When going into the field to evaluate a crop, there are typically three fundamental points we need to take into consideration that include: 1) stage of growth, 2) general crop vigor and yield potential, and 3) anticipate the next stage of development and what we need to do in terms of field crop management. These considerations are commonly focused on aboveground crop evaluations. The root system is also an important part of the crop condition to evaluate but we commonly do not evaluate roots because of the difficulty in doing so.
Root systems and early development were described in a basic manner in a recent article on 4 September (UA Vegetable IPM Newsletter Volume 15, No. 18).
The effective root zone depth is the depth of soil used by the bulk of the plant root system to explore a soil volume and obtain plant-available moisture and plant nutrients. Effective root depth is not the same as the maximum root zone depth. As a rule of thumb, we commonly consider that about 70% of the moisture and nutrient uptake by plant roots takes place in the top 24 inches of the root zone; about 20% from the third quarter; and about 10% from the soil in the deepest quarter of the root zone (Figure 1).
The small and very fine root hairs are the most physiologically active portion of a developing root system. It is important that plants continue to develop and generate fresh young roots and an abundance of fine root hairs to maintain water and nutrient uptake.
Figure 1. General pattern for plant-water and nutrient uptake from the soil profile.
Root development patterns are dependent on the nature of the soil profile in the field. Soil profiles with compaction layers, as well as rock, clay, or caliche layers can limit and alter root development and the full exploration of the soil volume that the plants are capable of (Figure 2). So, it is good to know what the soil profile looks like in the field and understand how that will impact plant root development.
Figure 2. Generalized soil profile with major horizons.
Leafy green vegetable crops need to develop a marketable plant in a relatively short amount of time and a strong root system is essential. Transplants are commonly being used in vegetable crop production systems and the transition of transplants to field conditions is a major step in the production process. The transition is primarily experienced by the plant below ground.
Transplanted crops will have altered root systems due to the constraints within the rooting cone. Further root development beyond the original cone rooting mass is important for crop success. Thus, it is important to monitor the root system transition and the relationship to overall plant development.
Checking root systems is a plant destructive process since we need to literally excavate the roots from the soil and it does take time and effort. Accordingly, it is also important to be careful of where and how we sample plants and evaluate the root systems in a field.
Crop species can vary significantly in their patterns of root development, and it is important to know what is “normal” when evaluating crops in the field. An excellent reference for vegetable crop root system development is a 1927 publication by Dr. John E. Weaver and William E. Bruner from the University of Nebraska (Root Development of Vegetable Crops). This publication can be found at the following link:
https://soilandhealth.org/wp-content/uploads/01aglibrary/010137veg.roots/010137toc.html
A few basic examples from the Weaver and Bruner publication are provided in the following figures (Figures 3-10).
Figure 3. Cauliflower, 3 weeks after transplanting
Figure 4. Cabbage roots, 55 days after transplanting.
Figure 5. Cabbage roots, 75 days after transplanting.
Figure 6. Pepper roots, 24 days.
Figure 7. Pepper roots, 45 days (6 weeks).
Figure 8. Pepper roots, mature.
Figure 9. Lettuce roots, 3 weeks. The roots on the right were grown in compact
soil, the roots on the left were grown in loose/open soil.
Figure 10. Lettuce roots, 60 days.
First, I want to thank everyone who participated in last week's Vegetable Pest Losses Survey.
This year's survey included the return of the lettuce disease losses section. While several diseases were present and managed last season, downy mildew accounted for the majority of disease management costs by a wide margin. This really underscores the
impact that last spring's unusually rainy weather had on disease development across the Yuma lettuce production region.
No one can predict exactly what this upcoming spring will bring, but there has been discussion about the possibility of a strong El Niño leading to an extended monsoon season. If that proves true, the conditions would once again support spring
downy mildew development. The pathogen only needs about 3 to 4 hours of continuous leaf wetness to infect lettuce, so periods of overnight moisture, prolonged morning dew, or frequent rainfall when inoculum (spores) are present increase disease risk.
With that in mind, this seems like a good opportunity to review what is known about downy mildew and discuss strategies for its management.
Resistance in lettuce to Bremia lactucae, the causal oomycete pathogen behind downy mildew, is inherited in a gene-for-gene fashion, meaning one major gene product in the plant host interacts with one major gene product in the pathogen. When
resistance is present, this leads to an incompatible interaction between plant and pathogen and results in complete immunity to infection. Resistance genes in these types of interactions most often encode a protein molecule that acts like a burglar
alarm. These molecular sensors in the host bind to proteins secreted specifically by the pathogen, and when that happens a storm of defense responses is activated in the plant that excludes further infection. This is not the only mode of genetic resistance
found in plants, but it is often the most drastic and effective against obligate parasites like downy mildew.
