In the last two issues of this UA Vegetable IPM Newsletter, I have presented a melon (Cucumis melo ‘reticulatus’ L.) crop phenology model (Figure 1; Silvertooth, 2025a) based on actual heat unit accumulations (86/55 ºF thresholds). This model can be useful in predicting and tracking crop development and identifying important stages of crop growth and development (crop phenology).
Referring to the data from AZMET for several locations in the Yuma area, the HU accumulations from 1 January 2025 for a set of four possible 2025 planting dates are listed in Table 1. The HU accumulations from 1 January 2025 to 28 April 2025 for these sites are listed in Table 2.
The HU accumulations after planting (HUAP) for these four possible planting dates for three Yuma area locations to 28 April 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: HU from 1 January to 28 April 1096 - 73 HU accumulated at planting on 15 January = 1023 HUAP for this case.
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 1. In the most edition of this newsletter (Silvertooth, 2025b) the projected stages of growth were presented based on this phenological model and current HU accumulations.
Based on this phenology model and current HU accumulations for this season we should be able to make some projections on the current stage of growth, which we can go to the field and check. For example, for melon fields in the lower Colorado River Valley at this time, we can expect to find fields planted and watered up in mid-January to have crown set melons maturing and approaching harvest conditions. These fields could have crown fruit ready for harvesting in about three weeks, based on these projections and normal HU accumulation patterns for this time of year. For fields planted and wet dates near the first of March, these fields should have small crown set melons approaching golf ball size.
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 14
April 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 on 30 April 2025 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. Melon (cantaloupe) phenological development model expressed in Heat Units
Accumulated After Planting (HUAP, 86/55 oF).
I hope you are frolicking in the fields of wildflowers picking the prettiest bugs.
I was scheduled to interview for plant pathologist position at Yuma on October 18, 2019. Few weeks before that date, I emailed Dr. Palumbo asking about the agriculture system in Yuma and what will be expected of me. He sent me every information that one can think of, which at the time I thought oh how nice!
When I started the position here and saw how much he does and how much busy he stays, I was eternally grateful of the time he took to provide me all the information, especially to someone he did not know at all.
Fast forward to first month at my job someone told me that the community wants me to be the Palumbo of Plant Pathology and I remember thinking what a big thing to ask..
He was my next-door mentor, and I would stop by with questions all the time especially after passing of my predecessor Dr. Matheron. Dr. Palumbo was always there to answer any question, gave me that little boost I needed, a little courage to write that email I needed to write, a rigid answer to stand my ground if needed. And not to mention the plant diagnosis. When the submitted samples did not look like a pathogen, taking samples to his office where he would look for insects with his little handheld lenses was one of my favorite times.
I also got to work with him in couple of projects, and he would tell me “call me John”. Uhh no, that was never going to happen.. until my last interaction with him, I would fluster when I talked to him, I would get nervous to have one of my idols listening to ME? Most times, I would forget what I was going to ask but at the same time be incredibly flabbergasted by the fact that I get to work next to this legend of a man, and get his opinions about pest management. Though I really did not like giving talks after him, as honestly, I would have nothing to offer after he has talked. Every time he waved at me in a meeting, I would blush and keep smiling for minutes, and I always knew I will forever be a fangirl..
Until we meet again.
References
Jay-Russell, M.T. (2013). What is the risk from wild animalsin food-borne pathogen contamination of plants?. CABI Reviews 4(8),1-16.https://doi: 10.1079/PAVSNNR20138040
Fig. 1. Bird fecal matter on romaine lettuce.
Fig. 2. Gull flying over romaine lettuce being harvested.
Fig. 3. Gulls flying over irrigation canal near lettuce field
being harvested.
Fig. 4. Bird fecal matter on lettuce harvesting equipment.
We are receiving some summer grass samples for identification. As you know the seedlings look very similar.
PCAs have mentioned, and we can corroborate that some species respond differently to herbicides. As an example, we have seen that Sprangletop (Leptochloa filiformis) is not controlled with selective postemergent herbicides like Fusilade or Poast. We have seen only good results with a high rate of clethodim (Select), and the generics off the same active ingredient. Sandbur is also tolerant to these herbicides.
