Drought tolerance is an important breeding objective for improving the yield of cereal crops. Identifying key drought-tolerant loci/genes from Setaria viridis and Setaria italica is essential for enhancing the yield and stress resistance of foxtail millet via molecular breeding technologies. Here, an interspecific recombinant inbred line (RIL) population was constructed by crossing the S. italica cultivar Yugu1 with the wild S. viridis H1. Phenotypic evaluation and QTL mapping for drought tolerance were conducted from the grain filling to the maturity stage. Five strong drought-tolerant lines were screened using the drought resistance index (DRI). Phenotypic variance analysis indicated that the period of duration was the key factor affecting drought tolerance in the population. Furthermore, the RIL population was subjected to whole-genome sequencing, and a high-density linkage map was constructed, comprising 3,029 bin markers spanning 709.34 cM with an average interval of 0.24 cM. A total of 10 QTLs were detected for panicle number per plot (PNP), grain weight per plant (GWP), and 1000-grain weight (TGW). Eight QTLs were associated with PNP, and the favorable alleles at all loci except qPNP4.1 were derived from Setaria viridis H1. The favorable alleles of the other two QTLs for GWP and TGW were all from Yugu1. Based on functional homology alignment, five genes located within three PNP-related QTL intervals (Seita.5G420900, Seita.7G306400, Seita.5G312700, Seita.5G319000, Seita.5G319500) were predicted to modulate the tillering, grain yield under drought stress conditions. These findings provide an important basis for drought-tolerant breeding and the dissection of the drought tolerance mechanisms in foxtail millet and its close species.

Improving crop resilience in the face of increasingly extreme and unpredictable weather and reduced access to agricultural inputs such as nitrogen fertilizer and water will require an improved understanding of phenotypic plasticity in crops. To understand the roles of different component traits in determining overall plasticity for grain yield, we generated data from a panel of 122 maize (Zea mays) hybrids grown in replicated field trials in 34 environments spanning 1126 km (700 miles) of the US Corn Belt. We observed that the levels of genetic versus environmental control and the relationships between mean parent release year, overall performance, and linear plasticity were trait-dependent across the 18 agronomic and yield components studied. Importantly and unexpectedly, we observed no clear tradeoff between linear plasticity and mean performance and found only rare examples where genotype-by-environment interactions would alter selection decisions based on the environments tested in our dataset. Furthermore, we showed that overall plasticity was repeatable and that plasticity in response to nitrogen fertilization was not, which may help explain the limited success in breeding for nitrogen use efficiency. Together, these findings improve our understanding of phenotypic plasticity, with implications for maize breeding.

Use of amaranth grain is expanding in many countries worldwide due to its high-quality protein, and its gluten-free status. Amaranths have sustainability advantages from tolerating drought and a wide variety of growing conditions. Pseudocereal crops like grain amaranth require little water, fertilizer, and energy relative to traditional cereals (e.g., corn, wheat, rice). India has emerged as the major exporter of amaranth grain. Processing of grain amaranth requires innovative approaches due to its small seed size. Dry and wet milling techniques and popping are used to produce protein-rich fractions, protein concentrates, isolates, and flour. These ingredients are finding commercial food applications due to their highly functional and nutritious attributes. Grain amaranth has the potential for a significant impact on global food security by providing a plant-based protein-rich human diet.

