SKU: 15056561646
surmount herbicide where to buy

surmount herbicide where to buy Ornamec Over The Top Herbicide

Sale price$18.28 Regular price$20.31
Save 10%

Shipping Estimate
USA
  • USA
  • CAN

Ships within 48 hours · Estimated delivery Jul 14 - Jul 19

Promo Codes Available:

For Your Every Summer RSVP, with Code: SUMMER15

Description

surmount herbicide where to buy Ornamec Over The Top HerbicideOrnamec Over The Top Grass Herbicide Recommendations Post emergence control of grass weeds in and around ground covers, shrubs and trees in landscape beds, container yards and grower nursery fields. Ornamec Over The Top Grass Herbicide provides outstanding postemergence control of unwanted grasses in groundcovers, shrubs and trees. And the majority of the nearly 500 species and varieties of plants on the label may be treated with Ornamec applied over

Ornamec Over-The-Top Grass Herbicide

Recommendations
Post-emergence control of grass weeds in and around ground covers, shrubs and trees  in landscape beds, container yards and grower nursery fields.

Ornamec Over-The-Top Grass Herbicide provides outstanding postemergence control of unwanted grasses in groundcovers, shrubs and trees. And the majority of the nearly 500 species and varieties of plants on the label may be treated with Ornamec applied over-the-top*. Some species or varieties of ornamentals require that Ornamec be applied as a directed spray in order to minimize phytotoxicity.

Where can Ornamec be used? Examples include: Evergreen and wild flower beds to remove unsightly grass. Ground covers to maintain immaculate appearance. Nurseries to remove grass in the field-grown woody ornamentals.

Ornamec takes out unwanted bermudagrass without injury to desirable tall fescue and zoysia turf.

There are over 30 grass weed species listed on the label. Youll find many common types of unwanted annual grasses: crabgrass, barnyardgrass, goose grass, foxtail, sandbur, panicum. Also, few herbicides are as effective as Ornamec against hard-to-control perennial grasses. Quack grass, bermudagrass and torpedo grass are examples. Another is johnsongrass which is controlled in both rhizome and seedling stages.

Does not control broadleaf weeds, rushes and sedges.

*See label directions for species not to be sprayed over-the-top.

  •     Selectively controls emerged annual grasses panicum, goosegrass, crabgrass, foxtail, sandbur and barnyardgrass
  •     Also controls perennial grasses such as bermuda grass, quackgrass, torpedograss and johnsongrass
  •     "Over-the-top" applications on most ornamentals - shrubs, ground covers, trees, flowers and wildflowers listed on the label
  •     May be used on and around newly-emerging ornamentals as well as transplants
  •     Treated grass ceases growth in as little as 48 hours
  •     Grass death in 1 to 3 weeks
  •     Rain-fast 1 hour after application
  •     Selective removal of bermudagrass from zoysia and tall fescue turf
STATES NOT REGISTERED

AK

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: 15056561646

Discover Niche Categories That Outsell surmount herbicide where to buy

Top-Converting Item to Boost Your Average Order

4.1 ★★★★★
Based on 861 reviews
Sort
Highest Rating
Newest First
Oldest First
Product Reviews
Z
Verified Purchase
Zygerian99
Alexandria, US
★★★★★ 5
The definitive guide to becoming a researcher in the field
Format: Hardcover
This is not a coding book. I see a lot of negative reviews around the expectation that this book would teach the reader how to quickly build machine learning systems and write code. This book is not for that audience. If you just want to build applications, don't worry about how deep learning works. It's akin to needing to understand how an engine works just to drive a car. If you are looking for a coding resource, try: https://www.amazon.com/Hands-Machine-Learning-Scikit-Learn-TensorFlow/dp/1492032646/ref=sr_1_4?keywords=machine+learning+tensorflow&qid=1579608765&sr=8-4 . And even with that book, the material still goes far beyond what you need - use it as a light reference. I bought this book as an aspiring machine learning researcher, and towards that end, it is the best resource available in print (still true as of 2020). For instance: The first 5 chapters are timeless. These are things that were mostly established 20 or 30 years ago and beyond and are mostly STEM fundamentals at this point. There are whole textbooks dedicated to each of those chapters, but the authors provide a quick refresher and overview of probably 80% of what you'll encounter in deep learning. If you haven't previously learned each of these subtopics, you'll probably want to study them individually since they are the key to innovating (linear algebra, probability & stats, numerical computation, machine learning fundamentals). Chapters 6 thru 9 are the foundation of deep learning. We're about 12 years into seeing rapid change in the deep learning space, yet all of these principles and techniques still hold (many recent innovations are still relying on Convolutional models in 2020, which is the most layered/complex topics in those chapters). Therefore, I'd wager that these chapters are also fairly stable knowledge that is worth internalizing if you want to be deeply involved in the future of machine learning. Chapters after 9 are mostly experimental topics, and many of them are already the wrong strategies for optimal results. But there are interesting ideas in here that you'll often encounter in the wild, so it's good exposure to various topics. But probably not worth much of your time. And lastly, there is good history in here from people who know the space intimately. It's a good way to piece together the developments and learn the lexicon of deep learning so you can have intelligent conversation with experts.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on January 21, 2020
S
Verified Purchase
Shannon
Lexington, 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
Natrona Heights, 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
Battle Creek, 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
Cuba, 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

recommand products