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Breeding and Genetic Research of Cereal Grain Quality

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A special issue of Agriculture (ISSN 2077-0472). This special issue belongs to the section "Genotype Evaluation and Breeding".

Deadline for manuscript submissions: 25 July 2024 | Viewed by 7762

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Special Issue Editor

Dr. Fawad Ali

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Guest Editor

Centre for Planetary Health and Food Security, Griffith University, Nathan Campus, Brisbane, QLD 4111, Australia
Interests: agronomy and crop production; breeding for food and feed; advanced phenomics tools; genomics for adaptive technology; outcome
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Understanding how inheritance determines the key genetic pattern of cereal-grain-quality traits is the key to improving the grain's nutritional components and milling yields. There is limited knowledge about the gene metric measurements of key desirable grain-quality traits when plant species face biotic and abiotic stress across key developmental stages. The proposed genetic methods and fundamental quantitative genetic models may help us understand the complexity associated with yield reduction across cereal species in response to the environment under which the plants are grown. Further, evaluating grain-quality traits in response to biotic and abiotic stress and evaluating substantial changes in the grain molecular composition of the developing and developed seed helps us find novel pathways.

Therefore, it is important to understand the physiology, genetics, and basic inheritance pattern of cereal species facing biotic and abiotic stress and the possible solutions for future breeding in order to improve grain quality.

This Special Issue deliberates on the concepts, strategies, tools, and techniques of classical genetics and advanced quantitative genetic approaches to measuring the potential of the current cereal genome, including by studying breeding strategies, studying evolution patterns, the discovery of superior alleles, discerning new haplotypes, the assessment of intra- and interspecific genome similarity, and studies of gene expression and gene prediction. Available gene pools in global germplasm collections specifically consisting of wild allied species and local landraces may have the potential to assist in the further improvement of cereals by focusing on grain-quality traits.

The topics of papers we are soliciting include:

Classical breeding;
Molecular breeding;
Quantitative genetics of grain-quality traits;
Allele mining;
Association mapping of grain-quality traits;
Genetic mapping of grain-quality traits;
Pre- and post-harvest scenarios affecting grain-quality traits;
Biotic factors affecting grain quality in cereals;
Abiotic factors affecting grain-quality traits;
Agronomic factors affecting the grain quality in cereals;
Plant physiology and potential relationship with the grain quality;
Carbon partitioning and translocation and their potential impact on grain quality;
Optimization of the milling methods to improve grain quality.

Dr. Fawad Ali
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Agriculture is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

breeding and genetics of cereal grain quality
agronomic factors affecting grain quality
pre- and post-harvest factors affecting grain quality
milling methods
QTL mapping and association mapping of cereal grain quality
allele mining of cereal-grain-quality traits

Published Papers (4 papers)

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Research

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21 pages, 2979 KiB

Open AccessArticle

Optimizing Linseed (Linum usitatissimum L.) Seed Yield through Agronomic Parameter Modeling via Artificial Neural Networks

by Aliakbar Mohammadi Mirik, Mahdieh Parsaeian, Abbas Rohani and Shaneka Lawson

Agriculture 2024, 14(1), 25; https://doi.org/10.3390/agriculture14010025 - 22 Dec 2023

Viewed by 732

Abstract

Linseed (Linum usitatissimum L.), a globally cultivated oilseed crop in high demand, is the focal point of our efforts aimed at improving yield production. The achievement of robust yield outcomes relies on the intricate interplay of various agronomic traits. This study, conducted over two years at a research farm in Iran, presents a comprehensive analysis evaluating diverse agronomic characteristics inherent to different linseed cultivars and hybrids. Essential parameters, including days to emergence, days to flowering, plant height, number of branches, number of capsules per plant, number of seeds per capsule, 1000-seed weight, and seed yield per plant, were examined. For predictive insights into seed yield, machine learning techniques, specifically multilayer perceptron (MLP) and multiple linear regression (MLR), were employed. The analysis of contribution percentages for each agronomic variable to linseed seed yield revealed that the number of capsules per plant emerged as the most influential factor, contributing 30.7% among the considered variables. The results indicated the superiority of MLP over MLR, with RMSE and MAPE values equaling 0.062 g/plant and 3.585%, respectively. Additionally, R² values for training, validation, and test phases exceeded 0.97. Consequently, MLP served as a merit function in the genetic algorithm (GA), targeting the identification of optimal trait levels to maximize linseed yield. The optimization outcomes demonstrated the potential achievement of a yield of 4.40 g/plant. To attain this performance, a set of agronomic characteristic values was proposed by GA, initiating a discussion on genetic modification possibilities. The findings of this study highlight the remarkable efficacy of machine learning tools, particularly neural networks, when paired with evolutionary optimization techniques such as genetic algorithms. These methodologies prove to be invaluable assets in aiding biotechnologists as they strive to enhance the genetic makeup of products for various applications, providing unwavering reliability and invaluable guidance in the pursuit of genetic modification endeavors. Full article

(This article belongs to the Special Issue Breeding and Genetic Research of Cereal Grain Quality)

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19 pages, 3346 KiB

Open AccessArticle

Nutritional and Antinutritional Potentials of Sorghum: A Comparative Study among Different Sorghum Landraces of Tigray, Northern Ethiopia

by Tesfakiros Semere, Yemane Tsehaye, Lijalem Tareke, Ola T. Westengen and Siri Fjellheim

Agriculture 2023, 13(9), 1753; https://doi.org/10.3390/agriculture13091753 - 4 Sep 2023

