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2021 ◽  
Vol 14 (1) ◽  
pp. 79
Author(s):  
Abdulrazag Mohamed Etelawi

This study aims to know the time between apple production and marketing to help decision makers for apple products at Washington, in the USA. In order to do so, it needs an application of OLS for a linear and non- linear model for diameter apples and length apple over the years 2010-2013. The diameter or size apple linear model includes DAFB, FB, latitude, mean80, years, and FB. The results indicated that all independent variables are significant and Adj R-squared explains about 75 percent of diameter apple. While the length apple linear model includes DAFB, years, FB, longitude, elevation, latitude, mean120, and mean70.The resulted sate that all independent variables are significant and Adj-R-squares illuminates about 84percent of size apple. Moreover, Actual value and predicted values for linear and nonlinear models are very close. Thus, those models can help farmers make a good decision for apple industry, and achieve to get best size and length for their apple crop.


2021 ◽  
Vol 12 ◽  
Author(s):  
Jiewen Guan ◽  
Alison Lacombe ◽  
Bhargavi Rane ◽  
Juming Tang ◽  
Shyam Sablani ◽  
...  

Listeria monocytogenes (L. monocytogenes) causes an estimated 1600 foodborne illnesses and 260 deaths annually in the U.S. These outbreaks are a major concern for the apple industry since fresh produce cannot be treated with thermal technologies for pathogen control before human consumption. Recent caramel apple outbreaks indicate that the current non-thermal sanitizing protocol may not be sufficient for pathogen decontamination. Federal regulations provide guidance to apple processors on sanitizer residue limits, organic production, and good manufacturing practices (GMPs). However, optimal methods to control L. monocytogenes on fresh apples still need to be determined. This review discusses L. monocytogenes outbreaks associated with caramel apples and the pathogen’s persistence in the environment. In addition, this review identifies and analyzes possible sources of contaminant for apples during cold storage and packing. Gaseous interventions are evaluated for their feasibility for L. monocytogenes decontamination on apples. For example, apple cold storage, which requires waterless interventions, may benefit from gaseous antimicrobials like chlorine dioxide (ClO2) and ozone (O3). In order to reduce the contamination risk during cold storage, significant research is still needed to develop effective methods to reduce microbial loads on fresh apples. This requires commercial-scale validation of gaseous interventions and intervention integration to the current existing apple cold storage. Additionally, the impact of the interventions on final apple quality should be taken into consideration. Therefore, this review intends to provide the apple industry suggestions to minimize the contamination risk of L. monocytogenes during cold storage and hence prevent outbreaks and reduce economic losses.


Plant Disease ◽  
2021 ◽  
Author(s):  
Michael Bradshaw ◽  
Holly Bartholomew ◽  
Franz Johann Lichtner ◽  
Verneta Gaskins ◽  
Wayne Jurick

