Jun 15, 2022Whiteflies Building Up, Adults on the MoveTo contact John Palumbo go to: jpalumbo@ag.Arizona.edu
Cantaloupes (Cucumis melo L.) or “melons” are one of the important spring and fall vegetable crops of Arizona and the desert Southwest. Technically, “true” cantaloupes are rough, warty fruit, primarily grown in Europe. On a production scale, cantaloupes are not grown commercially in the United States. However, in the United States “cantaloupe” has become a general name of all netted, musk-scented melons (Simmone et al., 1998 and Soto, 2012).
Cantaloupes in the U.S. are divided into eastern and western types. The eastern type is characterized by round-shaped fruits, usually about five to seven pounds, sutured (sutures are the green lines that divide the rind into several sections), with variable levels of netting (netting is the network of cork-like marks that cover the rind), and large seed cavities. The western type is characterized by oval-shaped fruits of three to four pounds, sutureless, and a coarsely netted rind (Simmone et al., 1998 and Soto, 2012).
According to the United States Department of Agriculture (USDA) National Agricultural Statistical Services (NASS), the harvested Arizona cantaloupe acreage from 1992 to 2021 has ranged from 13,200 to 23,300 acres with an estimated production value ranging from $38 million to $82.5M. There were 19,300 acres of Arizona cantaloupes in 2021 (USDA, 2021). Most of the Arizona cantaloupe production takes place in Yuma, Maricopa, and Pinal Counties. Among the nine states with recorded cantaloupe production, Arizona commonly ranks second to California in acres and total production. (USDA, 2021 and Murphree, 2015).
Being able to accurately describe and predict important stages of crop growth and development (crop phenology) and harvest dates is important for improving crop management (e.g. fertilization, irrigation, harvest scheduling, pest management activities, labor and machinery management, etc.). Since plants operate on “thermal time”, they have no regard for calendars or time as we commonly measure it. So, we find it is best to monitor and predict plant development based on the actual thermal conditions in the plant’s environment. 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 (Baker and Reddy, 2001 and Soto, 2012).
Boswell (1929) first documented the concept of heat summations relative to vegetable crop production in 1929. Thereafter, HU accumulation techniques have been successfully applied to numerous vegetable production systems like cantaloupe (Baker et al., 2001).
The use of HU accumulations has been shown to be an efficient technique for modeling and predicting growth stages in crops (such as cantaloupes) as compared with the traditional days after planting (DAP) method, since variations among seasons and locations can be better normalized using heat units accumulated after planting (HUAP) calculations rather than DAP.
For more than 35 years we have had the benefit of excellent weather data collection in Arizona from the Arizona Meteorological Network (AZMET), which was first developed and directed by Dr. Paul Brown. For warm season crops, such as cantaloupes, we have been working HUs with both upper and lower temperature thresholds (86/55 oF), as first described by Baskerville and Emin (1969) and shown in Figure 1 (Brown, 1989). We have successfully developed crop phenology models using HUs with 86/55 oF thresholds for other common warm season crops in the desert Southwest, such as cotton (Silvertooth, 2001) and New Mexico type chiles (Silvertooth et al., 2010).
Baker et al., (2001) developed a muskmelon phenology model that could be run with easily obtainable weather station data and used by growers to quantify phenological development and aid in projecting harvest dates. The average model accuracy in predicting harvest dates ranged between 1 to 3 days for the data set used to construct the model. Also, after the evaluation of the performance of two GDD models to predict commercial harvest dates in 30 commercial melon fields in California, Hartz (2001) found that the two models were useful in predicting the date of harvest initiation. The standard deviation for the prediction of harvest date from emergence date represented between 2-3 days of normal growing-degree-day accumulation.
Beginning in 2000, we began working in Arizona to develop and test a phenology model for desert cantaloupe production. Following data collection from many spring cantaloupe fields, primarily in the Yuma area, we were able to develop and test the basic cantaloupe phenology model shown in Figure 2 (Silvertooth, 2003; Soto et al., 2006; and Soto, 2012).
