Identifying important stages of crop growth and development (crop phenology) for in-season management and harvest dates is important with melon (Cucumis melo ‘reticulatus’ L.) crop production. To monitor and predict plant development it is best to measure actual thermal conditions in the plant’s environment. Plant growth is a direct response to temperature and environmental conditions. Measuring “thermal time” is a more reliable measure and predictive tool for plant development as opposed to a calendar.
Thus far, 2026 has been an abnormally warm year for Arizona and the desert Southwest. Accordingly, crop development has been accelerated by conventional calendars but closely following the thermal calendars that plants respond to.
Various forms of temperature measurements and units commonly referred to as heat units (HU), growing degree units (GDU), or growing degree days (GDD) have been utilized in numerous studies to predict phenological events for many crop plants (Baskerville and Emin, 1969; Brown, 1989; Baker and Reddy, 2001; and Soto, 2012). A graphical depiction of HU computation using the single sine curve procedure is presented in Figure 1 (Brown, 1989).
A little over twenty-five years ago we began working on the development and testing of a phenology model for desert cantaloupe production for Arizona conditions. The basic cantaloupe phenology model is shown in Figure 2 (Silvertooth, 2003; Soto et al., 2006; and Soto, 2012). Since cantaloupes are a warm season crop, we use the 86/55 ºF thresholds for phenological tracking.
This melon crop phenology model was developed under fully irrigated and well-managed conditions, primarily in the lower Colorado River Valley. That is important since non-irrigated fields are more likely to experience water stress, which significantly disrupts crop development patterns.
Key stages of growth or “guideposts” indicated in Figure 2 represent general average or “target” values that are subject to a slight degree of natural variation, which is normal.
Referring to the data from the Arizona Meteorological Network (AZMET) and several locations in the Yuma area, the HU accumulations (86/55 ºF thresholds) from 1 January 2026 to a set of four possible 2026 planting dates are listed in Table 1. The HU accumulations from 1 January to 1 April 2026 are listed in Table 2.
The HU accumulations after planting (HUAP) for these four possible planting dates for three Yuma area locations to 1 April 2026 are shown in Table 3. The HUAP values in Table 3 are simply the difference between the values in Tables 1 and 2. An example for the Yuma Valley (UA Yuma Ag Center), 15 January 2026 planting date is: HU 1318- 95 HU = 1223 HUAP.
It is rather easy to test and evaluate this crop phenology model in the field under various planting dates, varieties, and conditions. Tracking HUs and reference to this phenology model (Figure 2) can serve as a check for melon crop development in the field. Based on the estimates in Table 3, the earliest planting dates are ready or close to crown fruit harvest and later planting dates are for small golf-ball and slightly large sized melons. Calendar wise, this is rather early but right on track based on seasonal HU accumulations.
Note: Yuma AZMET site is at the University of Arizona Yuma Agricultural Center. The North Gila AZMET site is located west of the Laguna Dam Road near County 3E. The Roll site is located near E. County 8th Street and S. Avenue 35E.References:
Baker, J.T., and V.R. Reddy. 2001. Temperature effects on phenological development and yield of muskmelon. Annals of Botany. 87:605-613.
Baskerville, G.L., and P. Emin. 1969. Rapid estimation of heat accumulation from maximum and minimum temperatures. Ecology 50:514-517.
Brown, P. W. 1989. Heat units. Ariz. Coop. Ext. Bull. 8915. Univ. of Arizona, Tucson, AZ.
Silvertooth, J.C. 2003. Nutrient uptake in irrigated cantaloupes. Annual meeting, ASA-CSSA-SSSA, Denver, CO.
Simonne, A., E. Simonne, R. Boozer, and J. Pitts. 1998. A matter of taste: Consumer preferences studies identify favorite small melon varieties. Highlights of Agricultural Research. 45(2):7-9.
Soto, R. O. 2012. Crop phenology and dry matter accumulation and portioning for irrigated spring cantaloupes in the desert Southwest. Ph.D. Dissertation, Department of Soil, Water and Environmental Science, University of Arizona.
Soto-Ortiz, R., J.C. Silvertooth, and A. Galadima. 2006. Nutrient uptake patterns in irrigated melons (Cucumis melo L.). Annual Meetings, ASA-CSSA-SSSA, Indianapolis, IN.
