鱼苗零售和存活率评估。它对于生物量估算和水产养殖密度控制应用也很有价值。总之，该数据集为研究界提供了宝贵的资源，推动了鱼苗计数和鱼群健康方面的研究，从而促进了智能水产养殖的发展。

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引用次数: 0

Dataset of shallow sub-surface soil moisture and soil temperature at various distances from downed trees and logs in a Pinus nigra forest after wildfire in Central Italy 意大利中部野火后黑松林中距离倒伏树木和原木不同距离的浅层次表层土壤水分和土壤温度数据集

IF 1 Q3 MULTIDISCIPLINARY SCIENCES

Data in Brief

Pub Date : 2024-10-28 DOI: 10.1016/j.dib.2024.111080

Flavio Taccaliti , Alessandro Vitali , Carlo Urbinati , Raffaella Marzano , Emanuele Lingua

In a conifer forest in Central Italy burnt by wildfire in 2017, shallow sub-surface (topmost 5 cm) soil temperature and soil moisture (% volumetric water content) were measured during summer 2022. Various distances from downed trees (natural barriers) and log erosion barriers (artificial barriers) were sampled. Additional data on the hour of sampling, barriers characteristics, and barriers location were collected.

2022 年夏季，在意大利中部一片于 2017 年被野火烧毁的针叶林中，测量了浅表层下（最上面 5 厘米）土壤温度和土壤湿度（体积含水量百分比）。在距离倒伏树木（天然屏障）和原木侵蚀屏障（人工屏障）的不同距离进行了采样。还收集了关于取样时间、屏障特征和屏障位置的其他数据。

引用次数: 0

Dataset on field estimation of vegetation cover loss due to charcoal production in Afram Plains of Ghana 加纳阿夫拉姆平原木炭生产造成植被损失的实地估算数据集

IF 1 Q3 MULTIDISCIPLINARY SCIENCES

Data in Brief

Pub Date : 2024-10-26 DOI: 10.1016/j.dib.2024.111022

Thelma Arko

The impact of urban charcoal consumption on tree cover loss in Ghana remains understudied, with limited data and inconsistent methodologies hindering a comprehensive understanding. This data article addresses these gaps by presenting a valuable dataset on charcoal production and its environmental implications in the Afram Plains of Ghana. A systematic data collection process was undertaken, encompassing 29 charcoal production sites across four communities: Tease, Odumasua, Anlo Fasso, and Forifori. Semi-structured interviews with community elders, chiefs, and charcoal producers provided insights into the historical context and local knowledge of charcoal production activities.

The dataset includes a wealth of information, such as land use characteristics, the number of trees utilized for charcoal production, and measurements of tree stump diameters, lengths, and volumes. Local names and scientific identification of tree species were recorded, offering a detailed understanding of the vegetation impacted by charcoal production.

The potential for reuse of this dataset is significant. Researchers can utilize the information to further explore the complex dynamics between charcoal production and tree cover loss develop evidence-based policies, and promote sustainable alternatives. By making this dataset publicly available, we encourage its reuse to support interdisciplinary research, enhance understanding of charcoal production's environmental footprint, and inform decision-making processes aimed at preserving Ghanaʼs valuable vegetation cover.

城市木炭消费对加纳树木植被损失的影响仍未得到充分研究，有限的数据和不一致的方法阻碍了对这一问题的全面了解。这篇数据文章介绍了加纳阿夫拉姆平原木炭生产及其环境影响的宝贵数据集，填补了这些空白。我们开展了系统的数据收集工作，涉及四个社区的 29 个木炭生产点：这四个社区分别是 Tease、Odumasua、Anlo Fasso 和 Forifori。对社区长老、酋长和木炭生产者进行的半结构式访谈有助于深入了解木炭生产活动的历史背景和当地知识。数据集包含大量信息，如土地使用特征、用于木炭生产的树木数量以及树桩直径、长度和体积的测量值。记录了树种的当地名称和科学鉴定，让人们详细了解木炭生产对植被的影响。研究人员可以利用这些信息进一步探索木炭生产与树木覆盖损失之间的复杂动态关系，制定有据可依的政策，推广可持续的替代品。通过公开该数据集，我们鼓励对其进行再利用，以支持跨学科研究，加深对木炭生产的环境足迹的了解，并为旨在保护加纳宝贵的植被的决策过程提供信息。

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引用次数: 0

Hyperspectral data of understory elements in boreal forests: In situ and laboratory measurements 北方森林林下要素的高光谱数据：现场和实验室测量

IF 1 Q3 MULTIDISCIPLINARY SCIENCES

Data in Brief

Pub Date : 2024-10-24 DOI: 10.1016/j.dib.2024.111068

Audrey Mercier, Susanna Karlqvist, Aarne Hovi, Miina Rautiainen

Enhancing our understanding of the spectral properties of forest elements is essential for interpreting airborne and satellite-borne remote sensing data. This article presents two datasets on the spectral properties of understory elements in boreal forests collected with close-range hyperspectral measurements. We conducted two field campaigns in June and July 2023 in Finland to acquire spectral measurements at wavelengths from 350 to 2500 nm using an ASD FieldSpec 4 spectrometer for forest understory elements. We measured ferns, decaying wood, common wood sorrel and May lily in situ. In a laboratory, we measured leaves from European fly honeysuckle, alder buckthorn and common hazel. These data support the analysis of vegetation characteristics, training of classification algorithms and improvement of forest radiative transfer models, and could be used to evaluate the potential of hyperspectral data to discriminate the understory elements of boreal forest.

