Search Results
Garlic (cv California Late) was produced under four irrigation regimes (110% and 130% evapotranspiration with two water cut-off dates, 10 and 24 May 1999) in combination with three nitrogen fertilization levels (100, 250, and 400 lb total N). Bulbs were manually harvested mid-June, cured 3 weeks shaded at ambient temperatures and the outer whorl of cloves manually peeled. Samples were freeze-dried, and carbohydrate (fructan and free sugars) and alliin (substrate for alliinase activity and indicator of potential pungency) concentrations were determined by HPLC. The percent dry weight was not affected by the irrigation treatment, but was reduced with increased N rate (41.3% to 39.0%). Alliin concentrations varied from 8.3 to 13.8 mg/g DW for 110% and 130% Eto irrigation treatments. Alliin concentrations were not affected by N fertilization (average = 11.5 mg/g DW). Fructan concentrations were affected by N fertilization treatment, with the highest content (802 mg/g DW) associated with the lowest N level, and the lowest (717 mg/g DW) content in samples from the highest N rate. Sucrose concentrations increased with increased N, but glucose and fructose concentrations did not vary with N fertilization. Fructan as percent of total carbohydrate remained constant across irrigation treatments (96.6% + 0.2%) and across N fertilization treatments (96.6% + 0.3%).
Current methods of making crop cover estimates are time-consuming and tend to be highly variable. A low-cost, digital, red/near-infrared band ratioing camera (Dycam Inc., Chatsworth, Calif.) and accompanying software (S. Heinold, Woodland Hills, Calif.) were evaluated for estimating crop cover. The camera was tested using a set of images having leaf areas of known sizes with different crop, soil, and lighting conditions. In the field, camera-based crop cover estimates were compared to light bar measured estimates. Results indicate that the camera and image analysis software are capable of estimating percent crop cover over a range of soil, crop, and lighting environments. Camera-based crop cover estimates were highly correlated with light bar estimates (tomato r 2 = 0.96, cotton r 2 = 0.98). Under the conditions tested, the camera appears to be a useful tool for monitoring crop growth in the field.