But this simple gene-for-gene interaction often puts incredible selection pressure on the pathogen populations to change such that they can get around the resistance. By losing the molecule that the plant detects in order to initiate a defense response,
the pathogen becomes unrecognizable to the resistance genes a plant variety may have. Just like spraying the same mode of action over and over again leads to a pest population developing resistance to a pesticide, the same selection applies to genetic
resistance. The longer a resistance gene is deployed in a region, the more likely the pathogen population is to change in response until that resistance gene is no longer effective at managing the disease.
One of the biggest challenges with lettuce downy mildew is that B. lactucae is constantly changing over time. It exists as many different races, where each race has a different reaction to the resistance genes bred into lettuce varieties. You
can think of these races as different versions of the same pathogen. A lettuce variety that resists one race may still be susceptible to another.
These races are identified by testing them against a panel of lettuce varieties with known resistance genes. In the western United States, races are named by the International Bremia Evaluation Board-U.S. (IBEB-US) and are given names with a number followed by the country’s abbreviation, such as 8US, 9US, or 10US. The populations found in the western U.S. are different from those found in Europe, so each region uses its own independent naming system.
The downy mildew population has changed considerably over time. Earlier races (1US through 4US) are now rarely found in commercial lettuce production. During the 2000s and 2010s, races 5US through 8US became the most common. Race 9US was recognized after being detected repeatedly between 2015 and 2017, and the newest officially recognized race, 10US, was designated in 2025. Below is a pie chart showing the relative frequency of the races identified from 114 Yuma County downy mildew samples between 2023-2024:
Figure 1: Pathotyping results of 114 lettuce samples from Yuma County collected between 2023 and 2024. Data source: https://bremia.ucdavis.edu/bremia_database_main.php
The results show that much of the downy mildew population found in Yuma County is made up of novel strains of Bremia lactucae that have not yet been officially classified as a race. An official race is only recognized after it has been shown to be stable and widespread over multiple locations and growing seasons. These newer strains may disappear over time, or they may eventually become established and earn an official race designation. In the meantime, this means growers and lettuce breeders in Yuma County are often dealing with strains that can dodge the resistance in some lettuce varieties before those strains are common enough to be officially recognized. It also highlights why relying on resistance alone is not enough to manage the disease.
Table 1: Pathotyping and fungicide sensitivity results of samples from Yuma County collected in 2025.
This trend appears to be continuing. All of the downy mildew samples sent for race testing last season were identified as novel strains rather than known, officially designated races.
It's impossible to predict exactly how these new strains will respond to the resistance genes found in today's commercial lettuce varieties. However, because they have not been previously characterized, they are more likely to overcome existing genetic
resistance than the races we already know about.
New strains develop naturally over time. They can arise when different strains exchange genetics (i.e. intermate) or through random mutations. When growers plant varieties with similar resistance packages over large areas, the pathogen population
is placed under strong selection pressure. Any strain that happens to acquire the ability to infect those resistant varieties gains a major advantage and gets to reproduce without competition where other strains cannot. Over just a few disease
cycles, those successful strains can become much more common in the population until they are the predominant strain overall.
An important point to remember is that the resistance bred into commercial lettuce varieties is not wearing out or becoming weaker over time. The genetics in the lettuce remain just as effective as when the variety was released. What changes is the
pathogen. As the downy mildew population evolves new strains emerge that can bypass resistance genes that previously worked very well.
That means that varieties carrying resistance to races 5US through 10US are still doing exactly what they were designed to do. They continue to suppress those known races and help prevent them from becoming widespread in commercial fields. So, if
you experience significant downy mildew in a field planted with a variety that has a strong resistance package, the culprit is most likely one of these newer, uncharacterized strains rather than a failure of the variety itself.
Unfortunately, Bremia lactucae can evolve much faster than scientists can identify new races and breeders can develop and release resistant varieties. That's why no resistance package should be viewed as a stand-alone solution.
This is also why extension, researchers, and the seed and crop protection industries place so much emphasis on the integrated pest management (IPM) concept. Genetic resistance is an essential tool, but it works best and remains the most sustainable when combined with other management practices. For novel strains that can slip past host resistance, timely fungicide applications and other disease management strategies become especially important for maintaining control.
