Comparison of manual and automatic barcode detection in rough horticultural production systems

Automation of production in the nurseries of flower producing companies using barcode scanners have been attempted but with little success.Stationary laser barcode scanners which have been used for automation have failed due to the close proximity between the barcode and the scanner,and factors such as speed,angle of inclination of the barcode,damage to the barcode and dirt on the barcode.Furthermore,laser barcode scanners are still being used manually in the nurseries making work laborious and time consuming,which leading to reduced productivity.Therefore,an automated image-based barcode detection system to help solve the aforementioned problems was proposed.Experiments were conducted under different situations with clean and artificially soiled Code 128 barcodes in both the laboratory and under real production conditions in a flower producing company.The images were analyzed with a specific algorithm developed with the software tool Halcon.Overall the results from the company showed that the image-based system has a future prospect for automation in the nursery.

Towards sustainable intensification of apple production in China—Yield gaps and nutrient use effi ciency in apple farming systems

China is in a dominant position in apple production globally with both the largest apple growing area and the largest export of fresh apple fruits. However, the annual productivity of China＇s apple is significantly lower than that of other dominant apple producing countries. In addition, apple production is based on excessive application of chemical fertilizers and the nutrient use efficiency （especially nitrogen） is therefore low and the nutrient emissions to the environment are high. Apple production in China is considerably contributes to farmers＇ incomes and is important as export product. There is an urgent need to enhance apple productivity and improve nutrient use efficiencies in intensive apple production systems in the country. These can be attained by improved understanding of production potential, yield gaps, nutrient use and best management in apple orchards. To the end, priorities in research on apple production systems and required political support are described which may lead to more sustainable and environmental-friendly intensification of apple production in China.

IR-YOLO: Real-Time Infrared Vehicle and Pedestrian Detection

Road traffic safety can decrease when drivers drive in a low-visibility environment.The application of visual perception technology to detect vehicles and pedestrians in infrared images proves to be an effective means of reducing the risk of accidents.To tackle the challenges posed by the low recognition accuracy and the substan-tial computational burden associated with current infrared pedestrian-vehicle detection methods,an infrared pedestrian-vehicle detection method A proposal is presented,based on an enhanced version of You Only Look Once version 5(YOLOv5).First,A head specifically designed for detecting small targets has been integrated into the model to make full use of shallow feature information to enhance the accuracy in detecting small targets.Second,the Focal Generalized Intersection over Union(GIoU)is employed as an alternative to the original loss function to address issues related to target overlap and category imbalance.Third,the distribution shift convolution optimization feature extraction operator is used to alleviate the computational burden of the model without significantly compromising detection accuracy.The test results of the improved algorithm show that its average accuracy(mAP)reaches 90.1%.Specifically,the Giga Floating Point Operations Per second(GFLOPs)of the improved algorithm is only 9.1.In contrast,the improved algorithms outperformed the other algorithms on similar GFLOPs,such as YOLOv6n(11.9),YOLOv8n(8.7),YOLOv7t(13.2)and YOLOv5s(16.0).The mAPs that are 4.4%,3%,3.5%,and 1.7%greater than those of these algorithms show that the improved algorithm achieves higher accuracy in target detection tasks under similar computational resource overhead.On the other hand,compared with other algorithms such as YOLOv8l(91.1%),YOLOv6l(89.5%),YOLOv7(90.8%),and YOLOv3(90.1%),the improved algorithm needs only 5.5%,2.3%,8.6%,and 2.3%,respectively,of the GFLOPs.The improved algorithm has shown significant advancements in balancing accuracy and computational efficiency,making it promising for practical use in resource-limited scenarios.

