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Description
wormwood potted plant Silver Lining Wormwood – Plant DetectivesSilver Lining Wormwood (Artemisia x 'Silver Lining') Silver Lining Wormwood is a silver, foliage forward perennial that brightens sunny beds and makes nearby colors look cleaner. Its low, wide mound fills space quickly, helping borders look finished without relying on flowers. Once established, it handles heat and drier conditions well, making it a practical choice for lower water landscapes. If you want a consistent silver layer that stays useful
Silver Lining Wormwood (Artemisia x 'Silver Lining')
Silver Lining Wormwood is a silver, foliage-forward perennial that brightens sunny beds and makes nearby colors look cleaner. Its low, wide mound fills space quickly, helping borders look finished without relying on flowers. Once established, it handles heat and drier conditions well, making it a practical choice for lower-water landscapes. If you want a consistent silver layer that stays useful from spring through fall, this plant delivers.
Distinctive Features
This artemisia forms a dense, mounded groundcover with finely cut, fragrant, silver-gray foliage that reads like a soft blanket across the garden. The plant is grown primarily for its foliage, while any buff-yellow flowers are usually minor and appear on taller stalks in late summer to early fall. It holds its shape well through the season in full sun, especially in lean, well-drained soils. In hot, humid climates the foliage can decline, so siting for airflow and drainage is key.
Growing Conditions
- Sun: Full sun for best color and a tight, dense mound.
- Soil: Well-drained soil is essential, and it performs well in average to poor soils.
- Water: Low to medium moisture, water to establish, then let soil dry between waterings.
- USDA Zones: 4 to 9.
- Mature Size: About 12 to 16 inches tall and 32 to 36 inches wide.
Ideal Uses
- Focal Point: Use a broad drift as a focal point of silver texture that anchors brighter flowers and deeper greens.
- Edging: Line paths and bed fronts for a clean, low border that stays bright through summer.
- Groundcover: Plant in groups to knit into a dense mat that covers soil and reduces weeding.
- Rock Gardens: Tuck into sunny, well-drained pockets where silver foliage can highlight nearby plants.
- Hot, Dry Beds: Pair with drought-tolerant perennials and grasses for a low-input planting with strong contrast.
Low Maintenance Care
- Shearing: Shear lightly in midseason if needed to refresh growth and keep the mound crisp.
- Drainage: Avoid wet soils and heavy winter moisture, since poor drainage can cause decline.
- Watering: Water deeply during establishment, then water only during extended drought.
- Spacing: Provide airflow and avoid overcrowding to help foliage stay clean in humid weather.
- Cleanup: Tidy in early spring by removing winter-worn foliage before new growth starts.
Why Choose Silver Lining Wormwood?
- Bright Silver Foliage: Silver-gray, finely cut leaves add contrast that makes the whole planting look sharper.
- Wide, Tidy Habit: Forms a low, broad mound that fills space and looks intentional all season.
- Drought Tolerance: Performs well in drier conditions once established in well-drained soil.
- Low Flower Maintenance: Foliage stays the focus, with any flowers typically minor and easy to ignore.
- Deer Resistance: Often avoided by deer and rabbits due to aromatic foliage.
If you want a silver plant that works like a design tool, Silver Lining Wormwood is an easy choice. Give it full sun and sharp drainage, then let it spread into a consistent, bright layer that ties the border together. It looks best repeated, creating a continuous silver thread through the garden. With an occasional shear and the right siting, it stays dense, clean, and dependable year after year.
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4.9 ★★★★★
Based on 7 reviews
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Product Reviews
★★★★★ 5
Need to read book
Format: Hardcover
The truth about the Native people.
THANK YOU Kent for writing this book.
We purchased about 12 total.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on November 24, 2019
★★★★★ 5
Native American history at its best!
Format: Hardcover
Kent Blansett's engrossing story about the life & times of the famed Mohawk activist Richard Oakes is Native American history at its best. I appreciated the well-written context provided about the birth, growth and impact of the Red Power Movement and the pivotal role that social justice activism played in the rise of modern Indian nations in the United States today. This scholarly work helps us understand modern Native America and is a "must-read" for every Native American Studies student and scholar, as well as readers interested in important American social justice movements.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on April 1, 2019
★★★★★ 5
Excellent book on ML
Format: Paperback
This is a great book on machine learning. Topics covered are extensive - from beginner level to advanced topics including math behind different algorithms. However, not "all" algorithms are covered. Please go through the table of contents.
