Modeling canopy architecture traits using UAS-acquired LiDAR features in diverse maize varieties

Modification of the cotton canopy results in shade avoidance and competition for light, which shows that density and spatial arrangement of cotton have a great impact on light interception. This experiment was conducted in 2018 and 2019 in the experimental field at the Institute of Cotton Research of Chinese Academy of Agricultural Science in Anyang city, Henan Province, China. Six plant densities of cotton variety SCRC28 were used to assess spatial competition for light in cotton populations during the whole growing period. Light interception data were collected and analyzed according to the spatial grid method and the extension of Simpson’s 3/8 rule. The results showed that at the bottom of the canopy, greater light interception was observed at high densities than at low densities, while in the external part of the layer of the canopy in the horizontal direction, low light interception was recorded at low densities. Leaf area, aboveground biomass and plant height were obviously correlated with light interception, and the cotton population with a higher density (8.7 plants m−2) performed best at the light interception competition, and with the highest yield. The results will provide guidance on light management through the optimization of the structure of the canopy to provide more solar radiation and a significant basis by which to improve the management of light and canopy architecture.

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Simulating the Response of Drought–Tolerant Maize Varieties to Nitrogen Application in Contrasting Environments in the Nigeria Savannas Using the APSIM Model

Agronomy ◽

10.3390/agronomy11010076 ◽

2020 ◽

Vol 11 (1) ◽

pp. 76

Author(s):

Aloysius Beah ◽

Alpha Y. Kamara ◽

Jibrin M. Jibrin ◽

Folorunso M. Akinseye ◽

Abdullahi I. Tofa ◽

...

Keyword(s):

Grain Yield ◽

Field Experiments ◽

Production Systems ◽

Agricultural Practices ◽

Net Income ◽

Nitrogen Application ◽

N Application ◽

Area Index ◽

Support Tool ◽

Maize Varieties

This paper assessed the application of the Agricultural Production Systems sIMulator (APSIM)–maize module as a decision support tool for optimizing nitrogen application to determine yield and net return of maize production under current agricultural practices in the Nigeria savannas. The model was calibrated for two maize varieties using data from field experiments conducted under optimum conditions in three locations during the 2017 and 2018 cropping seasons. The model was evaluated using an independent dataset from an experiment conducted under different nitrogen (N) levels in two locations within Southern and Northern Guinea savannas. The results show that model accurately predicted days to 50% anthesis and physiological maturity, leaf area index (LAI), grain yield and total dry matter (TDM) of both varieties with low RMSE and RMSEn (%) values within the range of acceptable statistics indices. Based on 31-year seasonal simulation, optimum mean grain yield of 3941 kg ha−1 for Abuja, and 4549 for Kano was simulated at N rate of 120 kg ha–1 for the early maturing variety 2009EVDT. Meanwhile in Zaria, optimum mean yield of 4173 kg ha–1 was simulated at N rate of 90 kg ha−1. For the intermediate maturing variety, IWDC2SYNF2 mean optimum yields of 5152, 5462, and 4849 kg ha−1, were simulated at N application of 120 kg ha−1 for all the locations. The probability of exceeding attainable mean grain yield of 3000 and 4000 kg ha−1 for 2009EVDT and IWDC2SYNF2, respectively would be expected in 95% of the years with application of 90 kg N ha−1 across the three sites. Following the profitability scenarios analysis, the realistic net incomes of US$ 536 ha–1 for Abuja, and US$ 657 ha−1 for Zaria were estimated at N rate of 90 kg ha−1 and at Kano site, realistic net income of US$ 720 ha–1was estimated at N rate of 120 kg ha−1 for 2009EVDT.For IWDC2SYNF2, realistic net incomes of US$ 870, 974, and 818 ha−1 were estimated at N application of 120 kg ha−1 for Abuja, Zaria, and Kano respectively. The result of this study suggests that 90 kg N ha−1 can be recommended for 2009EVDT and 120 kg N ha–1 for IWDC2SYNF2 in Abuja and Zaria while in Kano, 120 kg N ha−1 should be applied to both varieties to attain optimum yield and profit.

