With the produce season winding down, now is a good time to review the insecticide chemistries that are commonly used on desert crops to control insect pests. This is important because to sustain the insecticide efficacy that annually provides growers with cost-effective crop protection requires a conscious effort to prevent insecticide resistance. Over the past 20 years, the Agrochemical Industry has developed and brought to the market an unprecedented number of new chemistries. However, the development of new chemistries appears to be decreasing considerably, and older chemistries are continually being phased out of the marketplace (don't forget, endosulfan will be gone in 2013). Thus, it is imperative to sustain the efficacy of the newer IPM tools currently available, and makes insecticide resistance management (IRM) more important than ever. The most fundamental approach to IRM is to minimize the selection of resistance to any one type of insecticide. Historically, alternating or rotating compounds with different modes of action has provided sustainable and effective IRM in our desert cropping systems. The Insecticide Resistance Action Committee (IRAC), a coordinated crop protection industry group, was formed to develop guidelines to delay or prevent resistance. Using their most recent MOA grouping brochure, we have produced a table which provides the modes of action for the insecticide chemistries commonly used on desert crops (see: Insecticide Modes of Action on Desert Vegetables). We also provide general information on the routes of activity and pest spectrums for each chemistry. These classification lists will provide you with an additional set of guidelines to the selection of insecticides that can be used in desert IPM programs.

Being able to accurately track crop development and then to describe and predict important stages of crop growth and development (crop phenology) and harvest dates is important for improving melon (Cucumis melo ‘reticulatus’ L.) crop management (e.g. fertilization, irrigation, harvest scheduling, pest management activities, labor, and machinery management, etc.). It is best to monitor and predict plant development based on the actual thermal conditions in the plant’s environment. Thermal conditions are a more reliable measure and predictive tool for plant development as opposed to a calendar, simply because plant growth is a direct response to temperature and environmental conditions.

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).

Twenty-five years ago we began working on the development and annual 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. 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.

Referencing 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 2025 to a set off our possible 2025 planting dates are listed in Table 1. The HU accumulations from 1 January 2025 to 30 March 2025 are listed in Table 2.

The HU accumulations after planting (HUAP) for these four possible planting dates for three Yuma area locations to 30 March 2025 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, 15 January 2025 planting date is: 718.7 HU - 73.1 HU = 645.6 ~ 646 HUAP.

It is rather easy to test and evaluate this crop phenology model in the field under various planting dates, varieties, and conditions. The information in Table 3 can help serve as a reference to check for melon crop development in the field against this phenological model in Figure 2.

For melon crops in the lower Colorado River Valley, we would currently expect to find fields planted and watered up in mid-January to have small melons approaching golf-ball size and fields planted in early March should be starting to show fresh blooms soon.

Table 1. Heat unit accumulations (86/55 ºF thresholds) after 1 January 2025 on four possible 2025 planting dates utilizing Arizona Meteorological Network (AZMET) data for each representative site.

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

Table 2. Heat unit accumulations (86/55 ºF thresholds) after 1 January 2025 to 30 March 2025 utilizing Arizona Meteorological Network (AZMET) data for each representative site.

Table 3. Heat unit accumulations (86/55 ºF thresholds) after planting (HUAP) from four possible 2025 planting dates and three sites in the Yuma area utilizing Arizona Meteorological Network (AZMET) data for each representative site. Each value is rounded to the next whole number. 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.

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 super imposed 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 °F)

This study was conducted at the Yuma Valley Agricultural Center. The soil was a silty clay loam (7-56-37 sand-silt-clay, pH 7.2, O.M. 0.7%). Lettuce was seeded, then sprinkler-irrigated to germinate seed on Nov 28, 2023 on double rows 12 in. apart on beds with 42 in. between bed centers.  All other water was supplied by furrow irrigation or rainfall. Treatments were replicated five times in a randomized complete block design. Each replicate plot consisted of 25 ft of bed, which contained two 25 ft rows of lettuce. Plants were thinned Jan 17, 2024  at the 3-4 leaf stage to a 12-inch spacing. Treatment beds were separated by single nontreated beds. Treatments were applied with a tractor-mounted boom sprayer that delivered 50 gal/acre at 100 psi to flat-fan nozzles spaced 12 in apart.