A new electric field mill array with each of the mill’s rotor controlled precisely by a GPS module:Equipment and initial results

We have newly designed an electrostatic sensor,called an electric field mill(EFM),to simplify the estimation of the charge position and charge amount transferred by lightning discharges.It is necessary for this remote estimation of the transferred charge to measure electric field changes caused by charge loss at the time of a lightning strike at multiple locations.For multiple-station measurement of electric field changes,not only speed but also phase for exposure and shielding of the sensing plates inside each EFM of the array should be synchronized to maintain the sensitivities of the deployed instruments.Currently,there is no such EFM with specified speed and phase control performance of the rotary part.Thus,we developed a new EFM in which the rotary mechanism was controlled consistently to within 3%error by a GPS module.Five EFMs had been distributed in the Hokuriku area of Japan during the winter season of 2022-2023 for a test observation.Here we describe the design and a simple calibration method for our new EFM array.Data analysis method based on the assumption of a simple monopole charge structure is also summarized.For validation,locations of assumed point charges were compared with three-dimensional lightning mapping data estimated by radio observations in the MF-HF bands.Initial results indicated the validity to estimate transferred charge amounts and positions of winter cloud-to-ground lightning discharges with our new EFM array.

Data-driven polarimetric imaging: a review

This study reviews the recent advances in data-driven polarimetric imaging technologies based on a wide range of practical applications.The widespread international research and activity in polarimetric imaging techniques demonstrate their broad applications and interest.Polarization information is increasingly incorporated into convolutional neural networks(CNN)as a supplemental feature of objects to improve performance in computer vision task applications.Polarimetric imaging and deep learning can extract abundant information to address various challenges.Therefore,this article briefly reviews recent developments in data-driven polarimetric imaging,including polarimetric descattering,3D imaging,reflection removal,target detection,and biomedical imaging.Furthermore,we synthetically analyze the input,datasets,and loss functions and list the existing datasets and loss functions with an evaluation of their advantages and disadvantages.We also highlight the significance of data-driven polarimetric imaging in future research and development.

Agronomic and Physiological Responses of Rice (<i>Oryza sativa</i>L.) under Different Water Management Systems, Fertilizer Types and Seedling Age

A field experiment was conducted to evaluate the agronomic and physiological responses of rice under different water management systems, types of fertilizer and seedling age. This experiment was done at the farm of Agri Park, College of Agriculture, Central Experimental Station (CES), Crop Science Cluster of the University of the Philippines Los Banos, College Laguna during 2013. The strip-split plot design with three replications was used with the two types of fertilizer (vermicompost and chemical fertilizer), water management (with and without standing water) and two seedling ages (10 and 14-d old) were the treatments in the experiment. Chemical fertilizer produced the highest grain yield, total dry matter (TDM), leaf area index (LAI), net assimilation rate (NAR) and crop growth rate (CGR). Most of these characters significantly increased in 10-d old seedlings with chemical fertilizer without standing water. The shorter phyllochron and higher root pulling resistance (RPR) were observed in 10-d old seedlings without standing water. For the variety NSIC Rc 216, the use of 10-d old seedlings grown without standing water with chemical fertilizer is the optimum conditions for the better growth and high productivity.

A Dual-Channel Secure Transmission Scheme for Internet-Based Networked Control Systems

Two significant issues in Internet-based networked control systems （ INCSs）, transport performance of different protocols and security breach from Internet side, are investigated. First, for improving the performance of data transmission, user datagram protocol （UDP） is adopted as the main stand for controllers and plants using INCSs. Second, a dual-channel secure transmission scheme （DCSTS）based on data transmission characteristics of INCSs is proposed, in which a raw UDP channel and a secure TCP （transmission control protocol） connection making use of SSL/TLS （secure sockets layer/transport layer security） are included. Further, a networked control protocol （NCP） at application layer for supporting DCSTS between the controllers and plants in INCSs is designed, and it also aims at providing a universal communication mechanism for interoperability of devices among the networked control laboratories in Beijing Institute of Technology of China, Central South University of China and Tokyo University of Technology of Japan. By means of a networked single-degree-of-free- dom robot arm, an INCS under the new protocol and security environment is created. Compared with systems such as IPSec or SSL/TLS, which may cause more than 91% network throughput deduction, the new DCSTS protocol may yield results ten times better, being just 5.67%.