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HANDY: a device for assessing resistance to mechanical crushing of maize kernel

Plant Methods ◽

10.1186/s13007-021-00729-2 ◽

2021 ◽

Vol 17 (1) ◽

Author(s):

Yuan Su ◽

Yang Xu ◽

Tao Cui ◽

Xiaojun Gao ◽

Guoyi Xia ◽

...

Keyword(s):

Moisture Content ◽

Goodness Of Fit ◽

Function Analysis ◽

Physical Damage ◽

Maize Kernel ◽

Rotating Speed ◽

Maize Cultivars ◽

Maize Varieties ◽

New Perspective ◽

Mechanical Crushing

Abstract Background How to control the physical damage during maize kernel harvesting is a major problem for both mechanical designers and plant breeders. A limitation of addressing this problem is lacking a reliable method for assessing the relation between kernel damage susceptibility and threshing quality. The design, construction, and testing of a portable tool called “HANDY”, which can assess the resistance to mechanical crushing in maize kernel. HANDY can impact the kernel with a special accelerator at a given rotating speed and then cause measurable damage to the kernel. These factors are varied to determine the ideal parameters for operating the HANDY. Results Breakage index (BI, target index of HANDY), decreased as the moisture content of kernel increased or the rotating speed decreased within the tested range. Furthermore, the HANDY exhibited a greater sensitivity in testing kernels at higher moisture level influence on the susceptibility of damage kernel than that in Breakage Susceptibility tests, particularly when the centrifugation speed is about 1800 r/min and the centrifugal disc type is curved. Considering that the mechanical properties of kernels vary greatly as the moisture content changes, a subsection linear (average goodness of fit is 0.9) to predict the threshing quality is built by piecewise function analysis, which is divided by kernel moisture. Specifically, threshing quality is regarded as a function of the measured result of the HANDY. Five maize cultivars are identified with higher damage resistance among 21 tested candidate varieties. Conclusions The HANDY provides a quantitative assessment of the mechanical crushing resistance of maize kernel. The BI is demonstrated to be a more robust index than breakage susceptibility (BS) when evaluating threshing quality in harvesting in terms of both reliability and accuracy. This study also offers a new perspective for evaluating the mechanical crushing resistance of grains and provides technical support for breeding and screening maize varieties that are suitable for mechanical harvesting.

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Genetic analysis of three maize husk traits by QTL mapping in a maize-teosinte population

BMC Genomics ◽

10.1186/s12864-021-07723-x ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Xiaolei Zhang ◽

Ming Lu ◽

Aiai Xia ◽

Tao Xu ◽

Zhenhai Cui ◽

...

Keyword(s):

Phenotypic Variation ◽

Genetic Basis ◽

Molecular Breeding ◽

Best Linear Unbiased Predictor ◽

Maize Line ◽

Maize Varieties ◽

Outer Covering ◽

High Heritability ◽

Best Linear Unbiased ◽

Variation Explained

Abstract Background The maize husk consists of numerous leafy layers and plays vital roles in protecting the ear from pathogen infection and dehydration. Teosinte, the wild ancestor of maize, has about three layers of small husk outer covering the ear. Although several quantitative trait loci (QTL) underlying husk morphology variation have been reported, the genetic basis of husk traits between teosinte and maize remains unclear. Results A linkage population including 191 BC2F8 inbred lines generated from the maize line Mo17 and the teosinte line X26–4 was used to identify QTL associated with three husk traits: i.e., husk length (HL), husk width (HW) and the number of husk layers (HN). The best linear unbiased predictor (BLUP) depicted wide phenotypic variation and high heritability of all three traits. The HL exhibited greater correlation with HW than HN. A total of 4 QTLs were identified including 1, 1, 2, which are associated with HL, HW and HN, respectively. The proportion of phenotypic variation explained by these QTLs was 9.6, 8.9 and 8.1% for HL, HN and HW, respectively. Conclusions The QTLs identified in this study will pave a path to explore candidate genes regulating husk growth and development, and benefit the molecular breeding program based on molecular marker-assisted selection to cultivate maize varieties with an ideal husk morphology.

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