Millet is a small-seeded cereal crop with big potential. There are many different cultivars of proso millet (Panicum miliaceum L.) with different characteristics, bringing forth the issue of sorting which are important for growers, processors, and consumers. Current methods of grain cultivar detection and classification are subjective, destructive, and time-consuming. Therefore, there is a need to develop nondestructive methods for sorting the cultivars of proso millet. In this study, the feasibility of using near-infrared (NIR) hyperspectral imaging (900–1700 nm) to discriminate between different cultivars of proso millet seeds was evaluated. A total of 5000 proso millet seeds were randomly obtained and investigated from the ten most popular cultivars in the United States, namely Cerise, Cope, Earlybird, Huntsman, Minco, Plateau, Rise, Snowbird, Sunrise, and Sunup. To reduce the large dimensionality of the hyperspectral imaging, principal component analysis (PCA) was applied, and the first two principal components were used as spectral features for building the classification models because they had the largest variance. The classification performance showed prediction accuracy rates as high as 99% for classifying the different cultivars of proso millet using a Gradient tree boosting ensemble machine learning algorithm. Moreover, the classification was successfully performed using only 15 and 5 selected spectral features (wavelengths), with an accuracy of 98.14% and 97.6%, respectively. The overall results indicate that NIR hyperspectral imaging could be used as a rapid and nondestructive method for the classification of proso millet seeds.

Proso millet (Panicum miliaceum L.) is a short-season annual crop known for high water-use efficiency and drought tolerance. The low water requirement makes this ancient grain an excellent rotational crop for the winter wheat-based dryland cropping system in the High Plains of the United States. The genetic base of the commonly grown US cultivars is very narrow. Assessment of proso millet germplasm for agronomic traits is essential for its efficient utilization in the genetic improvement of this crop. The objectives of this study were to (1) characterize the US proso millet germplasm based on nine important morpho-agronomic traits and (2) classify the germplasm into clusters based on these morpho-agronomic traits. A total of 77 genotypes from 24 different countries were evaluated in the field during 2014 and 2015 at Scottsbluff and Sidney, NE. The genotypes showed significant variations for all the traits across locations. Many traits showed genotype x environment interactions and were highly correlated. Several genotypes were identified as sources of desired traits, such as maturity, lodging, and grain shattering. The genotypes formed six clusters based on morpho-agronomic data. Principal component analysis revealed that these nine traits explained maximum phenotypic variance and could be used as selection indices in proso millet breeding. This is the most comprehensive study of the US proso millet core collection based on morpho-agronomic traits and would be useful for developing improved proso millet cultivars.

Leaf chlorophyll concentration was measured for 84 publicly available maize hybrids grown under three nitrogen fertilizer treatments in two contrasting environments in Nebraska. The effect of nitrogen treatment on chlorophyll response was found to be significant (p < 0.05) for both locations. In Scottsbluff, chlorophyll concentrations increased significantly with increasing nitrogen rate, while no significant difference was found between medium and high nitrogen in Lincoln. Within equivalent nitrogen treatments, chlorophyll was more abundant in Lincoln than Scottsbluff for nearly every hybrid. Hybrid response was not consistent between environments, with approximately 11% of variance explained by genotype by environment interaction.

The pilot-scale genome-wide association study in the US proso millet identified twenty marker–trait associations for five morpho-agronomic traits identifying genomic regions for future studies (e.g. molecular breeding and map-based cloning). Proso millet (Panicum miliaceum L.) is an ancient grain recognized for its excellent water-use efficiency and short growing season. It is an indispensable part of the winter wheat-based dryland cropping system in the High Plains of the USA. Its grains are endowed with high nutritional and health-promoting properties, making it increasingly popular in the global market for healthy grains. There is a dearth of genomic resources in proso millet for developing molecular tools to complement conventional breeding for developing high-yielding varieties. Genome-wide association study (GWAS) is a widely used method to dissect the genetics of complex traits. In this pilot study of the first-ever GWAS in the US proso millet, 71 globally diverse genotypes of 109 the US proso millet core collection were evaluated for five major morpho-agronomic traits at two locations in western Nebraska, and GWAS was conducted to identify single nucleotide polymorphisms (SNPs) associated with these traits. Analysis of variance showed that there was a significant difference among the genotypes, and all five traits were also found to be highly correlated with each other. Sequence reads from genotyping-by-sequencing (GBS) were used to identify 11,147 high-quality bi-allelic SNPs. Population structure analysis with those SNPs showed stratification within the core collection. The GWAS identified twenty marker–trait associations (MTAs) for the five traits. Twenty-nine putative candidate genes associated with the five traits were also identified. These genomic regions can be used to develop genetic markers for marker-assisted selection in proso millet breeding.

