Fruit Set in Avocado: Pollen Limitation, Pollen Load Size, and Selective Fruit Abortion

Avocado is a woody perennial fruit crop originating in Central America and Mexico domesticated and cultivated in the Americas since pre-Columbian times, currently cultivated in subtropical, tropical, and Mediterranean climates worldwide, with increasing importance in international trade. Avocado shows an exuberant flower production that, however, results in a very low fruit set reflected in a massive abscission of flowers and fruitlets. Several factors are involved in this behavior, and, in this work, we have focused on pollination limitation. The results obtained show that pollen deposition takes place at the female and male stages during the avocado flowering season and that the percentage of flowers with pollen on the stigma varies along the flowering season, probably due to changes in temperature that affect not only the floral behavior but also pollinator activity. However, no embryo or endosperm development took place when pollination occurred during the male flowering phase. Thus, the low number of pollen grains landing on the stigmas of female stage flowers observed under natural pollination conditions might not be enough to ensure a good yield. The production of an excess of flowers and subsequent flower drop of most of the flowers provides the opportunity of a selective fruitlet drop depending on the genotype of the embryo since fruits derived from outcrossing showed higher chances of reaching maturity. Moreover, an important competition for resources occurs among developing fruits and new vegetative growth, conferring importance to the time of flower fertilization for effective fruit set.

High efficiency preparation of standard grade γ-tocopherol in plant-scale and its antioxidant activity

Natural standard grade γ-tocopherol are of great interest due to its good antioxidant activity and special pharmacological functions. This study separated and purified γ-tocopherol from mixed tocopherols using eco-friendly and low toxicity solvents. 0.28 g γ-tocopherol was obtained per performance with a purity of 98.89 ± 0.68% and a recovery yield of 93.23 ± 0.89%. The purification conditions were as follows: elution solvent n-hexane/ethyl acetate 94.5:5.5 (v/v), sample load size 0.5 g, a column height to diameter ratio of 16:1 and an elution rate of 2 mL/min. The purity and structure of γ-tocopherol was confirmed by HPLC, GC/MS and NMR. The adsorption isotherm of γ-tocopherol on silica gel (200-300 mesh) fitted the Langmuir isotherm model well. The antioxidant activity analysis showed that γ-tocopherol had the strongest antioxidant activity followed by δ-tocopherol and α-tocopherol. This study provides an economically attractive solution for the production of natural standard grade γ-tocopherol.

Load-Identification Method for Flexible Multiple Corrugated Skin Using Spectra Features of FBGs

Flexible corrugated skins are ideal structures for morphing wings, and the associated load measurements are of great significance in structural health monitoring. This paper proposes a novel load-identification method for flexible corrugated skins based on improved Fisher discrimination dictionary learning (FDDL). Several fiber Bragg grating sensors are pasted on the skin to monitor the load on multiple corrugated crests. The loads on different crests cause nonuniform strain fields, and these discriminative spectra are recorded and used as training data. The proposed method involves load-positioning and load-size identification. In the load-size-identification stage, a classifier is trained for every corrugated crest. An interleaved block grouping of samples is introduced to enhance the discrimination of dictionaries, and a two-resolution load-size classifier is introduced to improve the performance and resolution of the grouping labels. An adjustable weight is introduced to the FDDL classification scheme to optimize the contribution from different sensors for different load-size classifiers. With the proposed method, the individual loads on eight crests can be identified by two fiber Bragg grating sensors. The positioning accuracy is 100%, and the mean error of the load-size identification is 0.2106 N, which is sufficiently precise for structural health monitoring.

Influence of the Load Distribution And Sizes on the Wheel Geometry in Passenger Cars

This paper discusses impact of changes in the load size and distribution in passenger cars on geometry of the suspension and steering systems. It was found to have a major impact on the road safety. The research was carried out with the four most popular suspension system designs used in modern passenger cars, i.e. multi-link suspension on both front and rear axles, only on the front axle, only on the rear axle and a simple suspension design for both front and rear axles. Eight load variants were used for the tests. Changes in the following wheel geometry parameters were identified: toe-in and camber angles of all the wheels and castors for the front wheels. The numerical relationships were determined between the load distribution and sizes and changes in suspension and steering systems in passenger cars. It was found that cars with multi-link suspension in both front and rear axles adapt best to changes in weight and load distribution.

Relationship between drying parameters and drying performance in domestic tumble dryers

The purpose of this study is to investigate the effect of drying parameters on drying performance in an air-vented tumble dryer, and to optimize its drying performance by adjusting parameters. The critical drying parameters that influenced specific moisture extraction rate (SMER), final moisture content, evenness of drying, and smoothness appearance were determined by the analysis of variance in JMP software, which were rotational speed of the motor and load size, with clearly significant individual effects and binary interactions. In order to improve the applicability of the outcomes obtained in this study and to take into account the interactions between drying parameters and drum structure parameters on drying efficiency, non-dimensional analysis was used and the correlation between drying efficiency and dimensionless variables was studied. The Buckingham Pi theorem was applied to the problem to derive dimensionless Pi terms upon which the drying efficiency depends. A step regression analysis was then conducted to test the assumption that SMER was influenced by the dimensionless parameters based on the standard least squares fitting. Results indicated that the regression model showed an explanatory power of 73.8%. By adjusting the dimensionless parameters in the model, an optimized energy-saving drying program was obtained with the desirability goal of reducing the value of SMER. Compared with the original program, energy efficiency was improved by 32.4%.

Multi-Product Forwarder-Based Timber Extraction

Accurate predictions in forest operations can be used towards effective planning, costing, and maximizing the productivity of machines in mechanised cut-to-length (CTL) harvesting. There is a general and substantial gap in forwarder productivity data available for pine sawtimber in South Africa at present, and as the number of product assortments being harvested increase there is a need for more work to quantify the effects of extracting products of different dimensions. The aim of this study was to calculate the time consumption and productivity of two models of Ponsse forwarders (15 t and 20 t capacity) to consider and compare the effects of multiple variables including machine capabilities, product assortment, load size, extraction distance and fuel consumption. Productivity averaged at 34.08 m3 per productive machine hour excluding delays longer than one minute (PMH1) for the smaller machine, and 55.94 m3/PMH1 for the larger machine. Productivity and average log volume were strongly positively correlated. Regression models were created for each machine where load volume and extraction distance were both significant factors for predicting productivity. Average fuel consumption of the smaller machine was 15.55 l/PMH1 and 0.47 l/m3, and 20.57 l/PMH1 and 0.43 l/m3 for the larger machine. The product with the largest volume was found to require the least fuel per m3. The models developed could aid in predicting system productivity and potentially carbon emissions under similar conditions in a South African context of industrial plantation forestry.

Kinematic flexibility allows bumblebees to increase energetic efficiency when carrying heavy loads

Foraging bees fly with heavy loads of nectar and pollen, incurring energetic costs that are typically assumed to depend on load size. Insects can produce more force by increasing stroke amplitude and/or flapping frequency, but the kinematic response of a given species is thought to be consistent. We examined bumblebees (Bombus impatiens) carrying both light and heavy loads and found that stroke amplitude increased in proportion to load size, but did not predict metabolic rate. Rather, metabolic rate was strongly tied to frequency, which was determined not by load size but by the bee’s average loading state and loading history, with heavily loaded bees displaying smaller changes in frequency and smaller increases in metabolic rate to support additional loading. This implies that bees can increase force production through alternative mechanisms; yet, they often choose the energetically costly option of elevating frequency, suggesting associated performance benefits that merit further investigation.