Cited by 1 | Viewed by 2563

Abstract

Sorghum is one of the staple food crops in Tigray, northern Ethiopia. Despite this, limited research attention was given to the nutritional and antinutritional profiling of sorghum. Thus, this research was initiated to profile and evaluate the variabilities in protein, starch, minerals, flavonoid, tannin, and antioxidant activities among sorghum landraces of Tigray, northern Ethiopia. Protein and starch were analyzed using an infrared spectrophotometer, whereas mineral elements were estimated using an atomic absorption spectrophotometer. Antioxidant activity was analyzed using DPPH (2,2-diphenyl-1-picrylhydrazyl) free radical scavenging, ferric-reducing antioxidant power, and phosphomolybdenum assays. The result revealed significant variation among the landraces for all the evaluated parameters. Protein and starch contents ranged from 6.21 to 18% and 33.42 to 78.30%, respectively. Wider variations were observed for Fe (32–101), Zn (16.9–42.98), Cu (1.48–5.25), Mn (9.21–20.23), and Cr (0–1.5) as measured in mg/100 g. The variabilities were high for total flavonoid (0–665 mg CE/g) and tannin (0.18–7.5 mgCE/100 g). DPPH (EC₅₀ = 29.09–818.37 µg/mL), ferric reducing antioxidant power (17.85–334.81 mgAAE/g), and total antioxidant activity (1.71–63.88 mgBHTE/g) were also highly variable among the samples. The relationship between seed color and phenolics, as well as antioxidant activities, are discussed. Multivariate analysis revealed that the landraces were clustered into four distinct groups. The rich genetic diversity in the nutritional and antinutritional attributes may be an opportunity for breeding for grain quality improvements of sorghum that, in turn, helps in addressing malnutrition. Full article

(This article belongs to the Special Issue Breeding and Genetic Research of Cereal Grain Quality)

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16 pages, 2694 KiB

Open AccessArticle

QTL Mining and Validation of Grain Nutritional Quality Characters in Rice (Oryza sativa L.) Using Two Introgression Line Populations

by Mufid Alam, Xuan Tan, Hao Zhang, Guangming Lou, Hanyuan Yang, Yin Zhou, Amjad Hussain, Parashuram Bhantana, Gonghao Jiang and Yuqing He

Agriculture 2023, 13(9), 1725; https://doi.org/10.3390/agriculture13091725 - 31 Aug 2023

Cited by 1 | Viewed by 1077

Abstract

Nutritional grain quality is mainly influenced by the protein fraction content and grain protein content. Quantitative trait loci (QTL) mining for five traits, about 245 and 284 BC₃F₃ individual families of two introgression line (IL) populations were derived from Kongyu 131/Cypress (population-I) and Kongyu 131/Vary Tarva Osla (population-II), respectively. A genetic linkage map was developed using 127 simple sequence repeat (SSR) markers in population-I and 119 SSR markers in population-II. In total, 20 and 5 QTLs were detected in population-I and population-II, respectively. About twenty QTLs were mapped in population-I: five QTLs for albumin, seven QTLs for globulin, six QTLs for prolamin, one QTL for glutelin, and one QTL for grain protein content. In total, five QTLs were mapped in population-II: one QTL for albumin and four QTLs for grain protein content. Out of 25 QTLs, 19 QTLs exhibit co-localization with the previously reported QTLs. QTL-like qGPC7.3 was delineated for total protein content. This QTL was derived from population-I and was successfully validated in NILs (near-isogenic lines). The grain protein phenotype showed a significant variation between two NILs. This investigation serves as groundwork for additional cloning of nutritional quality-related genes in rice grains. Full article

(This article belongs to the Special Issue Breeding and Genetic Research of Cereal Grain Quality)

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Review

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21 pages, 1617 KiB

Open AccessReview

Current Status and Future Prospects of Head Rice Yield

by Fawad Ali, Abdulqader Jighly, Reem Joukhadar, Nabeel Khan Niazi and Fahad Al-Misned

Agriculture 2023, 13(3), 705; https://doi.org/10.3390/agriculture13030705 - 18 Mar 2023

Cited by 1 | Viewed by 2586

Abstract

Global warming poses a serious threat to food security because of its impacts on thermosensitive food crop production. Rice is of paramount significance due to the world’s three-billion-population dependence on it as a staple food. It is well established that the high temperatures at day or night times during the grain-filling period can reduce rice grain yield, although the intriguing impact of high temperatures on head rice yields (HRY) is poorly discussed. This is because high and stable HRY is vital to meet the demand for rice grain, which is a staple food for many developing and developed nations. Hence, identifying the novel heat-tolerant rice germplasm with higher head rice yields may help mitigate a critical problem threatening global food security resulting from climate change. This review addresses the key factors, including pre-and-post-harvest scenarios related to overall reductions in the HRY and how grain molecular composition can play a significant role in determining head rice yields. Moreover, the underlying genetics of head rice is discussed as and possible mechanism to breach the complexity of HRY before identifying the key alleles and genomic regions related to the reduction in the HRY. Future research should focus on understanding the mechanisms of tolerating heat stress in rice by combining modern statistical, physiological, and molecular techniques to increase HRY. This may include high-throughput phenotyping techniques, mapping quantitative loci affecting HRY loss processes and genomic prediction using a broad wild and cultivated rice germplasm. Full article

(This article belongs to the Special Issue Breeding and Genetic Research of Cereal Grain Quality)

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