scholarly journals Performance of Satsuma Mandarin Protected from Freezing Temperatures by Microsprinkler Irrigation

HortScience ◽  
2000 ◽  
Vol 35 (5) ◽  
pp. 856-859
Author(s):  
Monte L. Nesbitt ◽  
N.R. McDaniel ◽  
Robert C. Ebel ◽  
W.A. Dozier ◽  
David G. Himelrick

Several microsprinkler treatments were tested on 5-year-old satsuma mandarin orange (Citrus unshiu Marc.) trees to compare survivability of trunks and scaffold limbs in severe freezes. Three damaging freeze events occurred during winter, with two in 1995–96 and one in 1996–97. Air temperature dropped to –9.4, –5.6, and –6.7 °C, respectively. Almost 90% of the foliage was dead on the control plants after the first freezing event and 98% after the second. A single microsprinkler 1.6 m high in the canopy delivering 90.8 L·h–1 reduced injury; only 54% of the canopy was dead after the first freeze and 71% after the second. There was slightly more shoot-tip dieback on the plants in the microsprinkler treatments than on the control plants after the first two freezes. The amount of limb breakage by ice was minor. The third freeze killed 34% of the canopy in the control plants, but only 26% in the plants in the microsprinkler treatments. Use of microsprinklers increased yield in 1996, but yield for all treatments was very low. Yield for all treatments fully recovered in 1997, averaging 153 kg/tree. Although no death of scaffold limbs or trunks occurred, these results demonstrate that microsprinkler irrigation reduces damage to foliage and increases yield somewhat in severe freezes.

2001 ◽  
Vol 11 (1) ◽  
pp. 150a
Author(s):  
Monte L. Nesbitt ◽  
N.R. McDaniel ◽  
Robert C. Ebel ◽  
W.A. Dozier ◽  
David G. Himelrick

Several microsprinkler treatments were tested on 5-year-old satsuma mandarin orange (Citrus unshiu Marc.) trees to compare survivability of trunks and scaffold limbs in severe freezes. Three damaging freeze events occurred during winter, with two in 1995-96 and one in 1996-97. Air temperature dropped to -9.4, -5.6, and -6.7 °C, respectively. Almost 90% of the foliage was dead on the control plants after the first freezing event and 98% after the second. A single microsprinkler 1.6 m high in the canopy delivering 90.8 L·h-1 reduced injury; only 54% of the canopy was dead after the first freeze and 71% after the second. There was slightly more shoot-tip dieback on the plants in the microsprinkler treatments than on the control plants after the first two freezes. The amount of limb breakage by ice was minor. The third freeze killed 34% of the canopy in the control plants, but only 26% in the plants in the microsprinkler treatments. Use of microsprinklers increased yield in 1996, but yield for all treatments was very low. Yield for all treatments fully recovered in 1997, averaging 153 kg/tree. Although no death of scaffold limbs or trunks occurred, these results demonstrate that microsprinkler irrigation reduces damage to foliage and increases yield somewhat in severe freezes.


2004 ◽  
Vol 102 (3) ◽  
pp. 295-300 ◽  
Author(s):  
Yoshimi Yonemoto ◽  
Kazunori Matsumoto ◽  
Tadashi Furukawa ◽  
Masaaki Asakawa ◽  
Hitoshi Okuda ◽  
...  

2016 ◽  
Vol 20 (5) ◽  
pp. 1681-1702 ◽  
Author(s):  
Madeline R. Magee ◽  
Chin H. Wu ◽  
Dale M. Robertson ◽  
Richard C. Lathrop ◽  
David P. Hamilton

Abstract. The one-dimensional hydrodynamic ice model, DYRESM-WQ-I, was modified to simulate ice cover and thermal structure of dimictic Lake Mendota, Wisconsin, USA, over a continuous 104-year period (1911–2014). The model results were then used to examine the drivers of changes in ice cover and water temperature, focusing on the responses to shifts in air temperature, wind speed, and water clarity at multiyear timescales. Observations of the drivers include a change in the trend of warming air temperatures from 0.081 °C per decade before 1981 to 0.334 °C per decade thereafter, as well as a shift in mean wind speed from 4.44 m s−1 before 1994 to 3.74 m s−1 thereafter. Observations show that Lake Mendota has experienced significant changes in ice cover: later ice-on date(9.0 days later per century), earlier ice-off date (12.3 days per century), decreasing ice cover duration (21.3 days per century), while model simulations indicate a change in maximum ice thickness (12.7 cm decrease per century). Model simulations also show changes in the lake thermal regime of earlier stratification onset (12.3 days per century), later fall turnover (14.6 days per century), longer stratification duration (26.8 days per century), and decreasing summer hypolimnetic temperatures (−1.4 °C per century). Correlation analysis of lake variables and driving variables revealed ice cover variables, stratification onset, epilimnetic temperature, and hypolimnetic temperature were most closely correlated with air temperature, whereas freeze-over water temperature, hypolimnetic heating, and fall turnover date were more closely correlated with wind speed. Each lake variable (i.e., ice-on and ice-off dates, ice cover duration, maximum ice thickness, freeze-over water temperature, stratification onset, fall turnover date, stratification duration, epilimnion temperature, hypolimnion temperature, and hypolimnetic heating) was averaged for the three periods (1911–1980, 1981–1993, and 1994–2014) delineated by abrupt changes in air temperature and wind speed. Average summer hypolimnetic temperature and fall turnover date exhibit significant differences between the third period and the first two periods. Changes in ice cover (ice-on and ice-off dates, ice cover duration, and maximum ice thickness) exhibit an abrupt change after 1994, which was related in part to the warm El Niño winter of 1997–1998. Under-ice water temperature, freeze-over water temperature, hypolimnetic temperature, fall turnover date, and stratification duration demonstrate a significant difference in the third period (1994–2014), when air temperature was warmest and wind speeds decreased rather abruptly. The trends in ice cover and water temperature demonstrate responses to both long-term and abrupt changes in meteorological conditions that can be complemented with numerical modeling to better understand how these variables will respond in a future climate.


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