- Author: Luis Espino
Last year was a blast year. I first saw leaf lesions in some fields right about heading time. In other fields there were no leaf lesions, but neck blast developed later. It would be helpful to have a way to predict when weather conditions are favorable for blast so more information is available to make monitoring and treatment decisions.
Weather plays a key role in the development of blast. One of the factors that allows blast development is leaf wetness. This is free moisture in the surface of the leave. Spores need this moisture to germinate and infect the plant tissue. If the period of leaf wetness is too short, the spores may germinate but they might not have enough time to produce an infection. When the period of leaf wetness is sufficiently long, infections can occur.
This year I have deployed leaf wetness and temperature sensors in three rice fields in areas where blast is common (fig. 1). At all locations leaf wetness is very low during the day, increases to 100% at night, and then decreases again as the day warms up (fig2).
Figure 1. Fields where leaf wetness and temperature is being monitored at the canopy level. The three sites are indicated by the blue circles.
Figure 2. Leaf wetness during July 11 and 12 at the Rd 55 field.
Using data from the three fields, I calculated the hours of leaf wetness available each day for blast spore germination and infection and compared that to the time needed by spores to germinate and infect (fig. 3). The data shows that during the first week of July the hours of leaf wetness were sufficient for spore germination and infection. After infection, lesions may form 4 to 14 days later. This means that, if blast spores were present during early July, we may start seeing infections soon.
Figure 3. Graph comparing the hours available and needed for blast spore germination and infection at the Rd 55 location. When the hours available (orange line) are higher than the hours required (blue line), infections may occur if blast spores are present.
I will continue to monitor field conditions and update the forecast next week.
- Author: Whitney Brim-DeForest
- Author: Luis Espino
- Author: Roberta Firoved
- Editor: Taiyu Guan
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At our last meeting, we had some questions about the approved uses of pendimethalin in California rice. There are several products labeled for use on rice with pendimethalin as the active ingredient. As of June 2024, pendimethalin registered products (on rice) include Prowl H2O, Prowl 3.3, Harbinger, Satellite Hydrocap, Stealth, Helena Pendimethalin, Pavilion H2O, Pavilion 3.3, and a few others. Please make sure to always check the product label, as not all pendimethalin products allow use for the below-listed timings. Furthermore, labels are updated regularly, so it should not be assumed that the same use pattern applies from season to season. For the most currently-registered products, refer to the California Department of Pesticide Regulation website, product label databases, as well as manufacturers' websites for reference. Please remember the container label is the deciding point for pesticide use enforcement.
The mode of action of pendimethalin is disruption of mitosis (WSSA Resistance Group 3). In California rice, there is no other herbicide registered with this mode of action. The herbicide binds to clay soils, with residual activity of between 1 to 4 months, depending on environmental conditions. Pendimethalin can be readily absorbed by young roots, and thus, weeds are controlled as they germinate. Damage can also occur to rice or other crops as they germinate. Weeds are not controlled by this product once emerged and established.
Labeled controlled weeds are: junglerice, barnyardgrass, and sprangletop. Barnyardgrass and sprangletop are the two most abundant grass weeds in dry- or drill-seeded California rice, also causing the most yield loss. Rotating with pendimethalin can help to manage herbicide-resistance biotypes, as well as preventing the selection of herbicide resistance in these species.
Pendimethalin Rice Timings (product-dependent):
Preflood, preemergence: In drill- or dry-seeded rice, pendimethalin can be applied to the soil surface AFTER rice has been dry-seeded and lightly incorporated or drill-seeded. The product should be tank-mixed with a safener adjuvant. Water should be flushed across the field AFTER herbicide application (within 7 days).
Delayed preemergence: NOT a currently labeled use for any pendimethalin product registered in California.
Early postemergence: Only for dry-seeded rice and into fields with no standing water. Pendimethalin is usually applied with a tank-mix partner. Timing should be based on the leaf stage of the rice or weeds as appropriate for the tank-mix partner. Field should be flooded or flushed within 7 days after application.
Postemergence: For water-seeded rice (California ONLY) between the 4-6 leaf stage. Field must be completely drained with no standing water at time of the pendimethalin application and should be reflooded within 7 days after application.
- Author: Whitney Brim-DeForest
- Author: Taiyu Guan
Watergrass (Echinochloa spp.) in California rice is the most competitive weed complex. Plants can emerge under both continuously flooded conditions and flushed conditions, causing huge yield losses (up to 100% in dry- or drill-seeded systems). Watergrass is one of the first weed groups in which herbicide resistance was found (in the early 2000s). It has developed multiple herbicide-resistance and the resistance is metabolic, meaning that plants can essentially “consume” the herbicide, breaking it down so it does not kill the plant.
Currently, there are 4 main watergrass species in the California rice system: barnyardgrass (E. crus-galli), early watergrass (E. oryzoides), late watergrass (E. phyllopogon), and coast cockspur (E. walteri). Coast cockspur is a new species to California rice. We first found coast cockspur in California rice fields in 2017. It is robust and large-stemmed and can reach heights of over 6 ft tall when uncontrolled. All species have some level of resistance, and resistant biotypes are found throughout the Sacramento Valley (all counties).
In the past few years, we have been having increasing issues controlling watergrass, and many of us have resorted to using a double application of propanil to control it. The issue with this is that we are already seeing propanil resistance, and this practice will select for grasses that are propanil-resistant, causing us to eventually lose the product.
The best means to prevent the selection for propanil resistance are:
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Rotating modes of action (not using propanil as a clean-up spray year after year)
- Using tank mixes as clean-up sprays (in combination with propanil)
We have been researching possible cleanup tank mix options for the last few years (alternatives to the double propanil spray), and will continue to do so in 2024, to provide growers and Pest Control Advisors with feasible watergrass control options.
