Anthesis silking interval calculation

Abstract Background Identification of QTL with large phenotypic effects conserved across genetic backgrounds and environments is one of the prerequisites for crop improvement using marker assisted selection MAS. The objectives of this study were to identify meta-QTL mQTL for grain yield GY and anthesis silking interval ASI across 18 bi-parental maize populations evaluated in the same conditions across managed water stressed and well watered environments.

Anthesis silking interval calculation

Global Synthesis of Drought Effects on Maize and Wheat Production

Drought occurs in virtually all climatic regions and drought-induced crop yield loss is considered among the greatest losses in agriculture. During the last few decades, major drought events have been recorded and are projected to intensify in most parts of Asia and beyond, which could make farming exceedingly challenging in some countries [ 6 ].

With the exception of United States, major producers of maize e. This variability was large enough to offset the increases in production resulting from improvement in technology and elevated carbon dioxide concentration, generating declines in global maize and wheat production by 3. Similar trend was also found in the less developed regions such as South Asia and Southern Africa where malnourished human population has been concentrated [ 7 ].

Associated Data

With global climate change and uncertainties in precipitation patterns, food security may become more vulnerable than in the past [ 8 ], yet few economically-viable approaches exist to support crop production under drought [ 9 ].

Despite ongoing breeding efforts to develop drought-resistant cultivars [ 1011 ], prolonged droughts in the food-insecure regions may cause famine, epidemics, and deaths, generate water crisis due to drying up of perennial streams, impact agriculture-based livelihood systems, food security and overall economic development [ 12 ].

To fully understand the impact of drought on food security, it is necessary to elucidate the environmental variables and agronomic factors that determine the vulnerability of cereal production to drought.

As variabilities often accompanied site-specific field experiments, meta-analysis can be used to summarize results from numerous independent experiments on drought [ 13 ]. Based on this reasoning, this study aims to better characterize the co-varying effects of several important factors i.

This information may also aid food production modeling by providing information on drought sensitivity under different co-varying conditions which have been known to constrain the models [ 14 ].

Anthesis silking interval calculation

Our main research questions are: Methods Peer-reviewed journal articles published in English from to were collected to build the database based on Google Scholar search using the following two sets of keywords: Only articles that meet the following criteria were included in the database: The magnitude of yield responses is examined based on the following categorical variables: For the purposes of meta-analysis, we established discrete levels for the each of the aforementioned variable and coded each observation accordingly.

Since we focused our analysis on the amount of water available and yield, we only included studies which examined the single effect of water reduction to minimize the variability of other agronomic factors e.


More importantly, these other factors were usually controlled during water treatment experiments. For the selected articles, we only used paired study sites and therefore considered that other environmental factors e.

Agro-ecosystem types were differentiated based on aridity indices, which showed significant correlation with yield [ 16 ] and soil texture was differentiated based on soil texture triangle.

Anthesis silking interval calculation

We considered clay, sandy-clay, and silty-clay soils as fine texture, silt, silt-loam, silty-clay-loam, loam, sandy clay-loam soils, and clay-loam soils as medium texture, and sand, loamy-sand, and sandy-loam as coarse texture [ 17 ].

The flowchart diagram on how the process was conducted is presented in S1 Fig. The distribution of the study locations, generated using ArcGIS Seedling emergence, anthesis-silking interval, days to anthesis and silking had high heritability but the genetic coefficient of variations was low.

This indicates that though, the character is highly heritable, its improvement through early generation selection may not give the desired results. traits are linked with assimilate partitioning by anthesis flowering stage leads to ear growth and reduces silk silking interval (ASI), ear growth and barrenness, which appearance.

Anthesis-silking interval is a good indicator finally determine harvest index. The growth and of movement of newly produced assimilated to the ear. The duration of phase 3, between the end of cell division and the arrest of cell growth in silk apex, considerably increased with water deficit.

It corresponded to the anthesis-silking interval used by breeders to characterize the response of cultivars to stress. ASIw, QTLs detected on the anthesis–silking interval in field studies with well-watered conditions.

Lw, final leaf length in (1) and (2). a, QTLs detected on the maximum leaf elongation rate per unit thermal time in (1) and (2) and over the whole set of data (3). Drought-induced changes in anthesis-silking interval are related to silk expansion: a spatio-temporal growth analysis in maize plants subjected to soil water deficit.

Drought-induced changes in anthesis-silking interval are related to silk expansion: a spatio-temporal growth analysis in maize plants subjected to soil water deficit. Authors. The positions of the 68 mQTL for grain yield and anthesis silking interval.

The 95% genetic confidence interval of mQTL for grain yield and anthesis silking interval are shaded in green and pink colors, respectively, while those shaded in black coincided.

Plant Trait Ontology - anthesis silking interval - Classes | NCBO BioPortal