Turmeric (Curcuma longa) has long been used in traditional Indian medicine.India accounts for 80% of total global turmeric production.Lakadong turmeric gets its name from the tiny village of Lakadong, which is located in the foothills of the Jaintia Hills in Meghalaya, India.It is known for having a high curcumin content of more than 7%, as opposed to 2 -4% in regular varieties.The tribes of this region brought Lakadong turmeric from the forest and domesticated it for medicinal purposes centuries ago.Growth in local coal industries and a gradual decline in the market have had a significant impact on and reduced Lakadong turmeric production.To resurrect the industry, the Meghalaya government has embarked on a mission to increase production of Lakadong turmeric to 50,000 metric tons (MT) per year by 2023, up from 20,000 MT currently.However, most farmers in this region have abandoned Lakadong turmeric cultivation due to low returns.To ensure farmers' livelihoods, policymakers and the government must address future production challenges and create a viable market for such commodities.This review paper discusses the traditional history of Lakadong cultivation and its current status, challenges, and prospects.The paper also discusses the agronomic, phytochemical, and medicinal properties of turmeric.

应用微卫星标记对糜黍资源进行遗传多样性分析,确定其遗传背景,有利于资源的合理高效利用.以80份山西糜黍核心种质为材料,44个SSR标记为检测工具,利用软件PowerMarker 3.25和PopGen 1.32计算遗传多样性衡量参数,使用MEGA 11.0.10软件绘制聚类图,使用NTSYSpc2.11a软件进行主成分分析,应用ID Analy-sis 4.0软件构建材料的DNA分子身份证.结果表明,80份材料在44个位点共检测出130个等位变异,平均每个位点检出3个;基于UPGMA聚类分析,80份材料划归4个类群(Ⅰ、Ⅱ、Ⅲ、Ⅳ),分别以晋中市、忻州市、朔州市、忻州市材料为主.主成分分析将材料划归10类(G1～G10),其中,G1均来自大同市,G2均来自朔州市,G3均来自忻州市,G4均来自太原市,G5～G10分别来自阳泉市、晋中市、吕梁市、长治市、临汾市和运城市.综合多态性信息含量(PIC)和Shannon多样性指数(I)值得出,高于平均值的SSR引物有 21对(RYW3、RYW7、RYW11、RYW14、RYW18、RYW26、RYW28、RYW29、RYW30、RYW31、RYW37、RYW39、RYW40、RYW49、RYW54、RYW56、RYW61、RYW62、RYW65、RYW67 和 RYW82).利用 ID Analysis 4.0 软件分析,发现 16 个 SSR(RYW62、RYW67、RYW56、RYW65、RYW61、RYW40、RYW37、RYW31、RYW82、RYW29、RYW28、RYW49、RYW39、RYW54、RYW18和RYW30)组合在一起可区分全部材料.通过在线二维码生成器,对试验材料的基本信息及字符串信息进行加工处理,可得到二维码DNA分子身份证.

Proso millet (Panicum miliaceum L.) is a climate-resilient, ancient, and gluten-free cereal. This allotetraploid crop is healthy for humans and the environment. Its use as human food is steadily increasing, especially for people with diabetes and celiac disease due to its exceptional nutritional properties and gluten-free starch. There is no comprehensive review on proso millet seed nutraceuticals quantity, quality, characteristics, genetics, genomics (omics), and genetic improvement strategies. This review article aims to summarize published research on these aspects of proso millet seed nutrients and nutraceuticals. There are lots of reports on proso millet seed nutrients (macro, micro, and secondary metabolites) and their health benefits. There are a significant number of resources of "omics" tools for proso millet overall genetic improvement. However, no or very little genetic and genomic information (e.g., genes and genetic control mechanisms) and biosynthesis of majority of the nutraceuticals of proso millet seed are available. It may take years to see the full potential of "omics" for proso millet nutraceutomics. Phytochemical analyses and omics technologies are getting more efficient, faster, and cheaper. With this new opportunity, it is essential that proso millet scientists around the world especially food technologists, plant breeders, and geneticists of both public and private sectors work collaboratively for the genetic improvement of proso millet for nutraceutical. This will stimulate industries to use more proso millet in food products for human health and nutritional security under global climate change.

