SKU: 86286940702
burnout herbicide

burnout herbicide Avenger® | AG Optima Burndown Herbicide | Concentrate

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Description

burnout herbicide Avenger® | AG Optima Burndown Herbicide | ConcentrateAvenger AG Optima Burndown Herbicide Concentrate 1 gal. Item # AVGR OPTC1G 04 View SDS Avenger AG Optima is an excellent botanical alternative to synthetic, toxic herbicides when you need to use in areas where children and pets are present. Its intended for both agricultural and non agricultural use and has a more economical dilution ratio versus competitors. Using a natural citrus oil base, this is a non selective herbicide that kills a broad

Avenger® | AG Optima Burndown Herbicide | Concentrate | 1 gal.
Item # AVGR-OPTC1G-04 - View SDS

Avenger® AG Optima is an excellent botanical alternative to synthetic, toxic herbicides when you need to use in areas where children and pets are present. It’s intended for both agricultural and non-agricultural use and has a more economical dilution ratio versus competitors.  Using a natural citrus oil base, this is a non-selective herbicide that kills a broad spectrum of weeds and unwanted grasses naturally and quickly. Its main ingredient is d-Limonene and it is for use in organic production around both food crop and non-crop areas. Always follow label directions.

  • Environment: Outdoors, Crops, Orchards & Vineyards, Nursery
  • Active Ingredients: d-Limonene (citrus oil)
  • Shelf Life: 2 years from manufacture date
  • Toxicity: No toxicity known
  • Certifications: EPA, USDA NOP
  • Storage: Store in original container

 How to Use: 

Mix this product in clean water and apply to the foliage of vegetation to be controlled. Spray until weeds are thoroughly wet. Because the underside of the weed leaf may be more susceptible, side sprays are recommended.

Environmental Conditions:

Avenger® AG Optima is effective over a wide range of environmental conditions. Cool weather may slow the activity of the product. For best results, spray when ambient high temperatures are expected above 50°F and lows above freezing. On cooler days, spray during the warm part of the day. Allow heavy dew to evaporate prior to Avenger® AG Optima applications. Do not apply if windy conditions exist or rain is expected within 2 hours.

 Mixing of Avenger® AG Optima:

 Fill the spray tank ½ full with clean water. Add Avenger® AG Optima while agitating. Then fill remainder with water.

 Tank Mixing of Avenger® AG Optima:

 Fill the spray tank ½ full with clean water. Add any dry formulations and then liquid formulations to the tank. Add Avenger® AG Optima while agitating. Then fill remainder with water.

 Restrictions:

 Do NOT exceed 5 gallons of Avenger® AG Optima (20.4 lbs. d-limonene) per acre per application. Do NOT exceed a total of 16 gallons of Avenger® AG Optima (65.1 lbs. d-limonene; Table 1) per acre per year. Determine the final desired finished spray volume according to the appropriate dilution as describe in Table 1. Irrigation and Aerial

Applications: Do not apply this product through any type of irrigation system or by aerial application.

 Spray Drift Management:

 Follow directions for minimizing spray drift. Do not allow the herbicide solution to contact desirable vegetation as small amounts can cause severe damage to crops and other desirable plants. AVOID CONTACT WITH CROP – Intentional or accidental contact (including drift) of Avenger® AG Optima with the crop may result in severe damage or loss of the crop.

 Application Rate:

Four types of applications are described below: Broadcast, Banded, Spot and Pre-Harvest Desiccation. Mixing volumes for two dilution rates are found in Table 1. Apply Avenger® AG Optima at a 7-10% mixture depending on the size of the weeds. For smaller, young, actively growing weeds and grasses, apply the lower 7% mixture. For controlling larger, tough to kill weeds, use the higher 10% mixture. Use the lowest mixture whenever possible to control weeds and grass.

  • Broadcast Applications: Broadcast treatments are used for burndown of unwanted weeds and grass across a field or a plot or apply to burndown winter foliage. Apply Avenger® AG Optima at pre-emergence or at planting. Applications must be made before seedling emergence to avoid severe injury. Allow at least 2 days between application and transplanting. Spray until weeds and grass are thoroughly wet.
  • Banded Applications: Control or suppression of emerged weeds and grasses in row middles and between vines and trees. Apply Avenger® AG Optima at a 7-10% mixture depending on the size of the weeds. Only use the 10% mixture when absolutely necessary to control difficult weeds. Apply by directing spray between the rows and using hooded sprayers to prevent spray contact with crop plants. Keep hoods adjusted to ensure adequate contact with weeds and grass while shielding the crop from the herbicide. To minimize drift, do not use nozzles or nozzle configurations that produce fine droplets (mist).
  • Spot Applications: In cool situations or for tough to kill weeds, a more concentrated spray of d-limonene may be needed. In such situations, a 10% mixture of Avenger® AG Optima (1:10 mixture) may be used up to one (1) week before harvest (see Table 1).
  • Pre-Harvest Desiccation of Vegetable Vines: Apply Avenger® AG Optima at a 7 or 10% mixture to aid in the desiccation of vegetable vines prior to harvest operations. A second application may be necessary to obtain sufficient desiccation.

