Increasing stalk sucrose in sugarcorn (Zea mays L.): genetic analysis and preliminary breeding

Reid, L. M.; Zhu, Xiaoyang; Jindal, K.K.; Kebede, Aida Z.; Wu, Jian‐Fang; Morrison, Malcolm J.

doi:10.1007/s10681-016-1669-3

Cited by 6 publications

(3 citation statements)

References 20 publications

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“…The sign of additive effects only reflects which parent is chosen as P1. In other word, considering the low value parent as P1 resulted in negative sign of additive effects and vis versa (Reid et al 2016). The occurrence of significant additive effects for GZnC, GFeC and Zn/Fe efficient uptake-related traits in all three salinity levels are different from the reports of Gaddameedi et al (2018) that stated grain iron and zinc concentration and agronomic traits are largely inherited by both additive and dominant in sorghum.…”

Section: Discussioncontrasting

confidence: 59%

Pattern of Genetic Inheritance of Grain Zinc and Iron Content, Agronomic and Biochemical Traits in Bread Wheat Using Mixed Linear Models Under Salinity Stress

Ha¹,

Ssa²,

Sá³

et al. 2021

Preprint

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Wheat is the most important staple food that acts as a primary source of dietary calories, protein and most of the bioavailable micronutrients such as iron (Fe) and zinc (Zn) for the world’s population. Understanding genetic control of micronutrients uptake is necessary for development of good quality wheat genotypes. To study the nature of inheritance of Zn and Fe efficient uptake under none-saline and saline conditions, two Iranian facultative wheat variety; Navid (salt sensitive, Fe and Zn-deficient) and Roshan (salt tolerant, Fe and Zn-efficient); were crossed to generate six basic generations for generation mean analysis. All the genotypes of these six generations were evaluated for grain Zn and Fe content, agronomic and biochemical traits under none-saline and saline conditions. For all the studied traits, the non-additive components were greater than the additive component. Additive effects were negative and significant for all traits under non-saline and saline conditions, except for 100-SW in control, MDA in 100 mM salinity level, EL and LeaNaC in all salinity levels. Additive gene actions were important for grain Zn and Fe content; while for rest of traits both fixable and non-fixable genetic effects were important. Duplicate dominant type of epistasis was involved in inheritance of all the traits. Broad-sense heritability values (>0.6) for most traits under non-saline and saline conditions were high, whereas the narrow-sense heritability values for most of the studied traits were low to moderate. These Zn and Fe efficient uptake indices could be used to select Zn/Fe-efficient wheat genotypes from segregating populations.

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Section: Discussioncontrasting

confidence: 59%

Pattern of Genetic Inheritance of Grain Zinc and Iron Content, Agronomic and Biochemical Traits in Bread Wheat Using Mixed Linear Models Under Salinity Stress

Ha¹,

Ssa²,

Sá³

et al. 2021

Preprint

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“…Sugarcorn (with high stalk sugar content) [16] is a new energy crop from Canada. With the development of the agricultural technology it might replace sugarcane [ 17] and sweet sorghum [18,19], its stalk Juice contains ample amount of carbohydrates (C6 sugar), that can be fermented into ethanol.…”

Section: B-plan (Sugar Crops)mentioning

confidence: 99%

One of the 2G Bioethanol Queries: Straw Volume

Lu¹,

Liu²,

Thomsen³

2018

Preprint

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There are some controversies about 2G bioethanol and it is in need of a reliable test data in order to make a further analysis and proof. In collecting basic data from three classes of typical raw materials, such as wheat, maize stalk juice, and straw, it was found that 4.32 tons straw or 3.358 tons wheat is needed to produce 1-ton bioethanol. Using the coefficient of variation calculation and analysis method, it is able to obtain the C.V. value of straw fermentation efficiency 0.08932<0.15, indicating the fermentation technology and process of 2G bioethanol is already quite mature and reliable, without risk, and also with a raw material cost advantage. There is a problem in that the C.V. value of straw volume is 1.2648>0.95, indicating 2G bioethanol is in an extremely high-risk area. Using the straw volume calculation method, building and its costs – capital expenditure of 2G bioethanol plant is approximately seven times that of a wheat ethanol plant. This should be some of the important reasons why it is noncompetitive, extremely high price, and requiring government subsidies. Straw volume data study has caused the 2G bioethanol plant to require more cement, steel, equipment, and other materials. Thus, there are ample reasons to question the CO2 emissions and its carbon footprint of 2G bioethanol plant. Actually, the volume is not the only existing problem, it is necessary to re-evaluate and discuss the definition of 2G bioethanol and its future.

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“…Three self-pollinated ears from each genotype were harvested at 20-, 24-, and 28-days after pollination (DAP) for estimation of kernel sweetness. Digital refractometer/ brix meter (Atago, Japan) was used to measure brix which corresponds directly to percent sucrose (Reid et al 2016).…”

mentioning

confidence: 99%

Analysis of responses of novel double mutant (sh2sh2/su1su1) sweet corn hybrids for kernel sweetness under different sowing- and harvest-time

Mehta¹,

Hossain²,

Muthusamy³

et al. 2017

Indian J Agri Sci

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Sweet corn used as vegetable and component of various snack items, has emerged as one of the popular choices across the world. Identification of suitable sowing- and harvest-time for achieving high-kernel sweetness and yield is of paramount importance for successful commercialization of sweet corn hybrids. In the present study, 11 novel double mutant sweet corn (sh2sh2/su1su1) hybrids along with traditional sh2sh2-based checks were evaluated at three sowing- and harvest-dates. Kernel brix across double mutant sweet corn hybrids ranged from 17.6-26.6% (Mean:21.0%) and was comparatively higher than sh2sh2-based checks (19.3%). Sowing- and harvest- time had significant influence on brix accounting 19.4% and 8.5% of the total variation, respectively. Genotype Ã— sowing time, genotypeÃ— harvest time and genotype Ã— sowing time Ã— harvest time interactions contributed 11.4%, 10.3% and 15.2% of the total variation for brix, respectively. Average brix across harvest dates attained highest value in third sowing and 24-days after pollination recorded the highest brix across sowing dates. Few hybrids also displayed stable brix across sowing- and harvest- time. Significant influence of sowing time on both cob- and fodder- yield was also observed, and third sowing was identified as the most favourable environment for both the traits. Kernel sweetness did not show any correlation with cob- and fodder- yield. The information generated here hold significant promise in the improvement of sweet corn. This is the first ever report of responses of sh2sh2/su1su1-based hybrids to different sowing- and harvest- time for kernel sweetness and yield.

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Increasing stalk sucrose in sugarcorn (Zea mays L.): genetic analysis and preliminary breeding

Cited by 6 publications

References 20 publications

Pattern of Genetic Inheritance of Grain Zinc and Iron Content, Agronomic and Biochemical Traits in Bread Wheat Using Mixed Linear Models Under Salinity Stress

Pattern of Genetic Inheritance of Grain Zinc and Iron Content, Agronomic and Biochemical Traits in Bread Wheat Using Mixed Linear Models Under Salinity Stress

One of the 2G Bioethanol Queries: Straw Volume

Analysis of responses of novel double mutant (sh2sh2/su1su1) sweet corn hybrids for kernel sweetness under different sowing- and harvest-time

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