EDITORIAL article Front. Plant Sci., 28 September 2023Sec. Technical Advances in Plant Science Volume 14 - 2023 | https://doi.org/10.3389/fpls.2023.1291893

Historically, wheat (Triticum aestivum L.) cultivars developed by the cooperative University of Nebraska-USDA-ARS wheat improvement project were hard red winter wheat. With the expanding hard white wheat market, there is a greater emphasis on developing hard white winter wheat lines adapted to the Great Plains. 'NW13493' (tested as NW13493) (Reg. no. CV-1197, PI 699380) was selected for its white kernels, agronomic performance, relevant disease resistances, and end-use quality and is adapted to the central Great Plains. NW13493 was licensed to Bay State Milling Company on the basis of its superior agronomic and end-use quality performance and also the need to ensure hard white wheat growers have a known market for their grain. NW13493 hard white winter wheat was released in February 2021 by the developing institutions and the licensee. NW13493 was a selection in 2013 from the cross 'SD98W175-1'/'NW03666', which was made in 2007. The pedigree of SD98W175-1 is 'KS84273BB-10'/'KSSB110-9'//'KS831374-141B'/'YE1110'/3/ 'KS82W418'/'Stephens' and the pedigree of NW03666 is 'N94S097KS'/'NE93459'. The F-1 generation was grown in the greenhouse in 2008, and the F-2 to F-3 generations were advanced as bulks at Mead, NE, in 2009-2010. NW13493 was evaluated in replicated trials beginning in 2014. It has excellent winter survival and agronomic performance, acceptable disease reactions to many of the common diseases in its target area, and good end-use quality for bread making.

Broomcorn millet ( Panicum miliaceum L.) is a prehistorical cereal, today cultivated as a minor crop with low yields but with a renewed interest for its high water use efficiency and gluten-free grains. To reverse the downward trend in broomcorn millet cultivation, the crop needs genetic improvement and creation of novel genetic variation to increase productivity. In order to facilitate genomics-assisted breeding, we designed a reduced representation genome-sequencing assay that investigates 1.8% of the nuclear DNA in a targeted and reproducible way, with an intensity of genomic sampling that is a direct function of local recombination rate. We used this tool and set up bioinformatics analyses tailored to the polyploid genome of P. miliaceum for maternity and paternity testing, quantification and genomic distribution of homozygous regions and estimation of parental genome contribution for individual seedlings in advanced inbred lines from a breeding program and compared their genomic composition with registered varieties. We found several clues that suggest that the genetic purification process to ensure genetic uniformity is incomplete in varieties of this species. Residual heterozygosity was detected in the genome of three registered varieties ranging from 4.4 to 6.25% of their haploid genome length. Other registered varieties show genome-wide homozygosity. We found, however, evidence of intravarietal genetic variation in three cases that suggest that the breeder seed or commercial seed production had fixed by self-pollination multiple inbred lines with very similar, though not identical, genotypes within each variety.

