SKU: 19432880194
aglaonema key lime

aglaonema key lime Aglaonema 'Arctic Lime'

Sale price$19.51 Regular price$21.68
Save 10%

Pay in installments of $5.42 with ShopPay, AfterPay and Klarna

Shipping Estimate
USA
  • USA
  • CAN

Ships within 48 hours · Estimated delivery Oct 13 - Oct 18

Promo Codes Available:

For Your Every Summer RSVP, with Code: SUMMER15

Description

aglaonema key lime Aglaonema 'Arctic Lime'Aglaonema 'Arctic Lime' Aglaonema 'Arctic Lime' is a compact Chinese evergreen grown for soft lime green foliage with cream green marbling and deeper green edges. It forms an upright, leafy clump from short stems, with new leaves opening close to the centre before expanding into broad, oval lance shaped blades. The plant stays tidy in a pot, with pale foliage held clearly above the crown as it fills. This cultivar has a rounded indoor habit with a

Aglaonema 'Arctic Lime'

Aglaonema 'Arctic Lime' is a compact Chinese evergreen grown for soft lime-green foliage with cream-green marbling and deeper green edges. It forms an upright, leafy clump from short stems, with new leaves opening close to the centre before expanding into broad, oval-lance-shaped blades. The plant stays tidy in a pot, with pale foliage held clearly above the crown as it fills.

This cultivar has a rounded indoor habit with a dense upright crown. Young plants usually stay compact and multi-stemmed. Established plants widen gradually as fresh shoots develop from the base. The light leaf colour gives the crown a clear pale-green surface while the plant remains compact.

Aglaonema 'Arctic Lime' quick profile

  • Compact, upright Aglaonema with a tidy clumping habit
  • Broad oval to lance-shaped leaves with lime, cream-green and deeper green patterning
  • Smooth, slightly arching foliage that builds a rounded crown
  • Warm indoor rooms with bright filtered or steady medium light

Lime foliage, crown shape and background

Aglaonema 'Arctic Lime' grows from short, cane-like stems carrying leaves on fleshy petioles. The leaves are broad, smooth and gently pointed, with a pale central field and darker green margins. Each leaf shows a slightly different distribution of colour, creating natural variation while keeping the overall colouring light and even.

Aglaonema belongs to the Araceae, a family known for spadix-and-spathe inflorescences. Indoors, this cultivar is kept for its foliage. Mature, settled plants may occasionally flower, producing small arum-type inflorescences, but the leaf crown carries most of the colour and structure. Removing spent inflorescences keeps the crown neat.

Wild Aglaonema species come from warm, humid, shaded tropical forest habitats across Asia and New Guinea. Keep the plant in filtered light, even moisture cycles, airy substrate and stable warmth. 'Arctic Lime' is a cultivated Aglaonema selection.

Growing Aglaonema 'Arctic Lime' indoors

  • Light: Place in bright, filtered light or a steady medium-light position. Strong midday sun can mark the pale leaf tissue, especially close to hot glass.
  • Watering: Water when the top 2–4 cm of substrate has dried. Keep the root ball lightly moist during active growth, then water more sparingly during cooler, darker months.
  • Substrate: Use a loose aroid or foliage-plant mix with coco coir or fine bark, mineral particles and good drainage. The mix needs some moisture retention with air around the roots.
  • Pot and drainage: Use a pot with drainage holes. Let excess water drain fully before returning the plant to a cover pot.
  • Temperature: Keep above 16 °C, with 18–26 °C giving steadier growth. Cold windowsills, draughts and wet substrate can lead to dark, water-soaked-looking patches.
  • Humidity: Average home humidity is usually tolerated, but moderate humidity reduces sticking and crisping on new leaves. A humidifier or grouping with other tropical plants can raise humidity in very dry rooms.
  • Feeding: Feed lightly in spring and summer with a balanced houseplant fertiliser at reduced strength. Excess fertiliser can scorch leaf edges.
  • Repotting: Repot when the roots fill the pot or watering becomes difficult to manage. Move up by one pot size to keep the root zone evenly moist.
  • Pruning: Remove yellowing older leaves at the base. Older stems can be shortened if the plant becomes tall and bare, encouraging new growth from lower nodes.
  • Propagation: Established plants can be propagated by division or stem cuttings with visible nodes. Warmth and steady moisture are important during rooting.
  • Semi-hydro substrates: Aglaonema can adapt to mineral or semi-hydro substrates when roots are transitioned gradually and kept warm. Start with a healthy, actively growing plant.

Aglaonema 'Arctic Lime' health checks

  • Yellow lower leaves: One old leaf at a time is normal ageing. Several yellow leaves together point to a wet root zone, poor drainage or a cold position.
  • Brown leaf tips: Check watering pattern, fertiliser strength and very dry indoor air. Flush the substrate occasionally if salts have built up.
  • Pale, papery patches: These usually come from direct sun or heat against a window. Move the plant further from the glass or filter the light.
  • Soft stems or sour-smelling substrate: Inspect the roots. Soft brown roots indicate that the substrate has stayed too wet or too cold.
  • Fine speckling or dull leaves: Check the undersides and petiole bases for mites. Rinse the foliage and isolate the plant before treatment.

Rotation, display and leaf cleaning

Place Aglaonema 'Arctic Lime' where its pale leaves can be seen from above and from the side. Rotate the pot every few weeks to keep the crown balanced, especially near a window. Wiping dust from the leaves keeps the marbled pattern clear and makes pest checks easier.