Table 1. Heat unit accumulations (86/55 ºF thresholds) after 1 January 2026 on four
possible 2026 planting dates utilizing Arizona Meteorological Network (AZMET) data for
each representative site.
Table 2. Heat unit accumulations (86/55 ºF thresholds) after 1 January 2025 on 12 April
2026 utilizing Arizona Meteorological Network (AZMET) data for each representative site
in the Yuma Valley, North Gila Valley, and Roll.
Table 3. Heat unit accumulations (86/55 ºF thresholds) after planting (HUAP) as of 10
April 2026 from four possible 2026 planting dates and three sites in the Yuma area
utilizing Arizona Meteorological Network (AZMET) data for each representative site.
Note: the values in Table 3 are determined by taking the difference between the HUs for each representative site and four planting dates in Tables 1 and 2.
Yuma Valley: https://azmet.arizona.edu/application-areas/heat-units/station-level-summaries/az02
Yuma North Gila: https://azmet.arizona.edu/application-areas/heat-units/station-level-summaries/az14
Roll: https://azmet.arizona.edu/application-areas/heat-units/station-level-summaries/az24
Figure 1. Graphical depiction of heat unit computation using the single sine curve procedure. A sine curve is fit through the daily maximum and minimum temperatures to recreate the daily temperature cycle. The upper and lower temperature thresholds for growth and development are then superimposed on the figure. Mathematical integration is then used to measure the area bounded by the sine cure and the two temperature thresholds (grey area). (Brown, 1989)
Figure 2. Heat Units Accumulated After Planting (HUAP, 86/55 oF)
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 109For those interested in in-row weed control, checkout the quality video below (Fig. 1) on how finger weeders (Fig. 2) are being used on a 3,600 acre organic cotton farm in Texas. The grower states that finger weeders help him achieve 95-97% weed control and are a highly cost-effective tool for lowering hand weeding costs.
Fig. 1. Carl Pepper discusses how finger weeders are used to control in-row weeds on
his 3,600 acre organic cotton farm. Click here or on image to view. (Photo credit: Tilmor
LLC, Dalton, OH)
Fig. 2. Finger weeders, an in-row weeding tool, operating in seedling cotton. Finger
weeder pairs are centered on the seed row and overlapped slightly to loosen soil in the
row and uproot small weeds.
This winter at the Yuma Agricultural Center, we evaluated whether Kerb (pronamide) can be effectively applied through sprinkler irrigation using a custom venturi chemigation unit, rather than a traditional ground sprayer. We also tested whether adding Hydrovant fA improves performance.
This trial was conducted under very heavy Sudan grass pressure and in cloddy seedbed conditions, making it a strong stress test of these programs.
Read the full report HERE
Key Takeaways (14 DAT – Preliminary)
This is a single, unreplicated screening trial. Always follow label directions and consult your PCA before adjusting programs.
Visitors are welcome to walk the plots at YAC.
Figure 1. Early results (14 DAT) show strong goosefoot control with chemigated Kerb
programs.
This trial was made possible through partial funding from the Western IPM Center, with additional support from the University of Arizona Cooperative Extension and industry collaborators. Co-PIs on the project: Macey Keith and Wilfrid Calvin.
Insect pests are constantly adapting to their environment. Over time, they have evolved ways to overcome control tactics. Repeated use of the same insecticides or tactics places strong selection pressure on pest populations. This allows the few individuals that can survive treatments to reproduce, leading to populations that are increasingly difficult to control, a process known as resistance.
Insects can develop resistance in several ways. Some break down insecticides more efficiently or develop changes at the target site that reduce product effectiveness. Others avoid exposure altogether by changing their feeding or movement behavior. In some cases, insects even develop thicker cuticles that slow the absorption of insecticides.
Production practices can influence the rate of resistance development. Large, uniform cropping systems and repeated use of the same control tools reduce opportunities for susceptible insects to persist, accelerating resistance.
Figure 1: Chart illustrating how insecticide resistance develops when
insecticides with the same mode of action (MoA) are used repeatedly
What Should You Do?