Month	Max Temp (°F)	Min Temp (°F)	Average Temp (°F)	Rainfall
November	80	51	65	0.08 in
December	71	44	57	0.82 in
January	68	42	54	1.14 in
February	73	47	59	0.50 in

 
Powdery mildew (caused by Golovinomyces cichoracearum) efficacy trial treatments were made on February 15,2024, February 23, 2024, March 4, 2024, and March 12, 2024and .Disease was first seen on February  26,2024. Disease rating was done on March 15, 2024.   Disease severity was determined  by rating 10 plants within each of the four replicate plots per treatment using the following rating system: 0 = no powdery mildew present; 0.5 = one to a few very small powdery mildew colonies on bottom leaves; 1 = powdery mildew present on bottom leaves of plant; 2 = powdery mildew present on bottom leaves and lower wrapper leaves; 3 = powdery mildew present on bottom leaves and all wrapper leaves; 4 = powdery mildew present on bottom leaves, wrapper leaves, and cap leaf; 5 = powdery mildew present on entire plant. These ratings were transformed to percentage of leaves infected values before being statistically analyzed. Yield loss due to rejected lettuce heads would likely begin to occur on plants with a powdery mildew rating above 2.0 (percentage of leaves infected value of 40).         
The data in the table illustrate the degree of disease control obtained by application of the various treatments in this trial. Most treatments significantly reduced the final severity of powdery mildew compared to nontreated plants. The most effective fungicides were Rhyme, Merivon, Quintec, Cevya, Luna Sensation, Luna Experience, and Elisys. 

Founded in 2016, FarmWise has been at the forefront of AI based weeding technologies for nearly a decade. Over this time, the company has raised over $65 million in capital. In 2023, the company launched their flagship machine, Vulcan - a 21’ wide automated in-row smart cultivator for vegetable crops, priced at $645,000 (Fig. 1). In a surprising announcement just two weeks ago, FarmWise stated that the company was going through a business restructuring and will cease operations in the coming weeks. The bottom line for the decision was that despite having a field-tested automated weeding machine that reduces hand weeding labor costs, the company has not been able to reach profitability with the resources on hand. Moving forward, the company says that they are actively pursuing strategic opportunities including acquisition, partnerships and technology transfer to ensure the Vulcan technology lives on. During the transition, their number one priority is supporting current customers.

For insightful details on the need for restructuring and FarmWise’s plans going forward, you can refer to articles from The Packer and AgFunderNews.

Fig. 1. FarmWise’s automated in-row smart cultivator, the Vulcan, operating in Salinas,
CA. (Photo credit: FarmWise, Santa Clara, CA)

Reference 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

Thank You

In 2010 we started publishing the Arizona Vegetable IPM Updates to a small number of friends. It was embraced by the community because of contributions from Mike Matheron, John Palumbo and Barry Tickes in the Plant Pathology, Entomology and Weed Science areas. Mike, John and Barry are the original IPM dudes. 

I was honored to be part of the team editing and sending the Newsletter for almost
16 years. 


This is my last update, and I would like to thank the UA team and the agricultural community for the opportunity to work with you. 

Biological control is an important IPM tool globally. This pest suppression technique is especially important for managing pests in organic crop production. There are various biological control techniques, including conservation biological control, classical biological control, and augmentative biological control. Conservation biological control is the practice of providing habitat to support abundant populations of naturally occurring arthropods that attack crop pests. However, classical biological control and augmentative biological control involve the release of arthropod predators and parasitoids, usually non-native, into the field or greenhouses. This article focuses on conservation biological control.

The contribution of native beneficial insects to pest control has been estimated to be approximately $4.5 billion annually in the United States alone. However, the benefits of beneficial insects areoften overlooked. Research conducted across the country has shown evidence that conserving natural habitats leads to an increase in beneficial arthropod populations and a reduction in pest problems on farms. Beneficial arthropod predators and parasitoids often rely on natural or semi-natural areas adjacent to the field for their persistence. Between growing seasons, these natural and semi-natural areas provide alternative food sources, overwintering, and nesting habitats for natural enemies, thereby promoting their populations. To complete their life cycle, natural enemies require more than just prey or hosts; they also need refuge sites and alternative food sources.