Pet safety for Aglaonema 'Arctic Lime'

Aglaonema contains insoluble calcium oxalate crystals. Keep Aglaonema 'Arctic Lime' away from pets and small children, as chewing the leaves or stems can irritate the mouth, tongue and throat. The sap can also irritate sensitive skin, so gloves are helpful when pruning or dividing the plant.

Shipping Notes
  • Free Standard Shipping on $100+ Orders to the USA.
  • Except Preorder products are shipped in 48 hours.
  • Delivery to the USA:
  1. Standard Shipping : 3-10 business days
  • If time is of the essence, please consider selecting expedited delivery for faster service.
Exchange/Return Notes
  • We offer a 30-day return/exchange service after receiving.
  • Final sale items are not eligible for returns or exchanges.
  • To process your return/exchange, please contact us at [email protected]
  • Please click here for more details>>> Return & Exchange Policy
SKU: 19432880194

Discover Niche Categories That Outsell aglaonema key lime

Top-Converting Item to Boost Your Average Order

4.6 ★★★★★
Based on 13 reviews
Sort
Highest Rating
Newest First
Oldest First
Product Reviews
S
Verified Purchase
Shannon
Carnegie, US
★★★★★ 5
The best DL/ML book I have ever seen!!
Format: Hardcover
Fantastic deep-learning book! The logic is very easy to follow, but the content is very thorough when it comes to explaining the theories behind it, making it perfect for beginners as well as math and CS students. The best DL/ML book I have ever seen!!
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on November 30, 2025
W
Verified Purchase
William P Ross
Waukegan, US
★★★★★ 5
Comprehensive Look At An Incredibly Complex Topic
Format: Hardcover
Deep Learning is an advanced book with great explanations and details. There is a heavy math focus with the book's beginning chapters detailing the necessary linear algebra and probability that one will need to understand deep learning. I liked that the author's chose to cover only the parts of these subjects which are relevant to deep learning. There are many interesting philosophical sections in the book as well. Just about when I was feeling overwhelmed with the complexity of the mathematics the authors take a step back and cover the foundations of deep learning such as borrowing concepts from human learning. There was an interesting dicussion about the early studies done on the vision of cat's and monkey's in the 1970s. The text covers the entire history of deep learning and the bibliography is hundreds of sources. It is clear this is the most comprehensive text available about deep learning. For anybody interested in this topic this book is a mandatory read. There are sections about machine learning as well, which makes sense because deep learning is a subset of machine learning. These sections focused on the machine learning concepts which are most relevant to deep learning. The book was well organized and divided into three parts which cover mathematics related to deep learning, typical deep learning techniques, and then more experiment learning techniques. Often the author's state when a technique works well or when it does not, and which types of data works best for the technique. Just a warning, the math in this book is highly complex. It requires a lot of work to go through this book, but the effort will be well rewarded.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on March 15, 2017
A
Verified Purchase
Adam
Bozeman, US
★★★★★ 4
Too Dry.
Format: Hardcover
This was a required textbook for my class in college. I think it was too dry. The book titled Deep Learning: From Curiosity To Mastery is much more approachable.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 22, 2026
A
Verified Purchase
Amazon Customer
Grantham, US
★★★★★ 5
Comprehensive! The Bible of Deep Learning!
This book has by far surpassed my expectations! I have purchased many machine learning and deep neural network books in the past, but nothing has ever come close to this book! First of all, it is written by the fathers of Deep Learning, and is therefore an authority. Secondly, the book is broken into three parts: 1. A math overview and refresher. 2. Deep Learning applications and 3. Research in Deep Learning. I can't help but go through this book from front to back. It is a smooth read, and every sentence written is meaningful. These guys know their stuff! And after you read this book, YOU WILL ALSO know your stuff! If you feel daunted by the price, just remember, you get what you pay for! I'd say they could easily charge about $300+ for this book, but they are doing everyone a very kind favor by ONLY charging this reasonable amount. You get A LOT of bang for your buck with this purchase. I hesitated at first about buying this book because of the price, but I am soooooo happy that I did! Worth every penny! Look no further, get this book and start your Deep Learning journey!!
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on July 14, 2017
M
Verified Purchase
mackster
Fort Morgan, US
★★★★★ 1
A rushed, poorly written guide of how the "experts" can't really explain what Deep Learning is
Format: Hardcover
This book, in every sense of the word, is rushed. I think the authors wanted to establish themselves as leaders of this young-ish field, but does so by sacrificing quality. It also shows that Deep Learning theory has been there for a long time, known by another name called Neural Networks. The interesting algorithms are of MLP, Back Propagation and the classical neural networks. The optimization methods such as Adam are the ones that are new and interesting, and the only ones worthy of in this book. So, essentially, what you get from this book is use A for X, B for Y and C for Z type of dry, un-intuitive, badly written waste of paper. As for the structure of the book, it's like an example of how not to structure a book. It has some linear algebra, probability at the start (not good enough, and confuses more people and wastes paper). Goes on to prove other algorithms such as PCA (yeah, ok!). Then, talks about how this architecture works for this and that architecture. So, yeah, if you really want to try out deep learning, don't buy this book. Set up Tensorflow/pytorch/ other library, run the tutorials, find an architecture for the problem you are interested in and start tweaking that. You will have far more fun and would have saved your money. The praise that this book gets is beyond me. Did Musk even read this book? I doubt it.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 15, 2018

recommand products