Small ruminant value chain in Al-Ruwaished District,Jordan

This study aims to assess the small ruminant value chain in Al-Ruwaished District,Jordan,to identify the potential intervention areas that could improve the production efficiency and guarantee the sustainability of the small ruminant sector in this area.Sheep breeding is the source of livelihood for most of the people in Al-Ruwaished District,which is characterized by the large number of sheep and goats.We surveyed 5.0% of the small ruminant holders in the study area and conducted individual interviews and surveys with the potential actors in the value chain to undertake a small ruminant value chain analysis.From the survey,we found that the small ruminant value chain consists of five core functions,namely,input supply,production management,marketing,processing,and consumption.Despite the stable impression given by the large number of holdings in the small ruminant sector,the surveyed results show a clear fragility in the value chain of small ruminants in this area.The small ruminant production system is negatively impacted by climate change,especially continuous drought.In addition,the high prices of feed that the farmer cannot afford with clear and real absence of the governmental and non-governmental support activities also impact the development of the value chain.The results of strengths,weaknesses,opportunities,and threats(SWOT)analysis reveal that the major constraints faced by this value chain could be divided into external and internal threats.Specifically,the most prominent external threats are the nature of the desert land and continuous drought,while the major internal threats are the absence of appropriate infrastructure,shortage of inputs,and weakness in the production management and marketing.We proposed solutions to these challenges to ensure the sustainability and effectiveness of the sector,such as the formulation of emergency response plans to severe weather,qualifying farmers’skills,and establishment of agricultural cooperative societies.

Comparing Pan-Sharpening Algorithms to Access an Agriculture Area: A Mississippi Case Study

Numerous satellites collect imagery of the Earth’s surface daily, providing information to the public and private sectors. The fusion (pan-sharpening) of high-resolution panchromatic satellite imagery with lower-resolution multispectral satellite imagery has shown promise for monitoring natural resources and farming areas. It results in new imagery with more detail than the original multispectral or panchromatic images. In agricultural areas in Mississippi, landscapes can range from complex mixtures of vegetation and built-up areas to dense vegetative regions. More information is needed on pan-sharpened imagery for assessing landscapes in rural areas of Mississippi. WorldView 3 satellite imagery consisting of landscapes commonly found in rural areas of Mississippi was subjected to 17 pan-sharpening algorithms. The pan-sharpened images were compared qualitatively and quantitatively with three quality indices: 1) Erreur Relative Globale Addimensionelle de Synthese;2) Universal Image Quality Index;3) Bias. à trous wavelet transform with the injection model 3 and hyperspherical color spaced fusion methods were ranked among the best for maintaining image integrity for qualitative and quantitative analyses. The optimized high-pass filter method was often ranked last by the quality indices. The smoothing filter-based intensity modulation algorithm and the gaussian modulation transfer function match filtered with high-pass modulation injection model added artifacts to the images. Pan-sharpened satellite imagery has great potential to enhance the survey of Mississippi’s agricultural areas. The key to success is selecting an image fusion process that increases spatial content while not compromising the image integrity.

Machine Learning Mapping of Soil Apparent Electrical Conductivity on a Research Farm in Mississippi

Open-source and free tools are readily available to the public to process data and assist producers in making management decisions related to agricultural landscapes. On-the-go soil sensors are being used as a proxy to develop digital soil maps because of the data they can collect and their ability to cover a large area quickly. Machine learning, a subcomponent of artificial intelligence, makes predictions from data. Intermixing open-source tools, on-the-go sensor technologies, and machine learning may improve Mississippi soil mapping and crop production. This study aimed to evaluate machine learning for mapping apparent soil electrical conductivity (ECa) collected with an on-the-go sensor system at two sites (i.e., MF2, MF9) on a research farm in Mississippi. Machine learning tools (support vector machine) incorporated in Smart-Map, an open-source application, were used to evaluate the sites and derive the apparent electrical conductivity maps. Autocorrelation of the shallow (ECas) and deep (ECad) readings was statistically significant at both locations (Moran’s I, p 0.001);however, the spatial correlation was greater at MF2. According to the leave-one-out cross-validation results, the best models were developed for ECas versus ECad. Spatial patterns were observed for the ECas and ECad readings in both fields. The patterns observed for the ECad readings were more distinct than the ECas measurements. The research results indicated that machine learning was valuable for deriving apparent electrical conductivity maps in two Mississippi fields. Location and depth played a role in the machine learner’s ability to develop maps.