The first part - 11 chapters - covers machine learning concepts and second part covers advanced topics with Pytorch. There are lots of excellent code and they work!!
The quality of the book I received is excellent. I have gone through all 742 pages, and it has held up very well!!
I used Jupyter notebook to run all examples. I created a new notebook and copied and pasted the code and ran them. This approach worked very well for me. At the same time, I could experiment with my take on the code snippets and definitely added to my knowledge.
Only issue I have is on the second part of the book discussing PyTorch: (1) Some packages are a bit older version: e.g., transformer 4.9.1 whereas current version is 4.48+. It took some tweaking/recoding to get the examples working. (2) There is not much discussion on why certain architecture was chosen - e.g., number of layers, is there a rule of thumb on how to improve performance by changing these parameters? Even with CUDA the code run for a long time. Therefore, experimenting with different values of parameters become too time consuming. (3) On the same note, if I can achieve test accuracy of 90%+ using logistic regression and almost the same (perhaps one or two percent better with PyTorch with IMDB movie review dataset and that two much faster why should I use PyTorch for this dataset? Obviously, PyTorch is for certain types of problems. Discussions can be included by not adding to the exhaustive (and apt) contents.
Personally I was disappointed by lack of any example on time series.
Must have for ML practitioner as a reference and guide.
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Reviewed in the United States on December 20, 2024
★★★★★ 5
Excellent Textbook for Hands-On Learning of ML
Format: Kindle
This textbook is for the serious life-long learners of machine learning. There are at least two ways to ‘consume’ this book.
For the expert in ML, this is a textbook to study as a clear comprehensive ML overview and then to dive into sections of interest or ignorance. The concepts are grounded in code examples and are well cited (with links) to sources. Further, this textbook is appropriate if you are TensorFlow-centric and want to broaden into cutting-edge ML models/tools coded in PyTorch.
For a new learner to ML, this is a textbook to DO (not just READ) with hands-on and brain-engaged. If you realize that ML is a key life-long skill for your career, consider this textbook as part of a daily learning habit (10-30 min).
From personal experience, my advice to the new learner is as follows… First, clone the GitHub repository, setup your Python environment, and study the textbook, while working through the notebooks. Go on tangents and break the code. Do this methodically as part of your daily learning habit, but do not hesitate to jump ahead several chapters to prepare for tomorrow’s meeting. There is enough excellent material here for a full year of ML adventures.
I did a similar strategy with Raschka’s first textbook. About four years ago, I had finished Andrew Ng’s Deep Learning Specialization as a student in his first cohort. I knew the concepts well but could not do the actual application coding. I was surprised how my Python coding improved by following Raschka’s clean and elegant style. And Raschka’s code examples were meaty enough to be springboards into working applications.
Several textbook editions later, what is different about this new edition?
First, it moves you through scikit-Learn (a firm foundation) to PyTorch, instead of TensorFlow. PyTorch is a better stepping-stone, both conceptually and practically. With PyTorch, you will go further with less energy, while being able to convert your efforts into TensorFlow as needed. In addition, most of the cutting-edge ML/AI/DL research is in PyTorch. It is nice to read a recent arXiv paper, clone their repository, click on the Colab tutorial, and replicate their experiments, along with picking up a ton of new coding tricks & tips. I am excited to work through these PyTorch sections to hone my skills.
Second, there is a clear recognition of model tracking and tuning practices. This is often a gap in other ML textbooks and courses. Once you progress beyond the simple demo examples in a lecture, you realize that the real work is experiments, more experiments, and still more experiments, so that you must understand what the model architecture and hyperparameters are doing to your dataset. There is good coverage of scikit-Learn pipeline, grid search, model performance, and the like.
Third, ML/AI/DL practice is rapidly evolving. Every week new ML packages/services become available that could save much grief on your current project. What is refreshing about Raschka’s textbook series is that he constantly adding cutting-edge topics because he likes to stay current and to help us stay current. Hence, this edition contains recent ML treats as: transformers, self-supervised learning, autoencoders-to-GAN, graph neural networks, DBSCAN, t-SNE (with brief mention of UMAP), and PyTorch-Lightning.
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Reviewed in the United States on February 26, 2022
★★★★★ 4
Just learning it
Format: Paperback
Nice learning book just have to finish it
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on December 10, 2025
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