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)
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.
The Desert Difference: A Showcase of Ag Tech Opportunities for Growing in the Desert begins TODAY Wednesday, November 13th with a Field Demo Day at the Yuma Agricultural Center. The educational workshop will feature 13 of the latest automated and robotic technologies for pest control and improved vegetable production being demonstrated in the field. Registration begins at 7:00 am and the program starts at 7:30 am (agenda below).
The Field Demo Day is part of at wo-day event. The second day will be a standard conference with keynote speakers, breakout sessions and trade booths. The event will be held Thursday, November 14th at the Yuma Civic Center. Details of the event and Conference Day (Day 2) activities can be found here.
Looking forward to seeing everyone at both events!
Fig. 1. Field Demo Day agenda (Day 1) for The Desert Difference: A Showcase of Ag
Tech Opportunities for Growing in the Desert event. More information about the event
and Conference Day activities (Day 2) can be found here.
Today, the EPA posted in the Federal Register an Emergency Order suspending the Registrations of All Pesticide Products Containing Dimethyl Tetrachloroterephthalate (DCPA). We will include the link to the official document at the end of the article.
The notice says in the II. Emergency Order paragraph the following:
“Effective immediately, no person in any state may distribute, sell, offer for sale, hold for sale, ship, deliver for shipment, or receive and (having so received) deliver or offer to deliver to any person any pesticide product containing DCPA. Additionally, in accordance with FIFRA section 6(a)(1), EPA has elected not to permit the continued use of existing stocks, consistent with its policies applicable to cancellations where the Agency has identified significant risk concerns. See 56 FR 29362, 29367, June 26, 1991 (FRL-3845-4)”.
Also, the same paragraph in the document states clearly: “Accordingly, this Emergency Order expressly prohibits any person from using any pesticide product containing DCPA for any purpose. However, EPA will allow continued distribution of existing stocks of DCPA for the express purpose of returning any DCPA product to the registrant of such products”.
You can find and download the document posted in the journal today following this link:
https://live-azs-vegetableipmupdates.pantheonsite.io/sites/default/files/2024-08/240807_EPA_DCPA_ORDER_2024-17431.pdf
References:
We have conducted a field efficacy trial evaluating the efficacy of 14 biological insecticides alone or as a tank mix against lepidopteran pests, including diamondback moth (DBM), beet armyworm(BAW), and cabbage looper (CL). The insect pressures were relatively low when we initiated the insecticide applications; the CL number was never high enough to be considered for statistical analysis and treatment comparisons.
We applied all insecticides at the highest label rate when sprayed alone or at mid-rate when sprayed as a mixture of two insecticides using an application volume of 40 gal/ac. The adjuvant, Oroboost, was added to each of the insecticide treatments at a rate of 0.4% v/v. Most of the insecticides evaluated in our trial are registered for lepidopteran control except for M-Pede, BotaniGard, and PFR-97.
The results of our trial showed that Xentari, Xentari + Pyganic, and Entrust provided the highest level of BAW suppression. We also found that other insecticides/mixes, including Aza-Direct, Dipel, Dipel +Pyganic, Gargoil, Grandevo, Venerate, M-Pede, and PFR-97, may also cause some levels of BAW suppression (Figure 1A). Xentari and Dipel + Pyganic provided the best DBM suppression, followed by Xentari + Pyganic, Dipel, and Entrust, which provided 50-60% of DBM suppression (Figure 1B). Pyganic alone did not control either BAW or DBM (Figure 1A&B).
Table 1. List of bioinsecticides evaluated
Figure 1. Means Beet armyworm larvae (A) and Diamondback moth (B) per cabbage plant as affected by bioinsecticide sprays.
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.