加强对森林要素光谱特性的了解对于解释机载和卫星遥感数据至关重要。本文介绍了通过近距离高光谱测量收集到的两组有关北方森林林下成分光谱特性的数据集。我们于 2023 年 6 月和 7 月在芬兰进行了两次野外活动，使用 ASD FieldSpec 4 光谱仪采集波长为 350 到 2500 nm 的光谱，用于测量林下要素。我们在现场测量了蕨类植物、腐朽木材、普通木荷和五月百合。在实验室中，我们测量了欧洲飞燕草、赤杨和普通榛树的叶子。这些数据有助于分析植被特征、训练分类算法和改进森林辐射传递模型，并可用于评估高光谱数据在区分北方森林林下要素方面的潜力。

引用次数: 0

Dataset of dendrometer and environmental parameter measurements of two different species of the group of genera known as eucalypts in South Africa and Portugal 南非和葡萄牙两种不同桉树属树种的树枝测量仪和环境参数测量数据集

IF 1 Q3 MULTIDISCIPLINARY SCIENCES

Data in Brief

Pub Date : 2024-10-24 DOI: 10.1016/j.dib.2024.111035

Christopher Stefan Erasmus , Marthinus Johannes Booysen , David Drew

Eucalyptus plantations are a crucial global resource, offering raw materials for industries across five continents, including renewable energy sources, recyclable fibers, and eco-friendly wood products. To support sustainable management, ten wireless dendrometer and environmental sensor systems were deployed on Eucalyptus trees—six in Stellenbosch, South Africa, and four in Leiria, Portugal. These systems measure tree stem growth, air and soil conditions, and transmit data via LoRaWAN to a cloud-based platform (ThingSpeak), with local SD-card backups. Nine systems collect data at 6-minute intervals, while one collects at 11-minute intervals. This data is valuable for maintaining forest health and ensuring resource sustainability. EucXylo, a Research Chair funded by the Hans Merensky Legacy Foundation, focuses on the ecophysiology, growth, and wood formation in eucalypts. The dataset aids in developing models of tree growth and xylem production, offering high-resolution insights into Eucalyptus growth and environmental conditions.

桉树种植园是重要的全球资源，为五大洲的工业提供原材料，包括可再生能源、可回收纤维和环保木制品。为了支持可持续管理，我们在桉树上部署了十套无线树干测量仪和环境传感器系统，其中六套位于南非斯泰伦博斯，四套位于葡萄牙莱里亚。这些系统测量树干生长情况、空气和土壤条件，并通过 LoRaWAN 将数据传输到云平台（ThingSpeak），同时进行本地 SD 卡备份。九套系统以 6 分钟的间隔收集数据，一套系统以 11 分钟的间隔收集数据。这些数据对于维护森林健康和确保资源可持续性非常有价值。EucXylo 是由汉斯-梅伦斯基遗产基金会资助的研究教席，主要研究桉树的生态生理学、生长和木材形成。该数据集有助于开发树木生长和木质部生产模型，提供有关桉树生长和环境条件的高分辨率见解。

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引用次数: 0

Drivers of soil health across European Union – Data from the literature review 欧盟各国土壤健康的驱动因素--来自文献综述的数据

IF 1 Q3 MULTIDISCIPLINARY SCIENCES

Data in Brief

Pub Date : 2024-10-24 DOI: 10.1016/j.dib.2024.111064

Shaswati Chowdhury , Maria von Post , Roger Roca Vallejo , Karen Naciph Mora , Jenni Hultman , Taina Pennanen , Antti-Jussi Lindroos , Katharina Helming

Soil health in Europe has reached a critical point: it is estimated that 60-70% of European soils are unhealthy. Changes in land use, its intensity and the quality of management have significant impacts on soil health and soil related ecosystem services. A systems analysis of soil health dynamics requires an understanding of the drivers inducing changes in land use and management. The DPSIR framework was adapted to the context of soil health in the European Union (EU) and used as an analytical framework for identifying the drivers for soil health. A scoping literature review, divided in four parts based on different land use types (urban and industrial, agriculture, forest, and nature), was conducted using the PRISMA protocol. The identified drivers across all land uses have been adjusted and standardised in in-person and online workshops. This metadata set presents the typology of drivers sorted according to the EU soil mission's soil health objectives, land use type, and location. The literature review was conducted as part of SOLO (Soils for Europe), a EU´s Horizon Europe funded project and the dataset will support the co creation and knowledge developing platforms (think tanks) for each EU soil mission objectives.

