In two recent editions of this publication, I have described the work of Dr. Norman E. Borlaug and colleagues at the International Maize and Wheat Improvement Center (CIMMYT) and what is commonly referred to as the Green Revolution. I have also addressed
some of the criticisms and allegations that Borlaug’s work created environmental problems and what is often referred to as the Blue Revolution.
The basic framework of my argument is strongly supported by classical agronomy, crop physiology, and ecology. While different authors may organize the concepts somewhat differently, the combination of solar radiation, water, nutrients, and genetics are
the principal determinants of crop productivity. There is a strong foundation in relevant literature regarding this understanding of soil-plant-water relations.
The basic framework of limiting factors as I have previously presented in simplified form is consistent with classical agronomy, crop and soil science. Where crop productivity depends on these first four limiting factors:
The following references are among the most authoritative sources supporting this framework.
1. Monteith's Framework: Radiation Interception and Conversion Efficiency
Perhaps the most influential quantitative framework was developed by John Lennox Monteith. Monteith demonstrated that crop biomass production can be described as a function of:
This work established solar energy capture as the fundamental driver of crop productivity.
Key reference
Monteith J.L. 1977. Climate and the efficiency of crop production in Britain. Philosophical Transactions of the Royal Society of London B. 281:277–294.
2. de Wit and Yield Potential Theory
Cornelis de Wit developed the concept of potential production, water-limited production, and nutrient-limited production. His framework remains foundational in crop modeling, soil fertility,
and other agronomic applications.
de Wit made the following distinctions:
This closely parallels the hierarchy of limiting factors as I have presented them.
Key reference
de Wit C.T. 1958. Transpiration and Crop Yields. Wageningen, The Netherlands: Institute of Biological and Chemical Research on Field Crops and Herbage.
3. Classical Crop Physiology
The textbooks of Donald N. Moss, Paul J. Kramer, and later Robert M. Peet each emphasize that crop growth depends fundamentally on:
These texts describe genetics as determining the plant's capacity to utilize resources and partition biomass into economic yield.
4. Sinclair and Muchow
Thomas R. Sinclair and colleagues developed influential analyses showing that crop yield is fundamentally constrained by:
Plant genetics determines how efficiently those resources are converted into harvestable yield.
Key reference
Sinclair T.R., R.C. Muchow. 1999. Radiation use efficiency. Advances in Agronomy. 65:215265.
5. Cassman and Yield Potential Analysis
Kenneth G. Cassman formalized modern yield-gap analysis. His work identifies three yield levels:
Ken Cassman and his colleagues have done a nice job outlining how genetics establishes yield potential, while water and nutrients determine how much of that potential can be realized.
Key reference
Cassman, K.G. 1999. Ecological intensification of cereal production systems: Yield potential, soil quality, and precision agriculture. Proceedings of the National Academy of Sciences. 96:5952–5959.
Lobell, D.B., K.G. Cassman, and C.B. Field. 2009. Crop yield gaps: Their importance, magnitudes, and causes. Annu. Rev. Environ. Resour. 34:179–204.
6. Evans' Comprehensive Treatment
A particularly strong source supporting my overall interpretation is the work of Lloyd T. Evans. Evans argued that crop productivity results from interactions among:
Much of the twentieth century's yield growth arose from genetic improvements that allowed crops to make more effective use of available resources. The CIMMYT program directed by Dr. Borlaug is a great example of this.
Key reference
Evans, L.T. 1993. Crop Evolution, Adaptation and Yield. Cambridge, UK: Cambridge University Press.
A concise summary of the classical agronomic view holds that crop productivity is determined by the capture of solar energy through photosynthesis, constrained by the availability of water and essential nutrients, and ultimately expressed through the
genetic capacity of the crop to convert acquired resources into economically useful yield (Lobell et al., 2009).
This is consistent with the work of de Wit, Monteith, Evans, Sinclair, Cassman, and many other leading crop physiologists and agronomists. It also provides a strong scientific basis for the earlier argument regarding the Green Revolution: the principal innovation was genetic improvement, while irrigation and fertilization functioned primarily to remove environmental constraints and support more complete expression of genetic yield potential.
References
Cassman, K.G. 1999. Ecological intensification of cereal production systems: Yield potential, soil quality, and precision agriculture. Proc. Natl. Acad. Sci. USA 96:5952–5959.
de Wit, C.T. 1958. Transpiration and crop yields. Wageningen, The Netherlands: Institute of Biological and Chemical Research on Field Crops and Herbage.
Evans, L.T. 1993. Crop evolution, adaptation and yield. Cambridge (UK): Cambridge Univ. Press.
Lobell, D.B., K.G. Cassman, and C.B. Field. 2009. Crop yield gaps: Their importance, magnitudes, and causes. Annu. Rev. Environ. Resour. 34:179–204.
Monteith, J.L. 1977. Climate and the efficiency of crop production in Britain. Philos. Trans. R. Soc. Lond. B Biol. Sci. 281:277–294.
