May 4, 2022Spider Mites on Spring Melons 2022To 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.
DISEASE: Center Rot of Onion
PATHOGEN: Pantoea ananatis, Pantoea agglomerans, Pantoea alli and Pantoea stewartii subsp. indologenes
HOSTS: Onion (Allium cepa L.), garlic (Allium sativum L.), shallots (Allium cepa var. aggregatum L.), leeks (Allium ampeloprasum L.), chives (Allium schoenoprasum L.).
Symptoms and signs
Center rot of onion has not been a major problem in the desert southwest but when the environment is favorable, the disease can cause up to 90% loss. Foliar symptoms (symptoms on leaves) may start with water-soaked lesions spanning the length of the leaf blade, which gradually become blighted resulting in desiccation and collapse of the tissue. Experiments have shown that the bacteria can move from leaves to the bulbs, thus protecting foliage is important to manage the disease.
The bacteria can overseason to infect onions in a number of different ways. Like many bacterial pathogens, P. ananatis can be seed-borne with infested seed serving as a survival mechanism as well as a means of dissemination. It has been demonstrated that P. ananatis can be both naturally seed-borne and seed-transmitted in onion. The significance of the bacterium's ability to colonize seed is uncertain, as most onion seed production sites are located in arid climates but extremely important to understand to manage the disease.
Although P. ananatis can be seedborne, the proposed primary mode of transmission is by two insect vectors. Two species of thrips, tobacco thrips (Frankliniella fusca (Hinds)) and onion thrips (Thrips tabaci), have the ability to transiently acquire and transmit P. ananatis and P. agglomerans . The bacterium can persist in a non-circulative manner in the gut of thrips for 128 h, allowing the vector to infect plants over an extended period of time.
P. ananatis can survive epiphytically and endophytically on a wide range of hosts. These alternative hosts can serve as a source of inoculum in fields where susceptible crops are grown. In Georgia alone, 25 weed species, including carpetweed (Mollugo verticillata), common ragweed (Ambrosia artemisiifolia), crabgrass (Digitaria sanguinalis), common cocklebur (Xanthium pensylvanicum), curly dock (Rumex crispus), Florida pusley (Richardia scabra), sicklepod (Cassia obtusifolia), stinkweed (Thlaspi arvense), Texas panicum (Panicum texanum), vaseygrass (Paspalum urvillei), wild radish (Brassica spp.), yellow nutsedge (Cyperus esculentus) and other multiple crop plants were found to harbor P. ananatis populations asymptomatically.
Pic Credit: Colton Tew
Onion cultivars resistant to Pantoea sp. are not commercially available. Use of certified onion seeds is encouraged to avoid introduction of Pantoea sp. inoculum in the production field. Planting early maturing or mid-maturing onion varieties are often recommended for growers. Late maturing varieties provide a larger window for infection and a potential epidemic to occur, which are favored by thrips pressure, hot and humid conditions, and lack of effective bactericides. Overhead irrigation should be avoided as it promotes bacterial spread compared with sub-surface or drip-irrigation. Controlling thrips population can be an effective management strategy to reduce center rot incidence as these vectors play an important role in bacterial transmission.
Center rot management in onion fields relies heavily on copper applications mixed with an ethylenebisdithiocarbamate fungicide (EBDC), such as mancozeb, which growers may apply weekly as a protectant. In addition, researchers found P. ananatis strains to be copper-tolerant indicating overuse and potential risk of insensitivity to this chemistry. Repeated applications of copper sprays during susceptible growth stages can be effective only to a limited extent and does not offer a robust solution to the problem. Perhaps the inefficacy of these sprays could be due to thrips preference to colonize certain parts of the onion plant, e.g. the basal meristems (neck region).
The implementation of successful weed management strategies are important in reducing P. ananatis inoculum in the field. By reducing weeds, growers can potentially reduce initial inoculum.
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Beet armyworm: Moth counts remain very low consistent with seasonal temperatures, but below average for this point in the season.
Cabbage looper: Slight increase in activity, but moth counts remain unusually low for late January.
Whitefly: Dult movement is at seasonal low consistent with temperatures and lack of melons or cotton.
Thrips: Activity remains lower than normal for this point late January. Increased movement noted in Roll/Tacna.
Aphids: Seasonal aphid counts peaked during the past 2 weeks, suggesting movement with recent winter storms and lack of desert vegetation. Counts were particularly high in North Yuma and Gila Valleys, and Bard. Above average for this time of year.
Leafminers: Adult activity remains light in most trap locations. Trap counts increasing slightly in the South Gila Valley.