Effect of timing of a deficit-irrigation allocation on corn evapotranspiration, yield, water use efficiency and dry mass

Water regulations have decreased irrigation water supplies in Nebraska and some other areas of the USA Great Plains. When available water is not enough to meet crop water requirements during the entire growing cycle, it becomes critical to know the proper irrigation timing that would maximize yields and profits. This study evaluated the effect of timing of a deficit-irrigation allocation (150 mm) on crop evapotranspiration (ETc), yield, water use efficiency (WUE = yield/ETc), irrigation water use efficiency (IWUE = yield/irrigation), and dry mass (DM) of corn (Zea mays L.) irrigated with subsurface drip irrigation in the semiarid climate of North Platte, NE. During 2005 and 2006, a total of sixteen irrigation treatments (eight each year) were evaluated, which received different percentages of the water allocation during July, August, and September. During both years, all treatments resulted in no crop stress during the vegetative period and stress during the reproductive stages, which affected ETc, DM, yield, WUE and IWUE. Among treatments, ETc varied by 7.2 and 18.8%; yield by 17 and 33%; WUE by 12 and 22%, and IWUE by 18 and 33% in 2005 and 2006, respectively. Yield and WUE both increased linearly with ETc and with ETc/ETp (ETp = seasonal ETc with no water stress), and WUE increased linearly with yield. The yield response factor (ky) averaged 1.50 over the two seasons. Irrigation timing affected the DM of the plant, grain, and cob, but not that of the stover. It also affected the percent of DM partitioned to the grain (harvest index), which increased linearly with ETc and averaged 56.2% over the two seasons, but did not affect the percent allocated to the cob or stover. Irrigation applied in July had the highest positive coefficient of determination (R2) with yield. This high positive correlation decreased considerably for irrigation applied in August, and became negative for irrigation applied in September. The best positive correlation between the soil water deficit factor (Ks) and yield occurred during weeks 12-14 from crop emergence, during the "milk" and "dough" growth stages. Yield was poorly correlated to stress during weeks 15 and 16, and the correlation became negative after week 17. Dividing the 150 mm allocation about evenly among July, August and September was a good strategy resulting in the highest yields in 2005, but not in 2006. Applying a larger proportion of the allocation in July was a good strategy during both years, and the opposite resulted when applying a large proportion of the allocation in September. The different results obtained between years indicate that flexible irrigation scheduling techniques should be adopted, rather than relying on fixed timing strategies.

Accumulation of dry mass and macronutrients by sourgrass plants

The experiment was carried out aiming to analyze the dry mass production and distribution and the content and accumulation of macronutrients in sourgrass (Digitaria insularis) plants cultivated under mineral nutrition standard conditions. Plants grew in 7-liter pots filled with sand substrate and daily irrigated with nutrient solution, being maintained under greenhouse conditions. Treatments consisted of times of evaluation (21, 35, 49, 63, 77, 91, 105, 119, and 133 days after emergence - DAE) and were arranged in a completely randomized design with four replicates. Sourgrass showed small accumulation of dry mass (0.3 g per plant) and macronutrients (3.7 mg of N per plant, 0.4 mg of P per plant, 5.6 mg of K per plant, 0.9 mg of Ca per plant, 0.7 mg of Mg per plant, and 0.3 mg of S per plant) at vegetative growth stage (< 49 DAE). Those accumulations increased mainly after 77 DAE, reaching the maximum theoretical value at 143, 135, 141, 129, 125, 120, and 128 DAE, for dry mass (12.4 g per plant), N (163.2 mg per plant), P (27.1 mg per plant), K (260.5 mg per plant), Ca (47.6 mg per plant), Mg (30.9 mg per plant), and S (13.7 mg per plant), respectively. K and N were found with higher rates and, as a consequence, they were required and accumulated in greater amounts in plant tissues of sourgrass.

NUTRITIONAL STATUS AND DRY MASS PRODUCTION OF ALFALFA IN FUNCTION OF POTASSIUM RATES IN TWO SOILS

Potassium fertilization is very important to alfalfa crop in terms of yield, quality and persistence of forage, especially on soils naturally poor K. Thus, to assess the effects of K fertilization in alfalfa production and nutritional status, was carried out an experiment in a greenhouse using samples of a Dystrophic Oxisol medium texture (LV) (0.6 mmol(c) dm(-3) K) and a Dystrophic Ultisol sandy/medium texture (PVA) (2.2 mmol(c) dm(-3) K). A completely randomized design in a factorial arrangement 6 x 2 (six K rates and two soils) was used, with four replications. The K rates used were: 0, 25, 50, 100, 150 and 200 mg kg(-1) K. Potassium fertilization increased K content in soil and shoots. Dry matter production was increased with the K addition. However, in the PVA, this occurred only in the second cut. In LV, potassium fertilization increased N concentration in alfalfa shoots in both cuts. Plants with K concentration around 10 g kg(-1) had typical symptoms of this nutrient deficiency. The K critical levels of K in soil and shoots were 1.8 mmolc dm(-3) and 16.7 g kg(-1), respectively.

Abundance and biomass of mesozooplankton in the Levantine Basin during the Bilim 2 cruise in April 2008

The Sesame dataset contains mesozooplankton data collected during April 2008 in the Levantine Basin (between 33.20 and 36.50 N latitude and between 30.99 and 31.008 E longitude). Mesozooplankton samples were collected by using a WP-2 closing net with 200 µm mesh size during day hours (07:00-18:00). Samples were taken from 0-50, 50-100, 100-200 m layers at 5 stations in Levantine Basin The dataset includes samples analyzed for mesozooplankton species composition, abundance and total mesozooplankton biomass. Sampling volume was estimated by multiplying the mouth area with the wire length. Sampling biomass was measured by weighing filters and then determined by sampling volume. The samples were sieved sequentially through meshes of 500 and 200 micron to separate the mesozooplankton into size fractions. The entire sample (1/2) or an aliquot of the taxon-specific mesozooplankton abundance and the total abundance of the mesozooplankton were was analyzed under the binocular microscope. Minimum 500 individuals of mesozooplankton were identified and numerated at higher taxonomic level. Taxonomic identification was done at the METU- Institute of Marine Sciences by Alexandra Gubanova,Tuba Terbiyik using the relevant taxonomic literatures. Mesozooplankton abundance and biomass were estimated by Zahit Uysal and Yesim Ak.