Growth dynamics and yield of melon as influenced by nitrogen fertilizer

Nitrogen (N) is an important nutrient for melon (Cucumis melo L.) production. However there is scanty information about the amount necessary to maintain an appropriate balance between growth and yield. Melon vegetative organs must develop sufficiently to intercept light and accumulate water and nutrients but it is also important to obtain a large reproductive-vegetative dry weight ratio to maximize the fruit yield. We evaluated the influence of different N amounts on the growth, production of dry matter and fruit yield of a melon ‘Piel de sapo’ type. A three-year field experiment was carried out from May to September. Melons were subjected to an irrigation depth of 100% crop evapotranspiration and to 11 N fertilization rates, ranging 11 to 393 kg ha –1 in the three years. The dry matter production of leaves and stems increased as the N amount increased. The dry matter of the whole plant was affected similarly, while the fruit dry matter decreased as the N amount was increased above 112, 93 and 95 kg ha –1 , in 2005, 2006 and 2007, respectively. The maximum Leaf Area Index (LAI), 3.1, was obtained at 393 kg ha –1 of N. The lowest N supply reduced the fruit yield by 21%, while the highest increased the vegetative growth, LAI and Leaf Area Duration (LAD), but reduced yield by 24% relative to the N93 treatment. Excessive applications of N increase vegetative growth at the expense of reproductive growth. For this melon type, rates about 90-100 kg ha –1 of N are sufficient for adequate plant growth, development and maximum production. To obtain fruit yield close to the maximum, the leaf N concentration at the end of the crop cycle should be higher than 19.5 g kg –1

SMA-Based Muscle-Like Actuation in Biologically Inspired Robots: A State of the Art Review

New actuation technology in functional or "smart" materials has opened new horizons in robotics actuation systems. Materials such as piezo-electric fiber composites, electro-active polymers and shape memory alloys (SMA) are being investigated as promising alternatives to standard servomotor technology [52]. This paper focuses on the use of SMAs for building muscle-like actuators. SMAs are extremely cheap, easily available commercially and have the advantage of working at low voltages. The use of SMA provides a very interesting alternative to the mechanisms used by conventional actuators. SMAs allow to drastically reduce the size, weight and complexity of robotic systems. In fact, their large force-weight ratio, large life cycles, negligible volume, sensing capability and noise-free operation make possible the use of this technology for building a new class of actuation devices. Nonetheless, high power consumption and low bandwidth limit this technology for certain kind of applications. This presents a challenge that must be addressed from both materials and control perspectives in order to overcome these drawbacks. Here, the latter is tackled. It has been demonstrated that suitable control strategies and proper mechanical arrangements can dramatically improve on SMA performance, mostly in terms of actuation speed and limit cycles.

Identification of intermediate debonding damage in FRP-plated RC beams based on multi-objective particle swarm optimization without updated baseline model

Fiber reinforced polymer composites (FRP) have found widespread usage in the repair and strengthening of concrete structures. FRP composites exhibit high strength-to-weight ratio, corrosion resistance, and are convenient to use in repair applications. Externally bonded FRP flexural strengthening of concrete beams is the most extended application of this technique. A common cause of failure in such members is associated with intermediate crack-induced debonding (IC debonding) of the FRP substrate from the concrete in an abrupt manner. Continuous monitoring of the concrete?FRP interface is essential to pre- vent IC debonding. Objective condition assessment and performance evaluation are challenging activities since they require some type of monitoring to track the response over a period of time. In this paper, a multi-objective model updating method integrated in the context of structural health monitoring is demonstrated as promising technology for the safety and reliability of this kind of strengthening technique. The proposed method, solved by a multi-objective extension of the particle swarm optimization method, is based on strain measurements under controlled loading. The use of permanently installed fiber Bragg grating (FBG) sensors embedded into the FRP-concrete interface or bonded onto the FRP strip together with the proposed methodology results in an automated method able to operate in an unsupervised mode.

Dominance intensity measure within fuzzy weight oriented MAUT: an application

We introduce a dominance intensity measuring method to derive a ranking of alternatives to deal with incomplete information in multi-criteria decision-making problems on the basis of multi-attribute utility theory (MAUT) and fuzzy sets theory. We consider the situation where there is imprecision concerning decision-makers’ preferences, and imprecise weights are represented by trapezoidal fuzzy weights.The proposed method is based on the dominance values between pairs of alternatives. These values can be computed by linear programming, as an additive multi-attribute utility model is used to rate the alternatives. Dominance values are then transformed into dominance intensity measures, used to rank the alternatives under consideration. Distances between fuzzy numbers based on the generalization of the left and right fuzzy numbers are utilized to account for fuzzy weights. An example concerning the selection of intervention strategies to restore an aquatic ecosystem contaminated by radionuclides illustrates the approach. Monte Carlo simulation techniques have been used to show that the proposed method performs well for different imprecision levels in terms of a hit ratio and a rank-order correlation measure.

Influence of body weight of the pullets at hatch on egg production at the onset of the subsequent laying period

We studied the influence of pre-incubation weight of eggs (EW) laid by 24 wk-old brown laying breeders on egg production from 18 (start of egg production) to 22 wk of age (average egg production across EW treatments of 87.8%). The experiment consisted in 7 treatments based on the initial EW (47 to 53 g with 1 g difference between groups) Average BW of the extreme groups varied at hatching from 32.5 to 35.4 g, respectively. Feed intake, egg production, and egg weight were recorded weekly by replicate as well as for the entire experiment (18 to 22 wk of age). Hens were weighed by replicate at the beginning and at the end of the experiment. From these data, ADFI, egg production, egg weight, egg mass, feed conversion ratio per kilogram of eggs and per dozen of eggs, and BW gain were calculated by week and for the entire experiment. Also, the number of dirty, broken, and shell-less eggs was recorded daily by replicate in all eggs produced. Data were analyzed as a completely randomized design with 7 treatments differing in the initial pre-hatching EW. Effects of EW on the variables studied were partitioned into linear and quadratic components. EW did not affect the age at which pullets reached 50% egg production, cumulative egg production, or BW gain of the hens from 18 to 22 wk of age. Egg weight and the proportion of dirty, broken, and shell-less eggs were not affected by the BW of the pullets at hatching. In summary, small eggs (>47 g) laid by young, healthy laying breeders, can be used successfully to produce high quality pullets