I encourage those who are working with spring cantaloupe production this season to test and evaluate this crop phenology model in the field under various planting dates, varieties, and conditions. We appreciate your feedback.
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)
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.
Boswell, V. R. 1929. Factors influencing yield and quality of peas. Maryland Agric. Exp. Sta. Bull. 306.
Brown, P. W. 1989. Heat units. Ariz. Coop. Ext. Bull. 8915. Univ. of Arizona, Tucson, AZ.
Hartz, T.K. 2001. Development and testing of a growing degree day model to predict melon harvest time. California Melon Research Board. 2001. Annual Report.
Murphree, J. 2015. Fun Statistics about Arizona Agriculture’s Melons and Sweet Corn. Arizona Farm Bureau https://www.azfb.org/Article/FunStatistics-about-Arizona-Agricultures-Melons-and-Sweet-Corn
Silvertooth, J.C. 2001. Following cotton development over the fruiting cycle. University of Arizona Cooperative Extension Bulletin No. AZ 1206.
Silvertooth, J.C. 2003. Nutrient uptake in irrigated cantaloupes. Annual meeting, ASA-CSSA-SSSA, Denver, CO.
Silvertooth, J.C., P.W. Brown, and S. Walker. 2010. Crop Growth and Development for Irrigated Chile (Capsicum annuum). University of Arizona Cooperative Extension Bulletin No. AZ 1529
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, Indianpolis, IN.
USDA Stats: 2021 State of Agriculture Overview.
This season we have already found few lettuce infected with bacterial soft rot. Though it rarely takes down the whole field, the symptom are not so pleasant. Bacterial soft rot in lettuce can occur in the field as well as post harvest.
It is caused by several types of bacteria, but primarily subspecies and pathovars of Erwinia caro-tovora and E. chrysanthemi. Other bacterial species that cause soft rot include Pseudomonas cichorii, P. marginalis, and P. viridiflava. They have a wide host range host range and includes genera from nearly all plant families
In lettuce fields, the symptoms are observed close to the harvest time. The tissue, mostly around inside the head of head lettuce softens and becomes mushy or watery. Slimy masses of bacteria and cellular debris frequently ooze out from cracks in the tissues. Decaying tissue, which may be opaque, white, cream-colored, gray, brown, or black frequently gives off a characteristically putrid odor. The odor is caused by secondary invading bacteria
that are growing in the decomposing tissues.
The bacteria overwinter in infected fleshy tissues in storage, in the field, garden or greenhouse, in the soil (especially in the rhizosphere around the roots of many plants), and on contaminated tools, equipment, containers, and in certain insects. The bacteria enter primarily through wounds made during planting, cultivating, harvesting, grading, and packing and through freezing injuries, insect and hail wounds, growth cracks, and sunscald. They may
also follow other disease-producing organisms. Uninjured tissues may become infected when the humidity approaches 100 percent or when free moisture is present. Rains, poorly drained or waterlogged soils, and warm temperatures favor infection in the field, as does high humidity in storage or transit.
The bacteria multiply rapidly by dividing in half every 20 to 60 minutes under ideal conditions at
temperatures between 65° and 95° (18° and 35°C). Minimum temperatures for development is between 35° and 46°F (2° and 6°C); and maximum between 95° and 105°F (35° and 41°C.
The bacteria are spread by direct contact, hands, tools and farm machinery, insects, running or splashing water, contaminated, water in washing vats, clothing, and decayed bits of tissue.
Promptly and carefully destroy infected plants. Maintain well aerated field, avoid close planting and overhead irrigation.
To minimize post harvest losses, avoid mechanical injusry after harvest, packing and shipping. Do not pack produce when wet. Store and ship produce at temperatures near 4°C (39°F).
Interested in the latest ag technologies? FIRA USA and a number of other entities are organizing a 3-day event October 18-20 in Freson, CA focused on autonomous ag robotics and technologies. The event includes keynote speakers, break out sessions, a trade show and in-field demos of harvesting, weeding, thinning, and planting robots. The emphasis is on specialty crops so it should be very interesting program. For more information, click here.