Alternatives to the Double-Propanil Application (2022)In 2022, we conducted one trial in a sweet rice field in Yuba County. Treatments tested are listed in Table 1. Applications were made at tillering (approximately 35-40 days after seeding), at 20 gallons per acre spray volume. Weed control (%) and phytotoxicity data were collected on 7, 14, and 28 days after spray (DAS) (Tables 2 and 3).
Table 1. Treatments applied in 2022 field testing (applied at 35-40 days after seeding) for watergrass control.
Table 4. Rough rice yields (lb/A) in 2022 field testing.
Alternatives to the Double-Propanil Application (2023)
Weed control (% control, watergrass only) and phytotoxicity (% Stunting, % Stand reduction, % Tip Burn) evaluations were made 7 Days After Application (DAA), 14 DAA, and 21 DAA. Fields were harvested in September 2023. Yields were lower than normal due to hand-harvesting as well as rice laying down flat in the water at harvest in a couple of the fields.
Results (2023)
Figure 1. Phytotoxicity (Tip Burn, Stunting, and Stand Loss) in 2023 field testing (7, 14, and 21 Days After Application) averaged across all 5 sites.
Figure 2. Percent watergrass control (%) (Treatments 2-12) compared to the untreated control (Treatment 1) in 2023 (21 Days After Application). Treatment 1 (Untreated) is the percent watergrass cover per plot, not the percent control. Averages are across 4 sites (Rice Experiment Station was not included due to low watergrass populations).
Figure 3. Rough rice yields (lbs/acre) for 2023 watergrass field testing averaged over the 5 locations.
Recommendations:
To effectively manage tough watergrass, growers should use integrated weed management where possible. This includes:
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Using combinations of chemicals (granular) and tank-mixes (foliar)
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Rotating chemistries at the beginning of the season
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Rotating clean-up herbicides
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Crop rotation or fallow
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Winter flooding to maximize seed predation and decomposition over the winter
Herbicide recommendations include (at the beginning of the season):
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Zembu® (pyraclonil) if other granular options are ineffective, to give other chemistries a break. Zembu® suppresses grass (does not control) but will help prevent the selection of resistance as it is a new mode of action for watergrass.
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Cerano® followed by Butte®, applied one week apart, which is effective even on tough grass.
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Implement a stale seedbed approach by applying glyphosate or Suppress® (capric/caprylic acid)
pre-plant as a rotational tool.
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Pendimethalin (Harbinger®, Prowl H2O®, and others) to rotate MOA (please see additional
recommendations about the use of pendimethalin in the other article in this newsletter).
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Abolish® + Regiment®
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Abolish® + SuperWham®/Stam®
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Regiment® followed by Superwham/Stam® (may cause injury on certain specialty varieties)
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SuperWham®/Stam® + Loyant®
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SuperWham®/Stam® + Shark H2O® (some phyto)
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Regiment® + Clincher®
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SuperWham®/Stam® + Clincher®
- Author: Luis Espino
I have been monitoring some fields in the Glenn and Butte County area the past two week and I have been finding some significant number of armyworms. Defoliation is not noticeable yet, at least not just by looking at the canopy. If you look under the canopy you may see some defoliation. The worms are still small but I have been finding 5 or more worms per square foot. Past research has shown that more than 5 worms per square foot can result in defoliation exceeding 25%.
Armyworms found on June 28, 2024, Butte County
Boxplot of number of larvae per square foot found causing defoliation in seven locations of the Sacramento Valley of California, 2022 and 2023. Numbers above boxes correspond to the number of observations of that level of defoliation.
Make sure you scout your fields closely this upcoming week. Early next week we will know if we are at peak moth flight, which would mean that next week is when we expect the most worm activity.
- Author: Sarah Marsh
- Editor: Taiyu Guan
- Editor: Consuelo B Baez Vega
Globally, approximately 570 million small and medium-sized farms need training in various agricultural fields. However, the delivery of agriculture training faces significant challenges. In some areas, the difficulty in obtaining this training has led to people turning to generative artificial intelligence (AI) models such as ChatGPT to ask questions relating to their agricultural production.
The way that ChatGPT and other models work is that the models are trained on vast amounts of data to learn patterns and relationships between words. This enables the models both to understand language in nuanced ways and to generate answers to a wide range of prompts, which means that ChatGPT can become adapted to specific uses and theoretically provide a comprehensive answer to any question. Researchers supported by the CGIAR's Excellence in Agronomy Initiative and the Digital Innovation Initiative studied the accuracy of Chat GPT-provided information and professional advice in response to queries from African farmers. Tzachor et al (2023) found significant inaccuracies that could potentially lead to poor management and crop losses. The problems with the answers ranged from vagueness to inaccuracy.
I became curious as to how accurate ChatGPT was with regards to questions relating to California rice and so conducted an informal test of my own. I asked ChatGPT questions relating to California water-seeded rice management to see how accurate the model was.
When queried about the insecticides that are registered for use in California water-seeded rice to control armyworms, ChatGPT responded with 6 insecticides – only one of which (lambda-cy) is used in CA rice systems. The remaining insecticides “recommended” were not used in California, not used for armyworms, or no longer commercially available.
I also asked ChatGPT “How to manage weedy rice in California water-seeded rice fields.” The model returned several paragraphs, with one problematic paragraph reproduced below:
Apply herbicides labeled for controlling weedy rice in water-seeded rice fields. Herbicide options may include products containing penoxsulam, propanil, or other active ingredients specifically targeting weedy rice. It's crucial to follow label instructions carefully and use herbicides at the appropriate timing and application rates to maximize effectiveness and minimize off-target effects.
As evidenced by these examples, ChatGPT is responding with answers that are not accurate and should not be taken as recommendations.