A review and analysis of particle size parameters and their relationships to physical properties of growing media

Stan Durand, William Carl Fonteno, Jean-Charles Michel
{"title":"A review and analysis of particle size parameters and their relationships to physical properties of growing media","authors":"Stan Durand,&nbsp;William Carl Fonteno,&nbsp;Jean-Charles Michel","doi":"10.1002/saj2.20661","DOIUrl":null,"url":null,"abstract":"<p>An expanded description of particle morphology and the analysis of its relationships with physical properties may help to optimize the selection of raw materials and particle size fractions used as growing media constituents. Previous works have described the outlines of these relations based mostly on sieving procedures to characterize particle size distribution. They have shown limited and sometimes contradictory results due to the different methods used, size fractions selected, and physical properties measured. Also, sieve analysis, which separates particles based on their width, is less accurate for non-spherical particles, which is the case for most growing media constituents. Recent works have promoted the use of dynamic image analysis (DIA) to precisely analyze both particle length and width. Five raw materials were chosen (white and black peats, coir, pine bark, and wood fiber) and sieved to obtain various particle size fractions. For each particle size fraction and the raw materials, the mean weight diameter (MWD), derived from sieving, was calculated, whereas mean particle length and width were determined using a DIA tool, the QicPic device. Also, physical properties were assessed from water retention curves established using Hyprop systems. The statement that the larger the particle size, the higher the air-filled porosity (AFP), the lower the water holding capacity (WHC) was more precisely redefined. Large variations in WHC and AFP mainly occurred for finest particle size fractions, whereas changes were conversely very small or non-existent for larger particle sizes. From data obtained for each particle size fractions, regression models were established to relate mean particle length and width (both determined using DIA) and MWD (determined from sieving) with WHC and AFP. Mean particle length was identified as the most relevant parameter for predicting WHC and AFP of the raw materials tested.</p>","PeriodicalId":101043,"journal":{"name":"Proceedings - Soil Science Society of America","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings - Soil Science Society of America","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/saj2.20661","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

An expanded description of particle morphology and the analysis of its relationships with physical properties may help to optimize the selection of raw materials and particle size fractions used as growing media constituents. Previous works have described the outlines of these relations based mostly on sieving procedures to characterize particle size distribution. They have shown limited and sometimes contradictory results due to the different methods used, size fractions selected, and physical properties measured. Also, sieve analysis, which separates particles based on their width, is less accurate for non-spherical particles, which is the case for most growing media constituents. Recent works have promoted the use of dynamic image analysis (DIA) to precisely analyze both particle length and width. Five raw materials were chosen (white and black peats, coir, pine bark, and wood fiber) and sieved to obtain various particle size fractions. For each particle size fraction and the raw materials, the mean weight diameter (MWD), derived from sieving, was calculated, whereas mean particle length and width were determined using a DIA tool, the QicPic device. Also, physical properties were assessed from water retention curves established using Hyprop systems. The statement that the larger the particle size, the higher the air-filled porosity (AFP), the lower the water holding capacity (WHC) was more precisely redefined. Large variations in WHC and AFP mainly occurred for finest particle size fractions, whereas changes were conversely very small or non-existent for larger particle sizes. From data obtained for each particle size fractions, regression models were established to relate mean particle length and width (both determined using DIA) and MWD (determined from sieving) with WHC and AFP. Mean particle length was identified as the most relevant parameter for predicting WHC and AFP of the raw materials tested.

粒度参数及其与生长介质物理性质关系的回顾与分析
扩大对颗粒形态的描述并分析其与物理性质的关系,有助于优化对用作生长介质成分的原料和颗粒大小组分的选择。以前的研究主要基于筛分程序来描述粒度分布,从而描述了这些关系的轮廓。由于使用的方法、选择的粒度组分和测量的物理性质不同,这些研究显示的结果有限,有时甚至相互矛盾。此外,筛分分析是根据颗粒的宽度来分离颗粒的,对于非球形颗粒的准确性较低,而大多数生长介质成分都是非球形颗粒。最近的研究提倡使用动态图像分析(DIA)来精确分析颗粒的长度和宽度。我们选择了五种原料(白泥炭和黑泥炭、椰壳纤维、松树皮和木质纤维),并对其进行筛分,以获得不同粒径的部分。对于每种粒度分馏物和原料,都计算了筛分得出的平均重量直径(MWD),并使用 DIA 工具 QicPic 设备测定了平均粒长和粒宽。此外,还通过使用 Hyprop 系统建立的保水曲线对物理特性进行了评估。粒度越大,充气孔隙率(AFP)越高,持水量(WHC)越低,这一说法得到了更精确的重新定义。持水量和充气孔隙率的巨大变化主要发生在最细的粒度组分上,而相反,粒度较大的组分变化很小或没有变化。根据所获得的各粒度组分的数据,建立了颗粒平均长度和宽度(均用 DIA 测定)以及最大粒径(用筛分法测定)与 WHC 和 AFP 的回归模型。平均粒长被确定为预测所测试原料的 WHC 和 AFP 的最相关参数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信