Neighboring natural and semi-natural habitats serve as sources of natural enemies during the growing seasons to suppress crop pests. The establishment of wildflower margins around crop fields increases the abundance of beneficial insects that search for pollen and nectar. For example, many adult parasitoids sustain themselves with pollen and nectar from nearby flowering plants while searching for hosts. Most natural enemies do not disperse far from their overwintering sites; access to permanent habitat near or within the field gives them a jump-start on early pest populations.

Farms with diverse and dense populations of natural enemies are likely to exhibit the following characteristics:

- Have small fields surrounded by natural vegetation.
- Composed of diversified cropping systems and plant populations in or around fields include perennials and flowering plants.
- Crops are managed organically or with minimal agrichemicals.
- Soils are high in organic matter and biological activity and, during the off-season, covered with mulch or vegetation.

Figure 1. Syrphid fly feeding from sweet alyssum flowers.


Figure 2. Mix flowers planted on strips between rows of celery to provide food and
shelter for natural enemies.

Estimation of evapotranspiration for specific crops (ETc) is important for irrigation scheduling and agricultural water management. ETc for crops such can be estimated using the following equation:

ETc = ETo x Kc

Where ETo is the evapotranspiration (ET) of a reference crop (usually grass or alfalfa), which is commonly called reference ET Reference ET (ETo) is defined as the ET from a 3-6" tall cool season grass that completely covers the ground and is supplied with adequate water. ETo is commonly used mostly in the eastern, southern, southeastern, and western U.S.

Reference ET (ETr) assumes a reference surface of tall grass (or alfalfa-20" tall) that completely covers the ground and is supplied with adequate water. ETr is more commonly used in the Midwest.

Both ETc and ETo can be expressed in units of water depth per unit of time, such as inches per day, inches per week, or inches per month. ETo is usually estimated using equations that use weather variables as inputs. These variables include solar radiation, air temperature, wind speed, and relative humidity. Reference ET or ETo can be obtained from AZMET Weather Data (https://cales.arizona.edu/AZMET/az-data.htm) 

Figure 1: The Arizona Meteorological Network

The Kc is an adjustment factor called the “crop coefficient,” which mainly depends on the type of crop and its growth stage. Usually determined experimentally. Each agronomic crop has specific crop coefficients to predict water use rates at different growth stages and could be obtained from university extension or agricultural research center.

Example 1:
A lettuce crop is at the KcD growth stage, with a crop coefficient (Kc) of 0.80 (as indicated in the Kc table). The reference evapotranspiration (ETo) from October 20 to 24 is 1.20 inches over a 7-day period since the last irrigation, based on AZMET data. Determine the actual crop evapotranspiration (ETc), which also represents the total irrigation requirement, assuming the irrigation system operates at 100% efficiency.

 

Solution:

ETc=ETo *Kc
Kc @ KcD is 0.80
ETo = 1.20 inches
ETc: 1.20 inches * 0.80
= 0.96 inches is actual crop water use which is total irrigation requirement that needs to apply.

Results of pheromone and sticky trap catches can be viewed here.
Area wide Insect Trapping Network   VegIPM Update, Vol. 12, No. 24, Dec 1, 2021.
 
Results of pheromone and sticky trap catches can be viewed here.
 
Corn earworm:             
CEW moth counts remained low over the past 2 weeks across all locations and about average for this time of the season. 
 
Beet armyworm:          
Trap counts decreased in most locations, and well below average for late-November. Most activity in Yuma Valley.
 
Cabbage looper:          
Cabbage looper trap counts remained low in most areas but increased in the Yuma Valley. Activity below average for late November.
 
Diamondback moth:     
Adults peaked in Bard, Gila and Yuma Valleys and slightly above average for this time of year. Traps located adjacent to cauliflower seed crops had the highest trap captures 
 
Whitefly:                      
Adults remains active in Dome Valley and Roll consistent with melon crops completing harvest, but below average movement for this time of season. 
 
Thrips:                          
Thrips adult movement decreased in most locations last week, and most active in Dome Valley, Wellton, and Tacna. Activity about average for mid-November.
 
Aphids:                         
Aphid movement peaked so far this season with highest activity in Dome Valley, Bard, N. Yuma Valley and N. Gila Valleys over the past 2 weeks. Activity average for this time of year.
 
Leafminers:                  
Adult activity increased sharply in the Dome, Yuma, and Gila Valleys, about average for this time of season.