Ethanol production and mitochondrial-related gene expression of maize (Zea mays) seed during storage

Chaengsakul, Chalisa; Onwimol, Damrongvudhi; Kongsil, Pasajee; Suwannarat, Sawita

doi:10.1016/s2095-3119(19)62558-x

Cited by 11 publications

(5 citation statements)

References 33 publications

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“…16,17 After the PM time, seed deterioration would decrease seed vigor if they were not harvested in time. 34 Previous research has shown that in-time harvest could obtain maximum seed vigor in rice and in later-maturity maize varieties. 19,21,35 In this work, we extended this conclusion from the later-maturity maize varieties to the early maturity varieties.…”

Section: Discussionmentioning

confidence: 99%

“…During seed development, seed vigor increased when dry matter increased, and it reached a maximum at a stage close to the PM time 16,17 . After the PM time, seed deterioration would decrease seed vigor if they were not harvested in time 34 . Previous research has shown that in‐time harvest could obtain maximum seed vigor in rice and in later‐maturity maize varieties 19,21,35 .…”

Section: Discussionmentioning

confidence: 99%

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The ideal harvest time for seed production in maize (Zea mays L.) varieties of different maturity groups

Han

Yang

et al. 2022

J Sci Food Agric

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BACKGROUND The correct time for harvesting is a key factor contributing to the production of high‐quality maize seeds. We conducted field experiments to harvest seeds at 11 developmental stages for 3 years, to investigate seed vigor traits in three early maturity maize varieties and two late maturity varieties in one location. RESULTS Significant correlations (r = 0.72 ~ 0.89) were found among six seed‐related traits: standard germination (SG), accelerated aging germination (AAG), cold test germination (CTG), hundred‐seed weight (HSW), seed moisture content (SMC), and ≥ 10 °C accumulated temperature from pollination to harvest (AT10). Analysis of variance showed that harvest stage, year, and variety had significant effects on all traits, and harvest stage displayed the greatest effect. The responses of SG, AAG, CTG, HSW and SMC to harvest stage fitted quadratic models, and AT10 fitted a linear model. From the quadratic models, an ideal harvest time (IHT, the final date to reach maximum SG, AAG, and CTG) could be calculated for each variety. The three early maturity varieties reached their IHT at 54.94–58.44 days after pollination (DAP); the two later maturity varieties reached IHT several days later (at 59.87–59.90 DAP). The early maturity varieties consistently required less AT10 to reach the IHT than the later maturity varieties. However, all of the varieties reached the IHT at similar SMC levels of about 35%. CONCLUSION The later maturity varieties reached the IHT at later DAPs when they acquired more AT10 than the early maturity varieties but both reached it at similar SMC levels. © 2022 Society of Chemical Industry.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

The ideal harvest time for seed production in maize (Zea mays L.) varieties of different maturity groups

Han

Yang

et al. 2022

J Sci Food Agric

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“…In the past, seed scientists have used two or three laboratory-based indirect methods together to determine seed vigor accurately, including the stress test, electrical conductivity test and seed growth rate test [2,27,28]. Other methods, such as fast ethanol assay, do not consider seedling performance but rely on expensive sensors and have not been reported to be successful with rice seed [29,30].…”

Section: Discussionmentioning

confidence: 99%

An Automatic Method for Rice Seed Vigor Classification Via Radicle Emergence Test Using Image Processing, Curve Fitting and Clustering Method