欧洲的土壤健康已经到了一个临界点：据估计，60-70% 的欧洲土壤是不健康的。土地使用、使用强度和管理质量的变化对土壤健康和与土壤相关的生态系统服务有着重大影响。要对土壤健康动态进行系统分析，就必须了解引起土地使用和管理变化的驱动因素。根据欧盟（EU）的土壤健康状况，对 DPSIR 框架进行了调整，并将其用作确定土壤健康驱动因素的分析框架。根据不同的土地利用类型（城市和工业、农业、森林和自然），采用 PRISMA 协议进行了范围界定文献综述，分为四个部分。在现场和在线研讨会上，对所有土地用途中已确定的驱动因素进行了调整和标准化。该元数据集展示了根据欧盟土壤任务的土壤健康目标、土地利用类型和地点分类的驱动因素类型。文献综述是欧盟资助的地平线欧洲项目 SOLO（欧洲土壤）的一部分，该数据集将为欧盟土壤任务目标的共同创建和知识开发平台（智库）提供支持。

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引用次数: 0

A dataset of µCT images of small samples of constructed Technosol from bioretention cells 从生物滞留池中提取的小样本技术溶胶的 µCT 图像数据集

IF 1 Q3 MULTIDISCIPLINARY SCIENCES

Data in Brief

Pub Date : 2024-10-24 DOI: 10.1016/j.dib.2024.111066

Petra Marešová , John Koestel , Aleš Klement , Radka Kodešová , Michal Sněhota

The dataset represents micro computed tomography (µCT) images of undisturbed samples of constructed Technosol, obtained by sampling from the top layer of the biofilter in two bioretention cells. A bioretention cell is a stormwater management system designed to collect and temporarily retain stormwater runoff and treat it by filtering it through a soil media called a biofilter. Soil samples were collected at 7, 12, 18, 23, and 31 months after the establishment of bioretention cells. The constructed Technosol was composed of 50% sand, 30% compost, and 20% topsoil. The bioretention cell 1 (BC1) was designed to collect water from the nearby building roof, and bioretention cell 2 (BC2) was without regular inflow for possible irrigation events. This allowed for the capture of the dynamics of early soil structure development. The dataset comprises a total of 120 three-dimensional µCT images. The 16-bit µCT images obtained by industrial scanner have resolutions of 12 and 20 µm. The characteristics of total porosity, volumetric weight of the dry sample and field capacity were determined in the laboratory for each sample. The generated dataset captures the soil structure development within the biofilter during the initial years of operation of bioretention cells with two distinct water regimes. Originally produced to describe the development of the macropore system during early biofilter evolution, this extensive and high-quality dataset can be reused for further studies on constructed Technosol evolution, focusing on soil structure or hydraulic properties. It is particularly beneficial for research into macropore network development and changes in hydraulic properties in constructed soils. The dataset can support model validation and improve understanding of soil property variability in bioretention systems. It serves as a valuable resource for researchers who lack the means to collect and scan their own samples.

该数据集代表了从两个生物滞留池中的生物滤池顶层取样获得的未受干扰的已建 Technosol 样品的微型计算机断层扫描 (µCT) 图像。生物滞留池是一种雨水管理系统，旨在收集和暂时滞留雨水径流，并通过称为生物滤池的土壤介质进行过滤处理。在生物滞留池建成后的 7、12、18、23 和 31 个月收集土壤样本。构建的 Technosol 由 50% 的沙子、30% 的堆肥和 20% 的表土组成。生物滞留池 1（BC1）的设计目的是收集附近建筑物屋顶的水，生物滞留池 2（BC2）则没有为可能发生的灌溉事件提供定期流入水。这样就可以捕捉到早期土壤结构发展的动态变化。数据集共包括 120 幅三维 µCT 图像。工业扫描仪获得的 16 位 µCT 图像分辨率分别为 12 和 20 微米。每个样本的总孔隙率、干样本的体积重量和田间容量等特征都是在实验室测定的。生成的数据集捕捉到了生物滞留池在两种不同水系下运行最初几年中生物滞留池内土壤结构的发展情况。该数据集最初用于描述生物滤池早期演化过程中大孔隙系统的发展情况，其广泛而高质量的数据集可重新用于对构造型技术溶胶演化的进一步研究，重点关注土壤结构或水力特性。它尤其有利于研究构建土壤中大孔隙网络的发展和水力特性的变化。该数据集可支持模型验证，并加深对生物滞留系统中土壤特性变化的理解。对于没有能力自行采集和扫描样本的研究人员来说，它是一个宝贵的资源。

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引用次数: 0