Combining rhizosphere and soil-based P management decreases the P fertilizer demand of China by more than half based on LePA model simulations

Phosphorus(P)is a finite natural resource and is increasingly considered to be a challenge for global sustainability.Agriculture in China plays a key role in global sustainable P management.Rhizosphere and soil-based P management are necessary for improving P-use efficiency and crop productivity in intensive agriculture in China.A previous study has shown that the future demand for phosphate fertilizer by China estimated by the LePA model(legacy phosphorus assessment model)can be greatly reduced by soil-based P management(the building-up and maintenance approach).The present study used the LePA model to predict the phosphate demand by China through combined rhizosphere and soil-based P management at county scale under four P fertilizer scenarios:(1)same P application rate as in 2012;(2)rate maintained same as 2012 in low-P counties or no P fertilizer applied in high-P counties until targeted soil Olsen-P(TPOlsen)level is reached,and then rate was the same as P-removed at harvest;(3)rate in each county decreased to1–7 kg ha^(-1) yr^(-1) after TPOlsen is reached in low-P counties,then increased by 0.1–9 kg ha^(-1) yr^(-1) until equal to P-removal;(4)rate maintained same as 2012 in low-P counties until TPOlsen is reached and then equaled to P-removal,while the rate in high-P counties is decreased to 1–7 kg ha^(-1) yr^(-1) until TPOlsen is reached and then increased by 0.1–9 kg ha^(-1) yr^(-1)until equal to P-removal.Our predictions showed that the total demand for P fertilizer by whole China was 693 Mt P2O5and according to scenario 4,P fertilizer could be reduced by 57.5%compared with farmer current practice,during the period 2013–2080.The model showed that rhizosphere P management led to a further 8.0%decrease in P fertilizer use compared with soil-based P management.The average soil Olsen-P level in China only needs to be maintained at 17 mg kg^(-1) to achieve high crop yields.Our results provide a firm basis for government to issue-relevant policies for sustainable P management in China.

Measurement of Shear Stress Acting on Flat Plate Using Oil Film Interferometry

Measurements of frictional resistance play an important role in engineering practice. There are several types of air resistance acting on an aircraft, for example. One of them, frictional resistance, accounts for half of the air resistance. Oil film interferometry is one of methods for measuring the frictional resistance. Oil dropped on an object is thinly stretched by the frictional resistance. The bright and dark fringe pattern is generated when monochromatic light is applied to the oil film. The gradient of the oil thickness decreases with the lapse of time, and thus the spacing between neighboring the dark lines increases. The rate at which the spacing increases is proportional to the frictional resistance. In this study, the frictional resistance acting on a small area on a plate was measured and compared with the theoretical value. As a result, these results qualitatively agree well with each other.

Agricultural remote sensing big data:Management and applications

Big data with its vast volume and complexity is increasingly concerned, developed and used for all professions and trades. Remote sensing, as one of the sources for big data, is generating earth-observation data and analysis results daily from the platforms of satellites, manned/unmanned aircrafts, and ground-based structures. Agricultural remote sensing is one of the backbone technologies for precision agriculture, which considers within-field variability for site-specific management instead of uniform management as in traditional agriculture. The key of agricultural remote sensing is, with global positioning data and geographic information, to produce spatially-varied data for subsequent precision agricultural operations. Agricultural remote sensing data, as general remote sensing data, have all characteristics of big data. The acquisition, processing, storage, analysis and visualization of agricultural remote sensing big data are critical to the success of precision agriculture. This paper overviews available remote sensing data resources, recent development of technologies for remote sensing big data management, and remote sensing data processing and management for precision agriculture. A five-layer-fifteen- level （FLFL） satellite remote sensing data management structure is described and adapted to create a more appropriate four-layer-twelve-level （FLTL） remote sensing data management structure for management and applications of agricultural remote sensing big data for precision agriculture where the sensors are typically on high-resolution satellites, manned aircrafts, unmanned aerial vehicles and ground-based structures. The FLTL structure is the management and application framework of agricultural remote sensing big data for precision agriculture and local farm studies, which outlooks the future coordination of remote sensing big data management and applications at local regional and farm scale.