糜子为禾本科草本植物,抗旱、耐盐碱、耐瘠、生育期短.为了给糜子抗逆分子育种提供候选基因,试验在前期转录组测序注释基因的基础上,利用糜子基因组染色体16上注释的NAC蛋白结构域比对得到PmNAC1基因的gDNA序列,通过PCR扩增、基因克隆获得糜子的核苷酸序列,使用在线软件ORF Finder Blast对糜子NAC编码蛋白的理化特性及结构等进行生物信息学分析.结果表明,PmNAC1基因全长1 634 bp,编码423个氨基酸,无信号肽和跨膜结构;二级结构中氨基酸主要由8个α-螺旋和14个β-折叠组成,为亲水性蛋白,保守位点在第73～211位氨基酸,共有59个磷酸化位点;超出水平线0.5的是糖基化位点;构建了糜子转录因子NAC氨基酸序列系统发育进化树,PmNAC1蛋白与柳枝稷CUC2的亲缘关系最近,二者的遗传变异系数为0.06.

【Objective】As an ancient minor grain crop, broomcorn millet ( Panicum miliaceum L. ) is abundant in germplasm. The construction of their DNA molecular identity based on fluorescent SSR markers would provide theoretical basis and molecular detection tool for digital management of resources.【Method】Two hundred and thirty five broomcorn millet core accessions from China were used as experimental material, polymerase chain reaction were conducted several times using the broomcorn millet specific SSR markers which developed previously by the Broomcorn Millet Crop Molecular Breeding Research Group of the Agronomy College in Shanxi Agricultural University, core markers were obtained. With the given reference genome information of broomcorn millet, the core markers were mapped on chromosomes through BLAST sequence alignment. Fluorescence (FAM/HEX) was labeled on the 5' end of the SSR primer, the genotype of the material was given by capillary electrophoresis. Using binary coding means of expression, “0, 1” was written representing the presence or absence of amplified bands, and the discrimination of the material was detected by the software ID Analysis 4.0. Decimal (0-9) coding methods were used to calculate the size of the amplified fragments so as to obtain the character string molecular identity card of the accession. Genetic diversity, genetic clustering and principal component analysis were performed using the softwares Popgene, Powermarker, MEGA and NTSYS. The two-dimensional code DNA molecular identity card of the accession was given using the two-dimensional code online software (https://cli.im/).【Result】PCR amplification results showed that all the 235 accessions could be separated by 7 fluorescent SSR markers (RYW3, RYW6, RYW11, RYW18, RYW37, RYW43 and RYW125) combined together. BLAST results showed that RYW18 and RYW37 were distributed on Chromosome 2, located at 0.60 cM and 0.80 cM, respectively. RYW125 is located on Chromosome 4 at 10.40 cM. RYW43 and RYW6 were distributed on Chromosome 5, located at 52.80 cM and 53.00 cM, respectively. RYW11 and RYW3 were located on Chromosome 6 at 2.10 cM and 20.70 cM, respectively. Genetic diversity analysis showed that 87 alleles were detected at 7 loci among all accessions, 3 (RYW11)-25 (RYW6) alleles were detected at each locus, with an average of 12.4286. Shannon diversity index (I) was detected and ranged from 0.2055 (RYW18) to 2.0587 (RYW6), with an average of 1.1398. The observed heterozygosity (Ho) was 0.0086 (RYW11)-0.9455 (RYW18). The expected observed heterozygosity (He) was 0.0795 (RYW18)-0.7469 (RYW11). Nei’s gene diversity index (Nei) was 0.0793 (RYW18)-0.7452 (RYW6). The polymorphism information content (PIC) was 0.0334 (RYW11)-0.8071 (RYW6), with an average of 0.5185. The results of cluster analysis and principal component analysis showed that 235 accessions were classified into 8 groups. The electrophoretic bands were number coding, and 7 marker combinations were used to construct the character string and two-dimensional code DNA molecular ID of all the accessions.【Conclusion】Two hundred and thirty five broomcorn millet core germplasms from China were used as material, polymerase chain reaction and capillary electrophoresis were conducted, 7 core SSR markers were screened. With the given reference genome information of broomcorn millet, the above markers were mapped on 4 chromosomes. Used the above SSR markers, genetic diversity analysis of all accessions was conducted and genetic diversity parameters were obtained. Based on Cluster analysis, all accessions were classified into 8 groups. Principal component analysis result resolved the deviation occured in Cluster analysis. According to the principle of most accessions were tell apart using the least markers, decimal (0-9) coding methods were used to calculate the size of the amplified fragments so as to obtain the character string molecular identity card of the accession. Combined the phenotype data with the above character string, two-dimensional code DNA molecular ID of all the accessions were developed.