These two weeds frequently come back from crowns surviving the winter which makes spring preemergence herbicides applied ineffective.
The following are common species of summer annual grass here:
|
echinochloa |
water grass and barnyard grass |
|
leptochloa |
red sprangletop and mexican sprangletop |
|
eriochloa |
southwestern cupgrass and prairie cupgrass |
|
cenchrus |
field sandbur and red sandbur |
|
setaria |
green foxtail and yellow foxtail and |
|
chloris |
feather finger grass and truncate finger grass |
Check out the Summer Annual Grass ID publication which contains pictures and descriptive characteristics of each of these species.
Western Flower thrips is among the most economically important insect pests that infests desert lettuce. Bean thrips started to become a major pest of fall lettuce in the desert over the last decade. Our objective is to determine alternative organic insecticides that can be used as part of an IPM program targeting these pests in leafy vegetable crops.
This fall, at the YAC experimental farm, we evaluated 10 organic insecticides frothier efficacy in suppressing western flower thrips and bean thrips in organic head lettuce. M-Pede, Pyganic, and Aza-Direct were evaluated with Oroboost included in one treatment and Orbit DL included in the other treatment. Thus, we evaluated these aforementioned insecticides in two different treatment entries. The purpose was to understand the performance of these insecticides with Orbit DL or Oroboost as adjuvant. The remaining insecticide treatments had only Oroboost as adjuvant. Both Oroboost and Orbit DL are OMRI approved organic adjuvants.
We expected that several of these bioinsecticides would exhibit some measurable level of thrips suppression. However, our data showed that only Entrust exhibited measurable reduction in immature thrips, western flower thrips, and bean thrips numbers (Fig. 1-3). Gargoil and Pyganic with the Orbit as adjuvant exhibited a slight reduction in western flower thrips adults (Fig. 2). We will continue to evaluate these organic insecticides against the thrips to gather more research-based evidence which will allow us to draw more accurate conclusions and make relevant recommendations.
Figure 1. Mean thrips nymph/plant as affected by organic insecticide application.
DAT=Day After Treatment.
Figure 2. Mean western flower thrips adult/plant as affected by organic insecticide
application. DAT=Day After Treatment.
Figure 3. Mean bean thrips adult/plant as affected by organic insecticide application.
DAT=Day After Treatment.
Organic farming faces two major challenges: weeds, which remain the number one concern, and insect pressures that can severely affect crop quality and yields. Effective strategies for managing weeds and insects are critical, especially as organic production expands. Traditionally, these tasks have been labor-intensive and time-consuming, creating a strong need for innovative solutions that can improve efficiency while maintaining crop standards. With the current momentum for increased AI integration into agriculture supported by both industry and Washington D.C., novel technologies AICropCAM present exciting opportunities for leafy green growers. These high-tech platforms could offer early-stage detection of weeds and insects, helping growers respond more quickly and precisely. Such innovations have the potential to save significant time and labor, particularly across large acreages, while improving overall crop management decisions.
What is AICropCAM, and How Does it Work?
AICropCAM (Figs. 1, 2, & 3) is an advanced edge image processing platform designed to extract plant and canopy features directly from field crops. Its structure includes three key layers:
One of AICropCAM’s biggest advantages is its ability to perform deep learning-based image processing directly in the field. This means it can detect subtle signs of weed emergence or insect damage in real-time, capturing critical information that traditional imaging or simple sensors often miss. Edge computing also significantly reduces the need for high-bandwidth data transmission, a major limitation in rural agricultural areas.
Looking Ahead
Incorporating AICropCAM into leafy green production systems could help growers proactively manage weeds and insect pressures, optimize resource use, reduce chemical interventions (especially important in organic systems), and save time and labor. These technologies offer a glimpse into the future of precision agriculture, where early detection and informed decision-making can significantly boost sustainability and profitability.
Figure 1 (left): AICropCAM-insect detection, Figure 2 (middle): AICropCAM-weed
detection, Figure 3 (right): AICropCAM-installed in the field.