Apples (Malus domestica, Rosaceae) are one of the most widely grown and economically valuable fruits worldwide. In Hood River County, Oregon in 1991 decayed apples exhibiting blue mold signs and symptoms were collected and spores from the causal agent of the disease were isolated. The decayed area of the infected apples was brown colored with soft, decayed tissue, which had bluish-green colored spores on the fruit surface. The whole genome of this isolate was sequenced (GenBank number: JYNM00000000) and it was originally identified as Penicillium solitum strain RS1 (Yu et al. 2016). Subsequent genome-wide species-level investigations showed higher homology to P. polonicum. Therefore, we taxonomically and phylogenetically reevaluated the fungus in question. Colonies were analyzed growing on potato dextrose agar (PDA), Czapek yeast autolysate agar (CYA) and malt extract agar (MEA) at 25°C. Colonies on PDA were blue-green and growth was moderately deep and raised at the center with low margins. Colonies on CYA were blue-green. The range of the colony diameter after 7 days at 25ºC was 24-27 mm on CYA and 20-25 mm on MEA. Colony reverse color on CYA was yellow-brown and on MEA was cream. Conidiophores were terverticillate. Stipes were septate with smooth walls and measured 62-250 × 3-5 µm, x̄ = 111.1 × 3.8 µm with 1-4 branches per stipe. Branches measured 8-25 × 2-6 µm, x̄ = 4.9 × 16.3 µm with 2-4 metulae per branch. Metulae measured 7-14 × 2-5 µm, x̄ = 10.1 × 3.6 µm with 1-3 phialides per metulae. Phialides were flask shaped and measured 5-11 × 2-5 µm, x̄ = 7.5 × 3.4 µm. Conidia were globose to subglobose, borne in columns measuring 2.2-5.4 × 2.1-5.3 µm, x̄ = 3.6 × 3.4 µm. Morphologically, the fungal strain RS1 matched the description of Penicillium polonicum K. Zaleski from Bashir et al. (2017), Duduk et al. (2014) and Frisvad and Sampson (2004) with some minor differences. The ITS, TUB and RpB2 sequences of the strain RS1 were extracted from GenBank accession number JYNM00000000. The sequences were then submitted for nucleotide BLAST (NCBI) analysis in GenBank and evaluated. The ITS sequence aligned 100% with the type specimen (CBS 222.28) of P. polonicum (GenBank number: NR_103687). The TUB sequence aligned over 99% with P. polonicum (GenBank numbers: MK450898, MK450935, MK450899). The RpB2 sequences aligned 99.9% or higher with multiple P. polonicum specimens deposited in CBS and CMV (GenBank numbers: MK450847, MK450846, JN985414 and JN985415). Koch’s postulates were conducted. Ten apples were wounded with the point of a 16-penny nail, and 10ul of a conidial suspension adjusted to 106 conidia-distilled water/tween solution was added to the wound. Ten separate apples served as a control that were wounded and 10ul of sterile Tween treated water was used to simulate inoculation. None of the control apples developed signs or symptoms of the disease. The inoculated apples all developed typical blue mold symptoms. The fungus was reisolated from the fruit and deemed to be morphologically identical to those of the original RS1, P. polonicum isolate. To the best of our knowledge this is the first report of blue mold caused by P. polonicum in the USA on apples (Farr and Rossman 2021). This information is important for the apple industry for which blue mold is a major problem.


Foods ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 1980
Author(s):  
Kyle Dunno ◽  
Isabel Stoeckley ◽  
Matthew Hofmeister

Postharvest damage, leading to loss and waste, continues to be a significant problem in the fresh produce industry. Trays, designed to reduce fruit-to-fruit contact, are utilized by the apple industry to minimize bruising of whole apples. During distribution, packaged apples are subjected to various supply chain hazards, which may lead to bruising damage. Currently, molded fiber (MF) and expanded polystyrene (EPS) trays transport whole apples from the packhouse to the retail outlet. Mechanical shock, by free-fall drop method, was used to evaluate the performance differences between the two trays and quantify the bruising characteristics of the apples. Results showed that the EPS trays provided better shock protection to the apple as compared to the MF tray, reducing the impact acceleration by more than 70%. Additionally, the bruise susceptibility was 40% less for the apples packaged inside the EPS trays, regardless of drop height. However, apples packaged in the middle layer trays were most susceptible to bruising damage, regardless of tray type.


PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0254820
Author(s):  
Yu Sun ◽  
Yonghua Lu ◽  
Zichun Wang ◽  
Mingyue Li

The global population is rapidly increasing, the arable land area is losing in a large scale, and the water supply capacity is limited. Meanwhile, China is in a critical period of the transformation of apple industrial structure, and the improvement of apple production efficiency is an important way to increase farmers’ output and income, moderate-scale operation is the inevitable trend in agricultural modernization. However, few studies have explored the production efficiency of the apple industry from the perspective of planting scale. In China, there are seven major apple-producing provinces: Shaanxi, Shandong, Gansu, Henan, Shanxi, Hebei, and Liaoning. Therefore, based on provincial panel data of the seven main apple-producing areas in China, this study used the Malmquist productivity index and data envelopment analysis to measure the efficiency level of the apple industry. At the same time, the threshold regression model was used to analyze the characteristics of the change in apple planting scale and production efficiency. The results showed that apple production efficiency in different regions of China exhibited regional differences and time series fluctuations. Apple planting scale had a "double" threshold effect, and the impact on apple production efficiency showed a "negative effect–positive effect" trend. Therefore, the suggestion is to appropriately adjust the scale of operation, take measures according to local conditions, promote the upgrading of apple production technology, and realize the integration of apple production and sales by using “Internet +.”


