Physiological quality of quinoa seeds submitted to different storage conditions

Souza, FlÃ­via Fernandes de Jesus; Devilla, Ivano Alessandro; Souza, Raniele Tadeu GuimarÃ£es de; Teixeira, Itamar Rosa; Spehar, Carlos Roberto

doi:10.5897/ajar2016-10870

Cited by 19 publications

(4 citation statements)

References 19 publications

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“…Quinoa seed of initial seed quality of 80% germination and 8% moisture content can be stored hermetically for six months without loss of viability under ambient conditions (25-40°C and 50-60% RH) while after one-year storage germination declines to 15% [231]. Quinoa seed maintains physiological quality for longer periods (up to 300 days) in impermeable packaging and under low temperature (4 ± 2°C) [232]. It is also reported that quinoa seed with 5% moisture content at 5°C can be stored for 8 months with maximum viability [233], and this moisture content is also ideal for long term storage.…”

Section: Detection Of Saponins In Quinoamentioning

confidence: 99%

Quinoa Phenotyping Methodologies: An International Consensus

Stanschewski¹,

Rey²,

Fiene³

et al. 2021

Plants

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Quinoa is a crop originating in the Andes but grown more widely and with the genetic potential for significant further expansion. Due to the phenotypic plasticity of quinoa, varieties need to be assessed across years and multiple locations. To improve comparability among field trials across the globe and to facilitate collaborations, components of the trials need to be kept consistent, including the type and methods of data collected. Here, an internationally open-access framework for phenotyping a wide range of quinoa features is proposed to facilitate the systematic agronomic, physiological and genetic characterization of quinoa for crop adaptation and improvement. Mature plant phenotyping is a central aspect of this paper, including detailed descriptions and the provision of phenotyping cards to facilitate consistency in data collection. High-throughput methods for multi-temporal phenotyping based on remote sensing technologies are described. Tools for higher-throughput post-harvest phenotyping of seeds are presented. A guideline for approaching quinoa field trials including the collection of environmental data and designing layouts with statistical robustness is suggested. To move towards developing resources for quinoa in line with major cereal crops, a database was created. The Quinoa Germinate Platform will serve as a central repository of data for quinoa researchers globally.

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Section: Detection Of Saponins In Quinoamentioning

confidence: 99%

Quinoa Phenotyping Methodologies: An International Consensus

Stanschewski¹,

Rey²,

Fiene³

et al. 2021

Plants

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“…Gelmond et al applied accelerated aging to obtain six different levels of vigor of sorghum seeds from an identical lot [6]. Souza et al also adopted an accelerated aging test during their study of the physiological quality of quinoa seeds under different storage conditions [7].…”

Section: Introductionmentioning

confidence: 99%

Identification of Maize Kernel Vigor under Different Accelerated Aging Times Using Hyperspectral Imaging

et al. 2018

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Seed aging during storage is irreversible, and a rapid, accurate detection method for seed vigor detection during seed aging is of great importance for seed companies and farmers. In this study, an artificial accelerated aging treatment was used to simulate the maize kernel aging process, and hyperspectral imaging at the spectral range of 874–1734 nm was applied as a rapid and accurate technique to identify seed vigor under different accelerated aging time regimes. Hyperspectral images of two varieties of maize processed with eight different aging duration times (0, 12, 24, 36, 48, 72, 96 and 120 h) were acquired. Principal component analysis (PCA) was used to conduct a qualitative analysis on maize kernels under different accelerated aging time conditions. Second-order derivatization was applied to select characteristic wavelengths. Classification models (support vector machine−SVM) based on full spectra and optimal wavelengths were built. The results showed that misclassification in unprocessed maize kernels was rare, while some misclassification occurred in maize kernels after the short aging times of 12 and 24 h. On the whole, classification accuracies of maize kernels after relatively short aging times (0, 12 and 24 h) were higher, ranging from 61% to 100%. Maize kernels with longer aging time (36, 48, 72, 96, 120 h) had lower classification accuracies. According to the results of confusion matrixes of SVM models, the eight categories of each maize variety could be divided into three groups: Group 1 (0 h), Group 2 (12 and 24 h) and Group 3 (36, 48, 72, 96, 120 h). Maize kernels from different categories within one group were more likely to be misclassified with each other, and maize kernels within different groups had fewer misclassified samples. Germination test was conducted to verify the classification models, the results showed that the significant differences of maize kernel vigor revealed by standard germination tests generally matched with the classification accuracies of the SVM models. Hyperspectral imaging analysis for two varieties of maize kernels showed similar results, indicating the possibility of using hyperspectral imaging technique combined with chemometric methods to evaluate seed vigor and seed aging degree.