Deformation behaviors of magnesium alloy AZ31 sheet in cold deep drawing

To investigate how the popular magnesium alloy AZ31 sheet(aluminum 3%,zinc 1%)behaves in cold working,deep drawing experiments at room temperature,along with finite element(FE)simulation,were performed on the cold forming sheet of the AZ31 alloy after being annealed under various conditions.The activities were focused on the fracture pattern,limit drawing ratio(LDR),deformation load,thickness distribution,anisotropic effect,as well as the influences of the annealing conditions and tool configuration on them.The results display that punch shoulder radius instead of die clearance,has much influence on the thickness distribution.The anisotropy is remarkable in cold working,which adversely impacts the LDR.The fracture often happens on the side wall at an angle to axis of the deformed specimen.The results also imply that the LDR for the material under present experimental conditions is 1.72,and annealing the material at 450 ℃ for 1 h may be preferable for the cold deep drawing.

Multispectral imaging systems for airborne remote sensing to support agricultural production management

This study investigated three different types of multispectral imaging systems for airborne remote sensing to support management in agricultural application and production.The three systems have been used in agricultural studies.They range from low-cost to relatively high-cost,manually operated to automated,multispectral composite imaging with a single camera and integrated imaging with custom-mounting of separate cameras.Practical issues regarding use of the imaging systems were described and discussed.The low-cost system,due to band saturation,slow imaging speed and poor image quality,is more preferable to slower moving platforms that can fly close to the ground,such as unmanned autonomous helicopters,but not recommended for low or high altitude aerial remote sensing on fixed-wing aircraft.With the restriction on payload unmanned autonomous helicopters are not recommended for high-cost systems because they are typically heavy and difficult to mount.The system with intermediate cost works well for low altitude aerial remote sensing on fixed-wing aircraft with field shapefile-based global positioning triggering.This system also works well for high altitude aerial remote sensing on fixed-wing aircraft with global positioning triggering or manually operated.The custom-built system is recommended for high altitude aerial remote sensing on fixed-wing aircraft with waypoint global positioning triggering or manually operated.

Rangelands of Central Asia:challenges and opportunities

Rangelands of Central Asia (referring to Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan and Uzbekistan in this study), the largest contiguous area of grazed land in the world, serve as an important source of livelihood for pastoral and agro-pastoral communities in this region. They also play an important role in absorbing CO2 as a global carbon sink. However, unsustainable management of rangelands has led to their degradation hugely by downgrading their potential agro-ecological, environmental and socio-economical roles. This paper reviewed the rangeland degradation in Central Asia, a topic which so far has received only scant coverage in the international scientific literature. It also provided examples of successful experiences and outlined possible options that land managers can adopt to enhance the sustainable management of these vast degraded rangelands. The experiences and lessons described in this paper may also be relevant for other degraded rangeland areas, especially in the developing countries. The causes of rangeland degradation within the Central Asian region are numerous, complex and inter-related. Therefore, while addressing the factors associated with improper rangeland management may shed some light on the causes of rangeland degradation, the scope of this paper would not be all-encompassing for the major causes of degradation. There is a need to develop and widely apply the viable and locally accepted and adapted packages of technical, institutional and policy options for sustainable rangeland management. Incentivizing the collective action of small-scale pastoralists who group together to facilitate access to remote pastures can reduce the degree of overgrazing within community pastures, such as those near the settlements. We also found that migratory grazing through pooling of resources among small-scale pastoralists can increase household income. After their independence, most Central Asian countries adopted various rangeland tenure arrangements. However, the building of enhanced capacities of pasture management and effective local rangeland governance structures can increase the likelihood, which will be sustainable and equitable. Finally, this paper presented several promising technical options, aiming at reversing the trend of rangeland degradation in Central Asia.