Figure 2: Mean disease severity by treatment. Disease severity was determined by rating 10 plants within each of the five replicate plots per treatment using the following rating system: 0 = no downy mildew present; 1 = downy mildew present on bottom leaves of plant; 2 = downy mildew present on bottom leaves and lower wrapper leaves; 3 = downy mildew present on bottom leaves and all wrapper leaves; 4 = downy mildew present on bottom leaves, wrapper leaves, and cap leaf; 5 = downy mildew present on entire plant. Disease severity is displayed as the mean of five replicates across all three lettuce varieties and bars show a 95% confidence interval around the mean calculated from individual treatment data. Compact letter display (CLD) above boxes show significantly different treatments (Kruskal-Wallis ANOVA and Dunn’s test). Boxes sharing the same letter(s) are not significantly different from one another. Fb = “followed by” in the rotation. Not all products are registered yet for use in lettuce. The inclusion of specific fungicide products or formulations in these trials does not constitute an endorsement or recommendation over other labeled products.
The most effective way to manage lettuce downy mildew is to use an integrated approach. Plant varieties with a strong resistance package against races 5US through 10US, and pair that resistance with timely, full-label-rate fungicide applications when environmental conditions favor disease. This combination provides the broadest and most reliable protection against both known races and the novel strains that continue to emerge in Yuma County.
If you have any concerns regarding the health of your plants/crops please consider submitting samples to the Yuma Plant Health Clinic for diagnostic service or booking a field visit with me:
Christopher Detranaltes, Ph.D.
Cooperative Extension – Yuma County
Email: cdetranaltes@arizona.edu
Cell: 602-689-7328
6425 W 8th St Yuma, Arizona 85364 – Room 109Over the last couple of years, there has been tremendous investment and research and development in autonomous weeding machines. At least 40 such robots have been promoted all over the world. Two of these available in the Yuma area are Naio Technologies’ Dino1 and FarmWise’s Titan. If you are not familiar with these technologies, the Naio Dino is a four wheeled, self-driving platform (Fig. 1). The robot is equipped with an imaging system that detects crop rows and an actuator that automatically adjusts the position of cultivating tools relative to the crop row allowing for close cultivation. The FarmWise Titan is an autonomous power unit coupled with an automated weeding machine (Fig. 2). It utilizes an imaging system to detect crop plants. Pairs of knife blades are automatically controlled to open and close around the crop plant to control in-row weeds.
Mosqueda et al. (2021) evaluated the two autonomous weeders in trials with lettuce last summer in Salinas, CA. The results were published in a UC Davis ANR blog article and the highlights are summarized here. In the study, the Naio Dino was equipped with finger weeders, a ground driven rubber fingered wheel designed for in-row weeding. Performance was compared to that of a standard cultivator which left an uncultivated band of 4-5 inches around the crop row. Assessments included stand and weed density counts before and after cultivation, hand weeding time and crop head weight. Weed counts were made in a 6 inches wide band centered on the seedline. The robot is equipped with finger weeders, a ground driven rubber fingered wheel designed to remove in-row weeds.
Trial results showed the finger weeder equipped Naio Dino controlled more than 1/3rd of the in-row weeds and reduced hand weeding time by about 2 hours per acre. This result is consistent with our findings in trials conducted in cotton crops where finger weeders controlled about 40% of the in-row weeds. Crop stand and head weight were not significantly reduced as compared to standard cultivation.
Similar results were found with the FarmWise Titan. The automatically controlled paired knife-blade weeding tool generally provided 40-50% in-row weed control and crop stand or yield was not significantly affected. As you might expect, reductions in hand weeding time were highly dependent on weed pressure. When weed density was low (<0.2 weeds/ft2) labor savings were negligible (< 0.1 hours/acre). At moderate weed (1.7 weeds/ft2) and high densities (>7 weeds/ft2), labor savings were more substantial at 1.7 hours/acre and > 7 hours/acre, respectively.
In summary, the trials showed that use of automated weeding machines were effective at controlling in-row weeds, reducing hand weeding time and that crop yield as measured by head weight was not negatively affected. Use of these machines is best suited for fields where weed pressure is high and significant labor savings can be obtained. I want to acknowledge Mosqueda et al. (2021) again for conducting these studies and sharing this information that helps growers make more informative decisions.
References
Mosqueda, E., Smith, R. & Fennimore, S. 2021. 2020 Evaluations of automated weeders in lettuce production. ANR Blogs. Davis, Calif.: University of California Davis. Available at: https://ucanr.edu/blogs/blogcore/postdetail.cfm?postnum=45566.