Sinclair, T.R. and R.C. Muchow. 1999. Radiation use efficiency. Adv. Agron. 65:215–265
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 109It is with mixed emotions that I write to inform you that this will be my last University of Arizona Vegetable IPM Update. The reason – I am retiring. Thank you for your support over the years. It’s been an honor and a privilege working with you and serving this ag community.
Figure 1. Automated Thinning & Weeding Technologies Field Day.
(Photo credits: Rosa Bevington)
Source: https://en.wikipedia.org/wiki/Spergularia_marina#/media/File:Starr_0806015237_Spergularia_marina.jpg
Recent reports from neighboring Imperial Valley, California indicate that Spergularia marina (sandspurry or saltmarsh sandspurry) is becoming an increasingly serious weed problem in alfalfa production. The species is well adapted to saline and alkaline conditions and can form dense, lowgrowing mats that persist beneath the alfalfa canopy. Given the similarities in climate, irrigation practices, and crop production systems between Imperial Valley and the Yuma area, we are interested in learning whether Arizona alfalfa growers are seeing this weed in their fields.
What Does Sandspurry Look Like?
Sandspurry is a low-growing, branching plant with narrow, fleshy leaves that can form dense mats in open areas. It is often associated with saline or poorly drained soils but may also be established
in irrigated agricultural fields. Early detection is important because small infestations can spread rapidly if left unmanaged.
Potential concerns for alfalfa production include:
In Imperial Valley, growers and crop advisors have reported increasing infestations and growing concerns about long-term management. While we do not yet know the extent of the problem in our local farms, early detection is important.
A Major Challenge: Limited Herbicide Options
One of the reasons sandspurry is attracting attention is the apparent lack of clearly effective, registered postemergence herbicide options specifically targeting this weed in established
alfalfa systems. As a result, management may rely heavily on:
We are particularly interested in hearing whether any currently registered alfalfa herbicides have provided acceptable suppression or control under the desert conditions.
We Need Your Input
If you grow alfalfa in Yuma County or elsewhere in southwestern Arizona, please let us know:
Why This Information Matters
Identifying new and emerging weed threats before they become widespread is a critical component of Integrated Pest Management (IPM). Information from you can help us determine:
Contact Us If you have seen sandspurry in your fields or have experience managing it, please share your observations. Photographs, field histories, and management experiences are especially valuable.
Your feedback will help us better understand the status of this weed in Arizona and develop practical recommendations for growers.
Integrated Pest Management (IPM) combines multiple compatible tactics to manage pests effectively and sustainably. Originally developed by entomologists in the 1950s and 1960s, IPM is now widely adopted by pest managers to address a range of pests, including
insects, weeds, and plant diseases. Most IPM tactics are compatible with both conventional and organic production systems.
In most production systems, no single management tactic provides complete or long-lasting pest control. The greatest success comes from combining multiple complementary tactics, resulting in more effective and sustainable pest management. This concept is often described as the “many little hammers” approach—each management tactic acts as a small hammer against the pest population, and together they provide meaningful suppression.
When developing an IPM program, it is important to prioritize planting resistant or tolerant crop varieties and adopt production practices that promote plant health and resilience. Additional strategies, such as physical, mechanical, and biological controls, can further reduce pest populations. Regular scouting is essential for monitoring pest levels, and economic thresholds can help guide decisions about when control actions may be necessary.
Figure 1. Illustration of common IPM tactics used in organic vegetable production.
IPM tactics commonly used in organic crop production
Organic crop production relies heavily on preventative and ecological pest management strategies. The following IPM tactics are commonly used in organic systems.
Resistant varieties
When available, resistant or tolerant crop varieties should serve as the first line of defense against pests. These varieties can reduce pest damage, lower production costs, and minimize environmental impacts associated with insecticide use.
Cultural control
Cultural practices modify the production environment, making it less favorable to pests. Examples include crop rotation, adjusting planting dates (early or late planting), selecting early-maturing varieties, and implementing systems such as trap cropping or push–pull strategies. These practices can reduce pest pressure and help protect crops from damaging infestations.
Scouting
Regular, timely scouting—at least once or twice per week during active crop growth—helps pest managers detect pest infestations early. Effective scouting helps ensure that control actions are taken only when necessary and prevents unnecessary pesticide applications.
Economic thresholds
The pest population or crop injury level at which control measures should be implemented to prevent economic loss. Used together with scouting, thresholds help determine when management actions are justified and can reduce unnecessary insecticide applications. This approach also helps mitigate the development of insecticide resistance.
Physical and mechanical control
Physical and mechanical tactics include installing physical barriers, tillage, and field sanitation. Removing volunteer plants and alternative hosts can reduce pest reservoirs. Tillage can also help suppress soil-dwelling pests by burying them, killing them directly, or exposing the pests to predators and environmental stresses.
Biological control
Biological control relies on natural enemies that attack pests. Important beneficial organisms include predators such as spiders, lady beetles, syrphid fly larvae, big-eyed bugs, minute pirate bugs, and lacewing larvae, as well as parasitoids such as parasitic wasps and flies. In desert vegetable systems, flowering field margins can help conserve natural enemies, such as lacewings, lady beetles, syrphid flies, and parasitoid wasps, which suppress aphid and other pest populations.