Millet is a small-seeded cereal crop with big potential and remarkable characteristics such as high drought resistance, short growing time, low water footprint, and the ability to grow in acidic soil. There is a need to develop non-destructive methods for differentiation and evaluation of the quality attributes of different of proso millet cultivars grown in the U.S. Current methods of cultivar classification are either subjective or destructive, time consuming, not allowing for the whole population to be tested, and requiring trained operators and special equipment. In this study, the feasibility of using near-infrared (NIR) hyperspectral imaging (900-1700 nm) to predict the quality attributes of proso millet (Panicum miliaceum L.) seeds as well to classify its different cultivars was demonstrated. Ten different cultivars of proso millet variety, which are the most popular in the US, investigated in this study included Cerise, Cope, Earlybird, Huntsman, Minco, Plateau, Rise, Snowbird, Sunrise, and Sunup. To reduce the large dimensionality of the hyperspectral imaging, principal component analysis (PCA) was applied, and the first two principal components were used as imaging features for building the classification models. The Classification performance showed a test accuracy rates as high as 99% for classifying the different cultivars of proso millet using gradient tree boosting ensemble machine learning algorithm. Moreover, using the partial least squares regression (PLSR) the coefficient of determination (R2) for quality prediction of proso millet seeds were 0.87, 0.80, 0.83, 0.93, and 0.92 for moisture content, crude protein, crude fat, ash, and carbohydrate, respectively. The overall results indicate that NIR hyperspectral imaging could be used to non-destructively classify and predict the quality of proso millet seeds.

Proso millet ( Panicum miliaceum L .), one of the major cultivated millets, serves as a complement to major cereal crops due to its drought tolerance and low input demands. Timing of heading is one of the key agronomic traits associated with its adaptation to a target environment and a major focus in breeding. Conventionally, heading percentage of a plot (genotype) was rated visually by breeders in field. Despite many successful studies reported in automatic head detections in other small grain species, little progress had been made to estimate heading percentage especially when multiple tillers exist. This study aimed to develop a method for automatic proso millet panicle detection and, more importantly, heading percentage estimation using regular red‐green‐blue images collected by an unmanned aerial vehicle. Aerial images of two dates were collected at heading stage in 2020 in Scottsbluff, NE. Faster regions with convolutional neural network models were trained to detect and count proso millet panicles in each plot. Then, using a sigmoid model, the number of detected panicles was converted to heading percentage without having the information of stand count and the number of tillers. Overall, the system achieved the highest coefficient of determination of 0.728 for proso millet heading percentage estimation, and an accuracy of 92.4% in determining whether a plot reached a certain threshold of heading (50% in this study). The methods developed in this study on heading percentage estimation can directly aid in decision making in proso millet breeding and can be ultimately incorporated into an automated proso millet high‐throughput phenotyping pipeline.

