Rootstock influence on bloom date and fruit maturation of `Redhaven' peach [Prunus persica (L.) Batsch] was studied over a 3-year period. Rootstock included seedlings (Lovell, Halford, Bailey, and Siberian C) and cuttings (GF677, GF655.2, Damas 1869, and `Redhaven'). Bloom dates of the various combinations differed in all 3 years, with a range of 3.6, 9.1, and 7.3 days in 1988, 1989, and 1990, respectively. Fruit development period differed each year with a range of 3.9, 5.8, and 4.4 days in 1988, 1989, and 1990, respectively. `Weighted-average harvest date also differed with a range of 3.6,2.9, and 5.6 days in 1988, 1989, and 1990, respectively. `Redhaven'/Lovell was the latest blooming and maturing combination in all 3 years of the study.
Lettuce (Lactuca Sativa L.) produced in the low desert typically shows large yield responses to N fertilization. Concern about the potential threat of nitrate-N to ground water prompted the state of Arizona to pass legislation aimed at implementing improved N management practices. Nitrogen management guidelines recommended by the University of Arizona for lettuce suggest a preplant application based on a soil nitrate-N test and subsequent sidedress applications based on plant tissue monitoring. However, growers have some anxiety that close adherence to recommendations resulting from an average plant sample may compromise crop uniformity. Aerial photographs have the potential to detect differences in N status in any portion of the field. This study evaluated digital computer analysis of aerial photographs as a tool for evaluating the N status of lettuce. The digitized photographs appeared to detect deficiencies not apparent to the human eye. There were good correlations (R2 0.83 to 0.99) between Gray-scale ratio and N status, suggesting digital analysis of aerial photographs has potential for diagnosing N deficiencies in lettuce.
Equipment for measuring water use of a greenhouse crop of up to ± 1 kg h-1 over 30 m2 is described. It is based on growing a crop in nutrient film, with a nutrient tank replenished from a water tank, and controlled by accurate level sensors. The water tank is suspended from a load cell interrogated at frequent intervals by a data logging computer. Examples of data collected are given. Peak daytime transpiration rates varied from 50 mg s-1 m-2 to 150 mg m2 s-1 with a maximum error of 5%. With low transpiration rates, the errors were increased, but accuracy could be improved by calculating the rates over a prolonged time interval.