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.

 

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 2023, we conducted watergrass field trials at five locations in Butte County.  Watergrass populations were high in all fields except the one at the Rice Experiment Station, which was applied as a control to confirm toxicity. All varieties wereCalrose medium-grain. The herbicides tested wereStam 80DF® (propanil), Abolish® (thiobencarb), Shark H2O® (carfentrazone),  Loyant® (florpyrauxifen-benzyl), Clincher CA® (cyhalofop-butyl), Regiment® (bispyribac-sodium),andSandea® (halosulforon) (Table 5). Applications were made at 35-40DAS, at 20 gallons per acre spray volume. Results (averaged across the 5 locations) indicate that Regiment® followedbyStam® (9), and Stam + Abolish® (4) are good candidates forwatergrass control. Those 2 treatments showed great watergrass control and high yields (Figures 2 and 3). Additionally, only mild phytotoxicity was observed throughout the duration of the trial for the treatment (Figure 1). Treatments that are not quite as good in grass control but good in arotationincludeStam® +Loyant® (6),  Stam® + Shark® (5), Regiment® + Clincher® (11),andStam® + Clincher® (7). These treatments resulted in lower rice yields and less effective watergrass control compared to treatments 9 and 4 (Figures 2 and 3). They also caused some phytotoxicity,  with Stam® + Shark® (5) causing significant tip burn at the 7 days after application evaluation (Figure 1). In these treatments,  Stam® can be substituted withSuperWham®.

 

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.