May 4, 2022Spider Mites on Spring Melons 2022To contact John Palumbo go to: jpalumbo@ag.Arizona.edu
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.
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.
Fusarium wilt of watermelon, caused by Fusarium oxysporum f. sp. niveum, is one of the oldest described Fusarium wilt diseases and the most economically important disease of watermelon worldwide. It occurs on every continent except Antarctica and new races of the pathogen continue to impact production in many areas around the world. Long-term survival of the pathogen in the soil and the evolution of new races make management of Fusarium wilt difficult.
This year we have a lot of watermelon fields infected with Fusarium from Winterhaven to Yuma, Wellton, and Mohawk Valley. Rain, and overwatering of fields when plants set fruits might have contributed to the disease development.
Symptoms of Fusarium can sometimes be confused with water deficiency, even though there is plenty of water in the field. In Yuma valley we have seen fusarium problem in some overwatered fields.
Initial symptoms often include a dull, gray green appearance of leaves that precedes a loss of turgor pressure and wilting. Wilting is followed by a yellowing of the leaves and finally necrosis. The wilting generally starts with the older leaves and progresses to the younger foliage. Under conditions of high inoculum density or a very susceptible host, the entire plant may wilt and die within a short time. Affected plants that do not die are often stunted and have considerably reduced yields. Under high inoculum pressure, seedlings may damp off as they emerge from the soil.
Initial infection of seedlings usually occurs from chlamydospores (resting structure) that have overwintered in the soil. Chlamydospores germinate and produce infection hyphae that penetrate the root cortex, often where the lateral roots emerge. Infection may be enhanced by wounds or damage to the roots. The fungus colonizes the root cortex and soon invades the xylem tissue, where it produces more mycelia and microconidia. Consequently, the fungus becomes systemic and often can be isolated from tissue well away from the roots. The vascular damage we see in the roots is the defense mechanism of the plant to impede the movement of pathogen.
Disease management include planting clean seeds/transplants, use of resistant cultivars, crop rotation, soil fumigation, soil solarization, grafting, biological control. An integrated approach utilizing two or more methods is required for successful disease management.
Corn earworm: First significant CEW moth activity since mid-November; particularly active in Dome/Wellton/Tacna areas.
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 this time of season.
Whitefly: Adult movement is at seasonal low consistent with temperatures and lack of melons or cotton.
Thrips: Thrips activity beginning to pick up, particularly in Tacna and Yuma Valley. Movement is still below average for February.
Aphids: Seasonal aphid counts peaked in early February and tending down last week. Counts remain high in Gila Valley and Wellton. 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.