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“…Leaf length, breadth, thickness, petiole length, and area were computed using the averages of 30 measurements (10 plants per plot for each of the 3 different leaf and petiole sizes). The harvest was done manually, panicles were carefully removed to minimize grain spilling, then the panicles were threshed by a mechanical thresher, seeds were cleaned, and the seeds were held in an electric oven at 100 o C for 48 hours to regulate the moisture content to 12 percent, as advised by (Biru, 1978;de Jesus Souza et al, 2016). A digital caliper was used to measure the diameter of the stem and the thickness of the leaves (Digimatic Solar DC-S15 m, Mitutoyo, Japan).…”

Section: Data Collection and Measurementsmentioning

confidence: 99%

Morphological characterization, variability, and diversity among amaranth genotypes from Ethiopia

Yeshitila

Gedebo

Olango

et al. 2023

Genet Resour Crop Evol

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Amaranths are dicotyledonous plants with high yield potential, a high mineral uptake rate, short days, and high adaptability. It has been extensively investigated as a model C4 plant. The objectives of the current study were to estimate genetic diversity, heritability, and genetic advance for yield and yield-contributing traits of amaranth genotypes based on agro-morphological traits. The study was done on one hundred twenty amaranth genotypes planted over two growing seasons using an alpha lattice design with two replications. The analysis of variance showed the presence of signi cant variation (P ≤ 0.001) between genotypes, years, and their interactions for most of the studied traits. Among the genotypes, based on their performance, promising genotypes KAZ-059, 225713, KAZ-058 and KEN-019, 242530, and 212890 exhibited higher leaf area, branch number, and plant height at maturity, and plant height at owering. Selection based on these traits could be effective for amaranth leaf yield improvement. On the other hand, KEN-016, KEN-020, KAZ-060, KEN-010, KEN-018, and 22571 produced high grain yield along with better leaf area, axillary in orescence length, terminal in orescence lateral length, terminal in orescence stalk length, grain sink lling rate, and thousand seed weight, indicating phenotypic-based selection on these traits might be reliable for grain yield improvement in amaranth genotypes. These genotypes were chosen as a result due to their high yield potential and good yield-related traits. Future selection efforts for amaranth should therefore continue to evaluate the genotypes under various environmental conditions. These genotypes were selected as a result because they had a high potential for yield and desirable traits that might boost yield.Amaranth is a high-yielding, climate-smart, nutrient-rich plant that is essential for meeting rising world demand while also reducing dependency on a few cereal crops. The potential of both native and exotic species for food or industrial must be harnessed, or new types must be created (Janovská et al., 2012). Therefore, amaranth has become more important in recent years as a substitute crop for other major cereals. The amaranth plant not only thrives in a variety of climates (Lakshmi & Vimala, 2000), but it is also one of the few exceptionally nutritionally multi-purpose crops. It is used as a vegetable, cereal, medicinal plant, dye plant, forage plant, ornamental plant, as well as a fuel source (Mlakar et al., 2009;Sheikh & Singh, 2013). Historically an important component of African agriculture, amaranth is currently farmed in Ethiopia and other East African nations, mostly as a vegetable (Emire & Arega, 2012;Corke et al., 2016). Due to the great nutritional value of both its leaves and seeds, amaranth is a superior food source value (Barba de la Rosa et al., 1992;Fasuyi et al., 2007). The protein, calcium, dietary ber, and gluten-free starch content of the seeds is a higher and better balance of essential amino acids than that of grains and legumes (Singhal & Ku...

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Physiological quality of quinoa seeds submitted to different storage conditions

Cited by 19 publications

References 19 publications

Quinoa Phenotyping Methodologies: An International Consensus

Quinoa Phenotyping Methodologies: An International Consensus

Identification of Maize Kernel Vigor under Different Accelerated Aging Times Using Hyperspectral Imaging

Morphological characterization, variability, and diversity among amaranth genotypes from Ethiopia

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