Table 1. Mixing Directions of Avenger® AG Optima

Desired Spray volume (gallons)

7%

10%

1

9 fl. Oz

13 fl. Oz

60

4.2 gal

6 gal

100

7 gal

10 gal

160

11.2 gal

16 gal

228

16 gal

N/A

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SKU: 86286940702

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Amazon Customer
Los Angeles, 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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Kindle Customer
Grantham, US
★★★★★ 5
Very useful book
Format: Paperback
I use it for the machine learning class I teach.
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Reviewed in the United States on May 3, 2026
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Tommy Jonsson
Waukegan, US
★★★★★ 5
Cover many areas in detail and recommendations for more to read for what's outside
Format: Paperback
Good book!
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Reviewed in the United States on May 4, 2026
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Moses Kayanda
Boise, US
★★★★★ 5
One of the best machine learning books...
Format: Paperback, Format: Paperback
Machine Learning can often be intimidating whether you are starting out or already a practitioner. It is easy to get stuck on one concept, walk away frustrated, or just copy that code you find on StackOverflow without really understanding what it does. What the authors of this book, Machine Learning with PyTorch and Scikit-Learn, have managed to do is to keep the reader engaged giving a deeper illustration as to how the concepts work. In this book, you get practical code examples, a detailed explanation of how the various library tools work, and exposure to the mathematical concepts behind machine learning algorithms. In addition, what I like about the book unlike many machine learning books is that the authors have managed to intuitively explain how each algorithm works, how to use them, and the mistake you need to avoid. I have not read a Machine Learning book that better explains Transformers as this one does. The authors have managed to give a detailed dive into this model architecture through well-explained codes and illustrations. As a reader, you walk away having intuitively grasped the concepts of attention and self-attention in ways that will make this crucial NLP architecture clear. You get exposed to pre-trained models from HuggingFace library which really helps to have that hands-on experience working with large datasets. As they have done throughout the book, the authors have broken down those complex mathematical operations into simple explanations that are easy to follow. What I generally like about the book is how it seamlessly connects all the chapters, not throwing off the reader. There are numerous external resources quoted throughout the book. This helps spark that curiosity to dig deeper. In addition, you get introduced to PyTorch, getting exposed to all those sophisticated libraries that help the reader learn how to maximize their compute power. I would say it is not intimidating at all even if you have not used PyTorch before. I would recommend this book to anybody seeking a textbook that is both easy to read and modern in its content. If were to rate the book I will give it a 10/10 as it really applies to both beginners and experienced practitioners, covers all the concepts one needs to apply in their operations, and acts as a quick reference.
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Reviewed in the United States on March 1, 2022
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Gabe Rigall
Whiting, US
★★★★★ 5
Thorough Primer for Machine Learning and PyTorch
Format: Paperback
BLUF: A thorough primer for machine learning enthusiasts with plenty of theory to underscore its many practical examples. A definite must-have for anyone looking to add PyTorch to their machine learning tool belt. PROS: - Extremely thorough (if not comprehensive). I really appreciate that this book doesn't just thrust one into building models with PyTorch. It starts at the "beginning" and provides examples, theory, additional resources, and citations along the way. - Theory. Those whose calculus and linear algebra courses ended many years ago will appreciate (if not remember exactly) the mathematical theory and notation that accompanies almost every paragraph. This book gives one the opportunity to "dig deeper" or stay in the shallows until the notation stops. - Python. Rather than simply utilizing Scikit-Learn to illustrate concepts and introduce models, this book contains many sections where models (such as a Perceptron) are coded from the ground up so the reader can fully understand the underlying mechanics. Python enthusiasts will nerd out. Parents of small children might want to skip a few pages. - Graphs, charts, and graphics. There are plenty of places where a drier text might have foregone the use of graphs. This text does not. It does however refrain from overusing them. - PyTorch. This should be obvious from the title, but this text prioritizes PyTorch instead of TensorFlow. This is especially helpful for those looking for an alternative to Keras and TensorFlow as the PyTorch API is very user-friendly. CONS: - Almost too much code. This isn't a true "con" but anyone wanting to emulate or follow along with the examples would do well to get the digital edition so they can copy and paste. - Length and complexity. Anyone hoping for a "quick read" or a "quick start guide" will be disappointed. This book hovers somewhere between an undergraduate primer and a graduate-level text for length and readability. This is not to say that it's difficult to read, merely that there are other "quick start" / "practical" texts out there that cater more to a lay audience.
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Reviewed in the United States on February 26, 2022

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