Bioinsecticides
Bioinsecticides are products derived from natural sources such as botanical extracts, fungi, bacteria, or viruses. These products can provide effective pest suppression while remaining compatible with organic production. Common examples include bacterial products such as Bt (Dipel, XenTari, Agree) and spinosad (Entrust, Seduce); botanical products such as pyrethrins and azadirachtin (Pyganic, Neem-based products); and fungal products such as Beauveria bassiana (BotaniGard).
Conclusion
Successful pest management requires combining multiple tactics rather than relying on a single solution. By integrating resistant varieties, cultural practices, scouting, biological control, and bioinsecticides, growers and PCAs can develop effective pest management programs that support both crop productivity and environmental sustainability.
Heat and humidity are one number: VPD
Growers watch temperature and humidity separately, but the crop responds to their combined effect, captured in a single term: vapor pressure deficit (VPD), the difference between the moisture the air can hold when saturated and the moisture actually present (Mohammed, 2026). VPD is the atmosphere's demand for water. Two days at the same temperature place very different loads on a crop if humidity differs, which is exactly what the monsoon delivers.
What 20 days of AZMET data show
Daily records from the Yuma Valley AZMET station (July 1–20, 2026) make the pattern concrete. Three days frame the whole period (Table 1):
Table 1. Three representative days from July 1–20, 2026, Yuma Valley AZMET station.
Maximum air temperature remained punishingly high all month, while dew point climbed from the mid-40s to the mid-60s as monsoon moisture arrived after about July 8 (Figure 1). Measured VPD peaked at 4.77 kPa on July 5, a bone-dry day with an RH minimum of 11%, and bottomed at 3.21 kPa on the humid, cloudy July 16 (Figure 2). Daily reference ET (ETo) ranged from 0.22 in on July 16 to 0.39 in on July 10, about a 75% swing with no matching swing in air temperature (Figure 3).
Figure 1 (heat and humidity). Maximum air temperature remained punishingly high all month, while dew point climbed from the mid-40s to the mid-60s as monsoon moisture arrived after about July 8. The narrowing gap between the two lines is the falling atmospheric demand.
Figure 2 (VPD). Measured VPD peaked at 4.77 kPa on July 5 — a bone-dry day with an RH minimum of 11% and bottomed at 3.21 kPa on the humid, cloudy July 16. Summer VPD in Yuma routinely reaches or exceeds 4 kPa, making it among the most demanding cropping conditions in North America.
Figure 3 (crop water demand). Daily reference ET (ETo) ranged from 0.22 in on July 16 to 0.39 in on July 10, about a 75% swing with no matching swing in air temperature. Over the full period, cumulative ETo was about 6.0 in, averaging 0.30 in/day.
The key insight is in Figure 3: crop water use follows solar radiation, VPD, and wind, not the thermometer. July 16 recorded the lowest demand of the period despite being classic "heat and humidity" weather, because monsoon cloud cover cut solar radiation to about a third of the clearday value. The highest demand, July 10, was not the hottest day; it was a windy day (mean 7.4 mph, gusts to 27) under full sun.
What it means for the crop
The stress was not uniform across the month. Early July (roughly the 4th through the 9th) was the hard stretch, with VPD above 4.2 kPa under clear skies (Figure 2), the conditions that force midday stomatal closure and throttle photosynthesis when roots cannot resupply. Sudan grass, a C4 summer grass, tolerates this better than a C3 vegetable would, but even it trades growth for water conservation at those levels. After the monsoon moisture surged in, that daytime pull eased, but overnight lows of 84–88°F (July 10–20) raise night respiration, so some of the carbon fixed by day is burned off at night. Expect the strongest daytime growth limitation early in the month and a night-respiration drag late.
What it means for irrigation
This is where the data pays off most directly. A fixed summer irrigation set would have overapplied on July 16, when true demand fell nearly by half under cloud, and under-applied on July 10, when wind and full sun pushed demand to the period high (Figure 3). Scheduling to daily ETo or a three-day running ETo to smooth storm-day noise rather than to a calendar rate is the single highest-value adjustment, and it carries straight into fall stand establishment.
What it means for IPM
The monsoon shift can change pest and disease risk. Hot, dry weather mainly stresses the crop, while humid nights can favor some diseases. After July 10, higher humidity and warm nights likely made scouting more important, especially in weak or uneven areas of the field. VPD does not predict pests by itself, but it helps show when the field environment is changing. In Yuma, tracking heat, humidity, and crop condition together can help growers time scouting and management decisions more effectively.
VegIPM Update Vol. 17, Num. 12
June 10, 2026
Results of sticky trap catches below!!
Whitefly: Adult activity has increased significantly across locations; above average for this time of the year. Historically, whitefly numbers peak in July.
Thrips: Adult thrips activity remained steady over the last two weeks. About average for this time of the year. Historically, thrips numbers remain low until Sept-Oct.