Onwimol

Phimcharoen

Sermwuthisarn

et al. 2021

Preprint

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Background: Rice seed vigor classification is important for seed storage management by seed producers and by farmers planning their cultivation activities. Field emergence is a direct method of seed vigor testing but is laborious, time-consuming and subjective. The saturated salt accelerated aging (SSAA) test is often used as an indirect method for rice seed vigor classification in the laboratory. However, the results from such a method are often imprecise. This paper presents the SV-RICE package, a simple, cost-efficient and flexible procedure that utilizes computer image analysis for high-throughput, automatic rice seed vigor classification. SV-RICE consists of 4 steps: dynamic imaging, image processing, curve fitting and clustering. Seed vigor has been classified based on radicle emergence indices, such as maximum radicle emergence (MRET), mean radicle emergence time (MaxRE), radicle emergence speed (t50), uniformity of radicle emergence (U7525), and area under the curve of the radicle emergence fitted curve (AUC).Results: Parameters used to classify rice seed vigor, such as MRET, U7525 and t50, were strong negative correlation with the SSAA test. The germination time of 90 hours, at 25°C, was sufficient for effective classification based on SV-RICE, whereas the SSAA test takes approximately 400 hours to complete. The SV-RICE software algorithm was set up to be especially suitable for assessment after 6 months under controlled atmosphere storage (at 15°C and 37%RH in hermetic bag). The study showed that SV-RICE could unambiguously classify 40 Indica rice samples with different varieties, production years, production sites, storage times and storage conditions compared to the SSAA test.Conclusions: This paper confirmed the accuracy, reproducibility and flexibility of the SV-RICE package for automatic seed vigor classification of Oryza sativa seeds; however, it is likely applicable to other species as a viable alternative to current methods that require more time and are less precise.

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“…In the past, seed scientists have used two or three laboratory-based indirect methods together to accurately determine seed vigor, including the stress test, electrical conductivity test and seed growth rate test [2,31,33]. Other methods, such as fast ethanol assays, do not consider seedling performance but rely on expensive sensors and have not been reported to be successful with rice seeds [34,35].…”

Section: Discussionmentioning

confidence: 99%

An Automatic Method for Rice Seed Vigor Classification Via Radicle Emergence Testing Using Image-Processing, Curve-Fitting and Clustering Methods

Onwimol

Sermwuthisarn

Phimcharoen

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

Background: Rice seed vigor classification is important for seed storage management by seed producers and by farmers while planning their cultivation activities. Field emergence is a direct method of seed vigor testing but is laborious, time-consuming and subjective. The accelerated aging (AA) test is often used as an indirect method for rice seed vigor classification in the laboratory. However, the results from this method are often imprecise. This paper presents the SVRice package, a simple, cost-efficient and flexible procedure that utilizes computer image analysis for high-throughput, automatic rice seed vigor classification. SVRice consists of 4 steps: dynamic imaging, image processing, curve fitting and clustering. Seed vigor was classified based on radicle emergence indices, such as maximum radicle emergence (MaxRE), mean radicle emergence time (MRET), radicle emergence speed (t50), uniformity of radicle emergence (U7525), and area under the curve of the radicle emergence fitted curve (AUC).Results: Parameters used to classify rice seed vigor, such as MRET, U7525 and t50, were strongly negatively correlated with the saturated salt accelerated aging (SSAA) test. A germination time of 90 hours at 25°C was sufficient for effective classification based on SVRice, whereas the SSAA test took approximately 400 hours to complete. The SVRice software algorithm was created to be especially suitable for assessment after 6 months under controlled atmosphere storage (at 15°C and 37% RH in a hermetic bag). The study showed that SVRice could unambiguously classify 40 indica rice samples with different varieties, production years, production sites, storage times and storage conditions compared with the SSAA test.Conclusions: This paper confirmed the accuracy, reproducibility and flexibility of the SVRice package for automatic seed vigor classification of Oryza sativa seeds; moreover, it is also likely applicable to other species as a viable alternative to current methods that require more time and are less precise.

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Ethanol production and mitochondrial-related gene expression of maize (Zea mays) seed during storage

Cited by 11 publications

References 33 publications

The ideal harvest time for seed production in maize (Zea mays L.) varieties of different maturity groups

The ideal harvest time for seed production in maize (Zea mays L.) varieties of different maturity groups

An Automatic Method for Rice Seed Vigor Classification Via Radicle Emergence Test Using Image Processing, Curve Fitting and Clustering Method

An Automatic Method for Rice Seed Vigor Classification Via Radicle Emergence Testing Using Image-Processing, Curve-Fitting and Clustering Methods

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