SKU: 52228503614
lotus indoor plant

lotus indoor plant Pink Sacred Lotus|Most Popular Grow at Home Lotus |Sacred Flower Lotus Tubers For Sale – Pond Megastore

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Description

lotus indoor plant Pink Sacred Lotus|Most Popular Grow at Home Lotus |Sacred Flower Lotus Tubers For Sale – Pond MegastorePink Sacred Lotus Our most popular lotus! The name Sacred Lotus refers to a type of lotus flower, not a particular variety. Sacred Lotus are usually tall pink or pink & white single petal lotus varieties. The lotus flower exudes beauty and grace. The Sacred Lotus is revered in many countries worldwide, often symbolizing the seat of Buddha and many Hindu deities. It is the most important flower in Eastern Cultures and often symbolizes peace, purity,

Pink Sacred Lotus - Our most popular lotus!

The name Sacred Lotus refers to a type of lotus flower, not a particular variety. Sacred Lotus are usually tall pink or pink & white single-petal lotus varieties. The lotus flower exudes beauty and grace. The Sacred Lotus is revered in many countries worldwide, often symbolizing the seat of Buddha and many Hindu deities. It is the most important flower in Eastern Cultures and often symbolizes peace, purity, devotion, and new beginnings. Grows 4 - 5 feet tall when planted in very wide containers

Tall/Pink/Single Petals

Planting Instructions

We may ship the lotus dormant weeks early in spring before you should plant; simply keep the small package in the refrigerator until outdoor temperatures are steadily 75 degrees or better and quite sunny where you will be planting every day. Tubers shipped in March should be fine up until Mid May in the refrigerator. 

Plant your sacred lotus tuber in a wide container (24 - 48 inches wide) using loam soil. Dig a trench in the soil and gently place your sacred lotus tuber in the trench, taking care not to break or damage the tuber. Cover all but the growth tips with an inch or two of soil and gently add a couple of inches of water above the soil. Place your lotus container outdoors where it will receive at least 8 hours of strong sunlight per day Tuber in a wide container (24 - 48  inches wide) using loam soil. Dig a trench in the soil and gently place your Sacred Lotus tuber in the trench, taking care not to break or damage the tuber. Cover all but the growth tips with an inch or two of soil and gently add a couple of inches of water above the soil. Place your lotus container where it will receive at least 8 hours of strong sunlight per day, outdoors.
When placing your lotus under water, we suggested a depth of about 5-7 inches of water above the soil line; however, sometimes the tall lotus do okay in full direct all-day sun in very large containers as much as 12 inches from the top of your soil to the waters surface. Do not plant lotus deep or they will drown. 

DO NOT fertilize until you have aerial leaves growing out of the water. Once you have at least two aerial leaves, you may fertilize your lotus

Fertilizing Instructions

Lotus are very heavy feeders. We recommend Waterlily World Fertilizer Tabs + Humates for optimum growth, best bloom and ease of use. Press the fertilizer tabs into the soil near the roots of your lotus, taking care not to damage the roots. Do this once a month throughout the growing/blooming season (June through August). Your Sacred Lotus should grow and bloom the very first year!

What Is Loam Soil?

Loam soil is a good mixture of Topsoil and Sand

If you are lucky enough to have good topsoil in your backyard, by all means, use your topsoil. All you will have to do is add fertilizer. If you are not so lucky--and your backyard is sand or heavy red or yellow clay, you can mix up a batch of loam soil.

 You can create your loam soil by mixing these two ingredients

 Mix thoroughly with a little water. The soil should clump when squeezed. If the soil is mixed properly, it will not muddy the pond water.


Don't buy brands like Scott's or Miracle-Gro, as they contain too much organic matter that can foul your water. Instead, buy an unbranded bag of topsoil.

You can purchase Pool Filter Sand at any store that sells pool supplies.

Loam soil is well-suited for all aquatic plants (except oxygenators). Oxygenators rarely need to be planted, just anchored in the substrate or in a container filled with sand or 1/8  inch pea gravel.

Sand holds little water but does allow for aeration and drainage.

Some DO's and DON'TS regarding Aquatic Planting Soil  

DO NOT use potting soils ( as they are too light and will float right out of the pot). Potting Soil has organic material that will rot and foul your water!

DO NOT add too much-composted material (as it is too rich in organic matter, and it will ferment underwater and destroy the ecology of your pond).

DO NOT use 100% calcined clay as there is no nutritional value in calcined clay.

DO NOT add rocks, stones or pebbles to the top of your planting container as this will inhibit the growth of your plants. Plants do not grow in rocks and stones in nature!

DO NOT purchase API Aquatic Planting Media or Microbe-lift Aquatic Planting Media as these products are NOT suitable for waterlilies, lotus or most other pond plants. They are suitable for submerged grasses ONLY!

We offer PondGro Aquatic Planting soil if you live in an area of the USA without proper topsoil.

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Carol
Belleville, US
★★★★★ 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.
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Reviewed in the United States on November 24, 2019
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Walter Echo-Hawk, author of THE SEA OF GRASS.
Cuba, US
★★★★★ 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.
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Reviewed in the United States on April 1, 2019
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Par
Waukegan, US
★★★★★ 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
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Richard Hackathorn
Pawtucket, US
★★★★★ 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
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Verified Purchase
Amazon Customer
Fort Morgan, US
★★★★★ 4
Just learning it
Format: Paperback
Nice learning book just have to finish it
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Reviewed in the United States on December 10, 2025

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