The quality of agricultural products relates to the internal structure, which has long been a matter of interest in agricultural scientists. However, inspection methods of the opaque nature of internal information on agricultural products are usually destructive and require sample separation or preparation. X‐ray computed tomography (X‐ray CT) technology is one of the important nondestructive testing (NDT) technologies without sample separation and preparation. In this study, X‐ray CT technology is used to obtain two‐dimensional slice images and three‐dimensional tomographic images of samples. The purpose of the review was to provide an overview of the working principle of X‐ray CT technology, image processing, and analysis. This review aims to focus on the development of the agricultural products (e.g., wheat, maize, rice, apple, beef) and its applications (e.g., internal quality evaluation, microstructure observation, mechanical property measurement, and others) using CT scanner. This paper covers the aspects regarding the advantages and disadvantages of NDT technology, especially the unique advantages and limitations of X‐ray CT technology on the quality inspection of agricultural products. Future prospects of X‐ray CT technology are also put forward to become indispensable to the quality evaluation and product development on agricultural products.
Abstract:Confronted with severe frost damage to plants, methods, technologies and equipment have been developed and applied during the past century. The paper presents a comprehensive review on the most effective and active technology to protect plants from radiation frost based on air disturbance technology. The working principle of the technology was elaborated with frost protection mechanism, structures and applicability of three types of working patterns: conventional wind machines, selective inverted sink and portable vertical blowing. As an automatic mechanized technology, control strategy, applicable occasion and proper parameters are introduced for each type of working pattern. The operation of the technology and equipment depends on plant critical temperature, prevailing climatic conditions, thermal inversions strength, as well as costs. The frost protection performance and effectiveness of conventional horizontal wind machines, selective inverted sinks and helicopters are discussed and compared from the cost-effectiveness and application aspects, and the feasibility of selective inverted sinks is still controversial. Therefore, conventional wind machines are the best choice for plant frost protection and consequently are widely used in temperate and subtropical areas throughout the world. The frost protection application with helicopters is not easy to use during the frost nights with high cost. The paper also provides researchers with some perspectives on improving air disturbance technology and its equipment, and some practice recommendations for growers.
For developing countries, scarcity of climatic data is the biggest challenge, and model development with limited meteorological input is of critical importance. In this study, five data intelligent and hybrid metaheuristic machine learning algorithms, namely additive regression (AR), AR-bagging, AR-random subspace (AR-RSS), AR-M5P, and AR-REPTree, were applied to predict monthly mean daily reference evapotranspiration (ET0). For this purpose, climatic data of two meteorological stations located in the semi-arid region of Pakistan were used from the period 1987 to 2016. The climatic dataset includes maximum and minimum temperature (Tmax, Tmin), average relative humidity (RHavg), average wind speed (Ux), and sunshine hours (n). Sensitivity analysis through regression methods was applied to determine effective input climatic parameters for ET0 modeling. The results of performed regression analysis on all input parameters proved that Tmin, RHAvg, Ux, and n were identified as the most influential input parameters at the studied station. From the results, it was revealed that all the selected models predicted ET0 at both stations with greater precision. The AR-REPTree model was located furthest and the AR-M5P model was located nearest to the observed point based on the performing indices at both the selected meteorological stations. The study concluded that under the aforementioned methodological framework, the AR-M5P model can yield higher accuracy in predicting ET0 values, as compared to other selected algorithms.
The estimation of evapotranspiration (ET) is essential for meteorological modeling of surface exchange processes, as well as for the agricultural practice of irrigation management. Hitherto, a number of methods for estimation of ET at different temporal scales and climatic conditions are constantly under investigation and improvement. One of these methods is surface renewal (SR). Therefore, the premise of this review is to present recent developments and applications of SR for ET measurements. The SR method is based on estimating the turbulent exchange of sensible heat flux between plant canopy and atmosphere caused by the instantaneous replacement of air parcels in contact with the surface. Additional measurements of net radiation and soil heat flux facilitate extracting ET using the shortened energy balance equation. The challenge, however, is the calibration of SR results against direct sensible heat flux measurements. For the classical SR method, only air temperature measured at high frequency is required. In addition, a new model suggests that the SR method could be exempted from calibration by measuring additional micrometeorological variables. However, further improvement of the SR method is required to provide improved results in the future.
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