2021 ◽  
Vol 4 (2) ◽  
pp. 74-84
Author(s):  
Friday Ogbu Edeh ◽  
Kok Ban Teoh ◽  
Yashene Murugan ◽  
Daisy Mui Hung Kee ◽  
Joey Wong ◽  
...  

Apple has a large customer base in Malaysia because they offer products of superior design and features. The main objective of this study is to determine the contributing factors to Apple’s sustainability in Malaysia’s Information and Communication Technology (ICT) Industry. This study is conducted based on quantitative research with 100 targeted respondents from Malaysia. The findings indicate that the marketing strategies, brand awareness, and customer experience are the major factors of the successful pathway of Apple’s sustainability. The research concludes that Apple Industry should adapt a frequent reengineering approach where the existing and upcoming Apple products will satisfy customer needs.


2021 ◽  
Vol 1 (1) ◽  
pp. 9-13
Author(s):  
Zhongqiang Huang ◽  
Ping Zhang ◽  
Ruigang Liu ◽  
Dongxu Li

The identification of immature apples is a key technical link to realize automatic real-time monitoring of orchards, expert decision-making, and realization of orchard output prediction. In the orchard scene, the reflection caused by light and the color of immature apples are highly similar to the leaves, especially the obscuration and overlap of fruits by leaves and branches, which brings great challenges to the detection of immature apples. This paper proposes an improved YOLOv3 detection method for immature apples in the orchard scene. Use CSPDarknet53 as the backbone network of the model, introduce the CIOU target frame regression mechanism, and combine with the Mosaic algorithm to improve the detection accuracy. For the data set with severely occluded fruits, the F1 and mAP of the immature apple recognition model proposed in this article are 0.652 and 0.675, respectively. The inference speed for a single 416×416 picture is 12 ms, the detection speed can reach 83 frames/s on 1080ti, and the inference speed is 8.6 ms. Therefore, for the severely occluded immature apple data set, the method proposed in this article has a significant detection effect, and provides a feasible solution for the automation and mechanization of the apple industry.


2021 ◽  
Vol 1 (1) ◽  
pp. 9-13
Author(s):  
Zhongqiang Huang ◽  
Ping Zhang ◽  
Ruigang Liu ◽  
Dongxu Li

The identification of immature apples is a key technical link to realize automatic real-time monitoring of orchards, expert decision-making, and realization of orchard output prediction. In the orchard scene, the reflection caused by light and the color of immature apples are highly similar to the leaves, especially the obscuration and overlap of fruits by leaves and branches, which brings great challenges to the detection of immature apples. This paper proposes an improved YOLOv3 detection method for immature apples in the orchard scene. Use CSPDarknet53 as the backbone network of the model, introduce the CIOU target frame regression mechanism, and combine with the Mosaic algorithm to improve the detection accuracy. For the data set with severely occluded fruits, the F1 and mAP of the immature apple recognition model proposed in this article are 0.652 and 0.675, respectively. The inference speed for a single 416×416 picture is 12 ms, the detection speed can reach 83 frames/s on 1080ti, and the inference speed is 8.6 ms. Therefore, for the severely occluded immature apple data set, the method proposed in this article has a significant detection effect, and provides a feasible solution for the automation and mechanization of the apple industry.


2021 ◽  
Vol 7 (5) ◽  
pp. 246-250
Author(s):  
Bakhtaver Hassan ◽  
Mahua Bhattacharjee ◽  
Shabir Wani

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