Fruit quality of ‘Gala’ and ‘Fuji’ apples cultivated under different environmental conditions

Argenta, Luiz Carlos; Amarante, Cassandro Vidal Talamini do; Freitas, Sérgio Tonetto de; Brancher, Thyana Lays; Nesi, Cristiano Nunes; Mattheis, James P.

doi:10.1016/j.scienta.2022.111195

Cited by 17 publications

(6 citation statements)

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“…Several factors can impact the internal quality of an apple, including genetics, environmental factors, and post-harvest handling practices [65][66][67]. Genetics plays a critical role in determining the natural sugar and acid content of the apple, as well as its texture and aroma.…”

Section: Internal Quality Parametersmentioning

confidence: 99%

Analyzing the Quality Parameters of Apples by Spectroscopy from Vis/NIR to NIR Region: A Comprehensive Review

Grabska

Beć

Ueno

et al. 2023

Foods

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Spectroscopic methods deliver a valuable non-destructive analytical tool that provides simultaneous qualitative and quantitative characterization of various samples. Apples belong to the world’s most consumed crops and with the current challenges of climate change and human impacts on the environment, maintaining high-quality apple production has become critical. This review comprehensively analyzes the application of spectroscopy in near-infrared (NIR) and visible (Vis) regions, which not only show particular potential in evaluating the quality parameters of apples but also in optimizing their production and supply routines. This includes the assessment of the external and internal characteristics such as color, size, shape, surface defects, soluble solids content (SSC), total titratable acidity (TA), firmness, starch pattern index (SPI), total dry matter concentration (DM), and nutritional value. The review also summarizes various techniques and approaches used in Vis/NIR studies of apples, such as authenticity, origin, identification, adulteration, and quality control. Optical sensors and associated methods offer a wide suite of solutions readily addressing the main needs of the industry in practical routines as well, e.g., efficient sorting and grading of apples based on sweetness and other quality parameters, facilitating quality control throughout the production and supply chain. This review also evaluates ongoing development trends in the application of handheld and portable instruments operating in the Vis/NIR and NIR spectral regions for apple quality control. The use of these technologies can enhance apple crop quality, maintain competitiveness, and meet the demands of consumers, making them a crucial topic in the apple industry. The focal point of this review is placed on the literature published in the last five years, with the exceptions of seminal works that have played a critical role in shaping the field or representative studies that highlight the progress made in specific areas.

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Section: Internal Quality Parametersmentioning

confidence: 99%

Analyzing the Quality Parameters of Apples by Spectroscopy from Vis/NIR to NIR Region: A Comprehensive Review

Grabska

Beć

Ueno

et al. 2023

Foods

View full text Add to dashboard Cite

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“…Results showed EVI's efficacy in estimating AOP, with a trend towards earlier season starts in the region. Argenta et al 32 investigated the influence of environmental conditions on apple quality in Brazil. Temperature, chilling hours, and the number of days from bloom to harvest varied across sites.…”

Section: Related Workmentioning

confidence: 99%

Intelligent Orchard monitoring: IoT integrated Fuzzy Logic based real-time apple disease prediction encompassing environmental factors

Sheel,

Sharma

2024

JIST

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This work presents a novel methodology for apple disease detection based on environmental factors, integrating the capabilities of the Internet of Things (IoT). Advanced sensors are placed in apple orchards to continuously monitor various environmental factors such as temperature, humidity, pressure, and light. The data gathered from these sensors is analyzed using the Mamdani fuzzy inference system (MFIS) to predict possible apple diseases. The use of advanced sensors, cloud storage, and the Mamdani fuzzy inference system proved effective in timely disease detection along with inclusion of environmental factors. According to predicted outcomes, a recommendation system is also presented in the mobile application. Initial experiments in Shimla, India, showed that this system is effective and efficient, with minimal delays in different stages. The study also compares this new approach with current advanced methods in disease detection.

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“…An increase of mean AT since FB to harvest date resulted in a shorter fruit growing season for 'Fuji' and 'Gala' apples, analyzing different growing sites and seasons (Argenta et al, 2022), and for 'Conference' pears, comparing growing seasons (Lysiak, 2022). Argenta et al (2022) noted that the effect of site on the growing season length was greater for 'Gala' than 'Fuji' apples, indicating a cultivar and/or maturation date of fruit response to spring temperature.…”

Section: Feature Selectionmentioning

confidence: 99%

Harvest date estimation of ‘Gala’ apples based on environment temperature using artificial intelligence

González

Sepúlveda

Yuri

2023

Chil. j. agric. res.

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Agroclimatic variables in different time windows were analyzed using Artificial Intelligence techniques to estimate the fruit growing season extension and harvest start date for 'Gala' apples (Malus domestica (Suckow) Borkh.) Meteorology and phenology data were collected from five orchards in Central Chile, between 2004 and 2019. The attributes derived from air temperature during the first days of fruit growing season showed the high relationship with harvest start date: The number of hours below 18 °C from full bloom to 35 d after (R = 0.9) and growing degree hours accumulated from full bloom to 45 d (R = -0.84). Different models were developed with these attributes. Simple and multiple linear regression models were the most accurate for explain the length of the total fruit growth period until harvest. The 35 d after full bloom time window was the most effective, with an R 2 = 0.82, for estimating harvest start date of 'Gala' apples. These results contribute to the apple growers demand to schedule fruit harvest and processing, especially in a climate change scenario.

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Fruit quality of ‘Gala’ and ‘Fuji’ apples cultivated under different environmental conditions

Cited by 17 publications

References 50 publications

Analyzing the Quality Parameters of Apples by Spectroscopy from Vis/NIR to NIR Region: A Comprehensive Review

Analyzing the Quality Parameters of Apples by Spectroscopy from Vis/NIR to NIR Region: A Comprehensive Review

Intelligent Orchard monitoring: IoT integrated Fuzzy Logic based real-time apple disease prediction encompassing environmental factors

Harvest date estimation of ‘Gala’ apples based on environment temperature using artificial intelligence

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Fruit quality of ‘Gala’ and ‘Fuji’ apples cultivated under different environmental conditions

Cited by 17 publications

References 50 publications

Analyzing the Quality Parameters of Apples by Spectroscopy from Vis/NIR to NIR Region: A Comprehensive Review

Analyzing the Quality Parameters of Apples by Spectroscopy from Vis/NIR to NIR Region: A Comprehensive Review

Intelligent Orchard monitoring: IoT integrated Fuzzy Logic based real-time apple disease prediction encompassing environmental factors

Harvest date estimation of &#8216;Gala&#8217; apples based on environment temperature using artificial intelligence

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Harvest date estimation of ‘Gala’ apples based on environment temperature using artificial intelligence