An integrated pest management (IPM) approach remains the best defense against resistance.
Key practices include:
Reducing selection pressure is critical. The more intensively a single tactic is used, the faster resistance will develop. A diversified management approach will help extend the life of available tools and improve long-term pest control.
Two weeks ago, we discussed how unusually high maximum and minimum air temperatures in Yuma Valley were likely accelerating crop development and shortening the vegetable production window. Mean relative humidity (RH) provides an additional perspective on this spring’s weather pattern because it affects crops through a different pathway than temperature. While temperature strongly influences crop development rate, respiration, and time to maturity, RH is more closely related to atmospheric drying, crop water relations, canopy microclimate, and some aspects of pest management and spray application conditions.
Mean RH at the AZMET Yuma Valley station from January 1 through March 29, 2026, was more variable than the temperature pattern discussed in the earlier blog (Figure 1). Unlike maximum and minimum air temperature, which showed a clearer and more sustained departure from the 2020–2025 pattern, RH fluctuated more over time. Even so, several periods during March 2026 appear to have had relatively lower RH than the recent historical pattern, including part of the late-March period highlighted in the figure. This distinction is important because lower RH under warm conditions can increase the drying power of the air and contribute to greater atmospheric demand for water.
Figure 1. Mean relative humidity at the AZMET Yuma Valley station from January 1
through March 29, 2026, compared with the 2020–2025 pattern.
This RH pattern should be interpreted differently from the maximum and minimum temperature trends. Higher maximum temperatures can accelerate heat-unit accumulation and move crops more quickly toward maturity. Higher minimum temperatures can increase nighttime respiration and reduce carbon-use efficiency by increasing the fraction of assimilated carbon used for maintenance. Lower RH, in contrast, does not directly speed crop development or increase respiration in the same way. Instead, it can increase evaporative demand and strengthen the gradient that drives water loss from the crop and soil surface. When relatively lower RH occurs during an already warm period, crop water demand may increase further, especially in actively growing fields.
From an agronomic standpoint, this means that RH may add to the stress associated with the temperature pattern rather than duplicate it. In fields where irrigation timing, soil moisture, or root-zone conditions are already marginal, periods of lower RH may increase the likelihood of transient midday stress, reduced leaf turgor, and lower growth efficiency. This does not mean that lower RH alone caused crop stress or yield loss, but it may have increased atmospheric pressure on crops that were already developing under unusually warm conditions. For this reason, RH can help explain why water management may have become more challenging during March.
The RH pattern may also have relevance for IPM. Hot and relatively dry conditions can favor some stress-associated arthropod pests in certain crop systems, particularly when the crop is already under heat or water stress. At the same time, relatively drier air may make conditions less favorable for some moisture-dependent foliar diseases. However, these responses are highly dependent on the crop, pest, pathogen, irrigation method, canopy structure, and leaf wetness duration. Therefore, this figure should not be interpreted as showing a universal increase or decrease in pest or disease pressure. Rather, it suggests that the field environment may have shifted in ways that could influence pest dynamics and disease favorability.
Relative humidity may also matter operationally for crop protection. Under hot and relatively dry conditions, spray droplets can evaporate more rapidly, especially during the warmest part of the day. This can make application conditions less forgiving and may increase the importance of timing and coverage. Again, this does not necessarily mean reduced efficacy, but it does mean that lower RH can add practical challenges to foliar application under already warm spring conditions.
Overall, the mean RH does not replace the temperature story described in the blog from two weeks ago. Instead, it adds another layer to it. The earlier temperature data suggested that crops in Yuma Valley may have been developing more rapidly than normal because of unusually warm days and nights. The RH pattern presented here suggests that, during some periods in March, the atmosphere may also have been relatively drier than normal, potentially increasing evaporative demand and adding to crop water-management and IPM complexity. In that sense, this figure helps explain how the spring environment may have become more demanding even beyond temperature alone.
What this may mean going forward
Going forward, this pattern suggests that unusually warm periods combined with lower RH could increase the risk of faster crop development, higher water demand, and more challenging IPM timing in Yuma Valley. If these conditions become more frequent, growers may need to place even greater emphasis on weather-based irrigation scheduling, close field scouting, and timely management decisions.
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.