Effect of Bacillus amyloliquefaciens and Bacillus subtilis on fermentation, dynamics of bacterial community and their functional shifts of whole-plant corn silage

Background:Bacillus amyloliquefaciens(BA)and Bacillus subtilis(BS)are usually used as feed supplements directly or bacterial inoculants in biological feeds for animals.However,few research have reported the effects of BA and BS on fermentation characteristics and bacterial community successions of whole-plant corn silage during ensiling.If the BA and BS inoculants have positive effects on silages,then they could not only improve fermentation characteristics,but also deliver BA or BS viable cells to ruminants,which would play its probiotic effect.Therefore,the objectives of this study were to investigate the effects of BA and BS on the fermentation,chemical characteristics,bacterial community and their metabolic pathway of whole-plant corn silage.Results:Freshly chopped whole-plant corn was inoculated without or with BA and BS,respectively,and ensiled for1,3,7,14 and 60 d.Results showed that BA and BS inoculations increased lactic acid concentrations of whole-plant corn silages compared with control,and BA inoculation decreased acetic acid concentrations,whereas BS inoculation decreased fiber contents and increased crude protein(CP)content.Higher water-soluble carbohydrate contents and lower starch contents were observed in BA-and BS-inoculated silages compared with that in control.The decreased CP content and increased non-protein nitrogen content were observed in BA-inoculated silage,which was consistent with the higher amino acid metabolism abundances observed in BA-inoculated silage.In addition,it was noteworthy that BA and BS inoculations increased the metabolism of cofactors and vitamins,and decreased the relative abundances of drug resistance:antimicrobial pathways.We also found that the bacterial metabolism pathways were clearly separated into three clusters based on the ensiling times of whole-plant corn silage in the present study.There were no significant differences in bacterial community compositions among the three groups during ensiling.However,BA and BS inoculations decreased the relative abundances of undesirable bacteria such as Acetobacter and Acinetobacter.Conclusion:Our findings suggested that the BS strain was more suitable as silage inoculants than the BA strain in whole-plant corn silage in this study.

Development and evaluation of low-altitude remote sensing systems for crop production management

Precision agriculture accounts for within-field variability for targeted treatment rather than uniform treatment of an entire field.It is built on agricultural mechanization and state-of-the-art technologies of geographical information systems(GIS),global positioning systems(GPS)and remote sensing,and is used to monitor soil,crop growth,weed infestation,insects,diseases,and water status in farm fields to provide data and information to guide agricultural management practices.Precision agriculture began with mapping of crop fields at different scales to support agricultural planning and decision making.With the development of variable-rate technology,precision agriculture focuses more on tactical actions in controlling variable-rate seeding,fertilizer and pesticide application,and irrigation in real-time or within the crop season instead of mapping a field in one crop season to make decisions for the next crop season.With the development of aerial variable-rate systems,low-altitude airborne systems can provide high-resolution data for prescription variable-rate operations.Airborne systems for multispectral imaging using a number of imaging sensors(cameras)were developed.Unmanned aerial vehicles(UAVs)provide a unique platform for remote sensing of crop fields at slow speeds and low-altitudes,and they are efficient and more flexible than manned agricultural airplanes,which often cannot provide images at both low altitude and low speed for capture of high-quality images.UAVs are also more universal in their applicability than agricultural aircraft since the latter are used only in specific regions.This study presents the low-altitude remote sensing systems developed for detection of crop stress caused by multiple factors.UAVs,as a special platform,were discussed for crop sensing based on the researchers'studies.

乙酰化半纤维素用于提高涂布纸张的性能

从云杉中经热水抽提出的聚半乳糖葡萄糖甘露糖(GGM)乙酰化后具有一定水溶性。将其涂布于食品包装纸上,结果表明GGM和乙酰化GGM均可提高食品包装纸的力学性能,且乙酰化GGM对力学性能的作用更好,涂有GGM和乙酰化GGM的纸有很好的耐油性能,且涂乙酰化GGM比涂GGM的纸具有更好的耐油性。