1Reference to a product or company is for specific information only and does not endorse or recommend that product or company to the exclusion of others that may be suitable.
|
|
||||||||
|
Trial |
Treatment |
Weed |
Weeds |
Weed |
Weed |
Weeding |
Stand |
Head |
|
|
|
(no. ft-2) |
(no. ft-2) |
(%) |
(%) |
(hr acre-1) |
(%) |
(lbs) |
|
Naio Dino |
|
|
|
|
|
|
|
|
|
1 |
Naio |
1.0 |
0.6 |
34.9 |
33.2 |
NA |
0.0 |
1.9 |
|
|
Standard |
1.3 |
1.2 |
1.7 |
|
NA |
0.0 |
2.1 |
|
2 |
Naio |
1.7 |
0.4 |
73.7 |
40.4 |
6.5 |
NA |
1.4 |
|
|
Standard |
2.3 |
1.5 |
33.3 |
|
8.4 |
NA |
1.4 |
|
FarmWise Titan |
|
|
|
|
|
|
|
|
|
1 |
FarmWise |
1.0 |
0.4 |
58.4 |
13.9 |
9.4 |
0.3 |
2.8 |
|
|
Standard |
1.3 |
0.7 |
44.5 |
|
11.1 |
0.0 |
2.8 |
|
2 |
FarmWise |
0.3 |
0.1 |
69.8 |
39.1 |
|
0.3 |
1.4 |
|
|
Standard |
0.4 |
0.2 |
30.7 |
|
|
0.0 |
1.3 |
|
3 |
FarmWise |
0.2 |
0.0 |
85.9 |
42.4 |
3.8 |
0.4 |
2.2 |
|
|
Standard |
0.1 |
0.1 |
43.5 |
|
3.9 |
0.0 |
2.1 |
|
4 |
FarmWise |
3.9 |
0.8 |
80.1 |
47.3 |
9.9 |
4.5 |
1.5 |
|
|
Standard |
3.4 |
2.3 |
32.8 |
|
16.9 |
0.3 |
1.4 |
|
5 |
FarmWise |
3.0 |
0.5 |
81.7 |
47.6 |
6.7 |
2.2 |
1.7 |
|
|
Standard |
3.4 |
2.2 |
34.1 |
|
14.7 |
0.3 |
1.7 |
|
1Data adapted from Mosqueda et al. (2021). |
||||||||
|
2In-row weed control results are estimates calculated from differences between automated and standard cultivator weed control data. |
||||||||
Fig. 1. Naio Technologies Dino autonomous robot equipped with finger weeders. (Photo Credits: Naio Technologies)
Fig. 2. FarmWise Titan autonomous automated weeding machine. (Photo Credits: FarmWise)
In our last newsletter we talked about the importance of proper weed identification before making decisions on control measures. We mentioned some of the literature that the Vegetable IPM Team uses at the Yuma Agricultural Center.
An increasing number of PCAs and growers are using several phone applications for weed ID.
In this update I would like to share some data that was collected from a group of students of the 2024 PLS 300 Applied Weed Science class.
Professor Barry Tickes asked his students to download two phone applications and test the accuracy of the weed species ID. The recommended applications used were PlantNet and PictureThis Plant Identifier, which according to some Pest Control Advisors are reasonably accurate.
We provided a display of 9 weeds to the students to take images and upload to the phone apps for ID and here are the results obtained:
Weed PictureThis PlantNet
Annual bluegrass 6 0
Creeping woodsorrel 8 6
Nettleleaf goosefoot 4 3
Prickly lettuce 8 0
Spiny sowthistle 6 1
Spinach 8 6
Malva 6 1
Silversheath knotweed 5 0
Littleseed canarygrass 0 0
PictureThis Plant Identifier performed better than PlantNet in this evaluation. Interestingly in 2022 the weed science class evaluated PlantNet with results showing that 84.6 % of the time the application was correct. If you have another application that you recommend, please send it in your comments and we will share it with others in this newsletter.
Get your free copy of the Weed Seedling Identification Pocket Guide at the Yuma Agricultural Center.
VegIPM Update Vol. 17, Num. 15
July 22, 2026
Results of trap catches below!!
Whitefly: Adult activity remains steady across locations; above average for this time of the year, especially high numbers seen in North Gila Valley. Historically, whitefly numbers peak in July.
Thrips: Adult thrips activity remained low over the last two weeks. About average for this time of the year. Historically, thrips numbers remain low until Sept-Oct.