利用80对高基元SSR引物检测北方春糜子区48份黍稷材料的多态性,用PowerMarker 3.25对多态性进行分析,用Structure 2.2对群体遗传结构进行分析,使用MEGA 5.0构建聚类图,通过PopGen 1.32进行等位基因、有效等位基因数和多样性指数的计算,用NTSYSpc 2.11软件进行主成分分析.结果表明,80个标记在48份材料中检测到206个等位变异,每个位点检测到2～3个,平均2.575个;其中,产生2个变异的位点有34个,产生3个变异的位点有46个.80个位点多样性指数介于0.6655(RYW95)～1.0786(RYW166),平均为0.8608;80个位点PIC值介于0.1850(RYW151)～0.7062(RYW111),平均为0.4536.不同地区的黍稷种质间的遗传距离为0.0286～0.0456,遗传一致度为0.9555～0.9736.基于UPGMA聚类分析,48份黍稷分为3个类群,类群Ⅰ、Ⅱ和Ⅲ分别以青海、山西和内蒙古材料为主.Structure分析结果将参试材料分为4个群组,分别以青海、内蒙古、甘肃和山西材料为主.PCA主成分分析发现,第1类群试验材料均来自青海,第2类群试验材料均来自甘肃,第3类群试验材料均来自内蒙古,第4类群试验材料均来自山西.通过对北方春糜子区48份样本黍稷的遗传多样性、遗传距离和遗传一致性分析,发现青海省材料具有最丰富的遗传多样性和复杂的遗传背景.

黍稷是起源于我国的古老作物之一,抗逆性强且遗传多样性丰富,EST-SSR已成为植物遗传多样性分析以及指纹图谱和遗传图谱构建的重要工具.选取来自黑龙江、陕西、内蒙古、青海、波兰以及印度共6个不同地理区域的黍稷为试验材料,以前期黄黍稷(00005272)与镇原大黍稷转录测序结果选取114个EST-SSR三碱基重复标记,通过聚丙烯酰胺凝胶电泳筛选具有多态性的引物,利用PowerMarker 3.25和PopGen 1.32计算遗传多样性参数.结果表明,43对引物具有多态性(多态率为37.7％),43个EST-SSR标记的碱基重复类型有24种,GCG三核苷酸重复类型占12％.引物分辨率Rp值平均为2.09,其中,Rp值介于2.0～2.5的标记频次最多(15个),介于0～1.0标记频次最少(2个);(Rp)值平均为0.74.43个EST-SSR标记共有118个等位基因变异(平均2.7442个),有效等位变异(Ne)为1.8519～2.9412(平均为2.4011);多样性指数(I)为0.5623～1.0986(平均为0.9160);观测杂合度(Ho)为0.1667～1.0000(平均为0.5492);期望观测杂合度(He)为0.4286～0.7500(平均为0.6321);Nei′s期望杂合度(Nei)为0.3750～0.6667(平均为0.5665);多态性信息含量(PIC)为0.2392～0.8102(平均为0.6252),说明43对EST-SSR引物为高度多态性引物,可以用于栽培黍稷的指纹图谱构建和种质遗传多样性分析.

Historically cultivars developed jointly by the University of Nebraska-Lincoln and USDA-ARS wheat (Triticum aestivum L.) improvement project tend to be late and better adapted to the northern Great Plains. LCS 'Valiant' (Reg. no. CV-1196, PI 693223; tested as NE10478-1) was released based on the merits of its earliness, agronomic performance, relevant disease resistances, and end-use quality characteristics and its adaptation to the central Great Plains. As such, the line was licensed to Limagrain Cereal Seeds for their ability to market outside of Nebraska. LCS Valiant hard red winter wheat was released in March 2020 by the developing institutions and the licensee. NE10478-1 was a selection in 2011 for uniformity and grain yield from NE10478, which was derived from the cross NI03418/'Camelot'. The pedigree of NI03418 is W91-248/NE95544 (=McVey 78015/NE88521)//'Thunderbird'. The final cross of NE10478 was made in 2004. The F-1 generation was grown in Yuma, AZ, in 2005, and the F-2 to F-3 generations were advanced as bulks at Mead, NE, in 2006-2007 or sent for Hessian fly resistance screening by the USDA. In 2007, single F-3-derived F-4 rows were planted for selection. There was no further selection in NE10478 other than to remove off-types thereafter until 2011 when heads were selected to increase uniformity. LCS Valiant was evaluated in replicated trials thereafter. It has excellent winter survival, acceptable reactions to many of the common diseases in its target area, and good end-use quality for bread making.