Genotype by environment analysis on multi‐canopy cropping system towards vertical harvest space in rice

2020 ◽  
Vol 112 (6) ◽  
pp. 4568-4577
Author(s):  
Luh Putu Yuni Widyastuti ◽  
Willy Bayuardi Suwarno ◽  
Hajrial Aswidinnoor
Keyword(s):  
Cropping System ◽  
Environment Analysis ◽  
Genotype By Environment

scholarly journals Evaluating maize and soybean grain dry-down in the field with predictive algorithms and genotype-by-environment analysis

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Rafael A. Martinez-Feria ◽  
Mark A. Licht ◽  
Raziel A. Ordóñez ◽  
Jerry L. Hatfield ◽  
Jeffrey A. Coulter ◽  
...  
Keyword(s):  
Environment Analysis ◽  
Genotype By Environment ◽  
Predictive Algorithms ◽  
Dry Down

scholarly journals Genotype × environment analysis of cowpea grain production in the forest and derived savannah cultivation ecologies

Agro-Science ◽  
2021 ◽  
Vol 20 (2) ◽  
pp. 20-24
Author(s):  
A.L. Nassir ◽  
M.O. Olayiwola ◽  
S.O. Olagunju ◽  
K.M. Adewusi ◽  
S.S. Jinadu
Keyword(s):  
Sum Of Squares ◽  
Grain Production ◽  
Environment Analysis ◽  
Late Season ◽  
Genotype By Environment ◽  
Differential Performance ◽  
Main Effect ◽  
Ammi Model ◽  
Main Effects ◽  
Selection Of

Differential performance of genotypes in different cultivation environments has remained a challenge to farmers and plant breeders, the emphasis being the selection of high yielding and stable genotypes, across similar ecologies. A set of nine cowpea genotypes were  cultivated in Ago-Iwoye and Ayetoro, two locations representing high and moderate moisture zones. Plantings were done with the early and late season rains in Ago-Iwoye and mid-late season rains of Ayetoro. Statistical analysis was done to understand genotype reaction to the different environments and the plant and environment factors mediating the performance. The Additive Main Effect and Multiplicative Interaction (AMMI) model captured 61.30% of the total sum of squares (TSS). The main effects: genotype (G) environment (E) and their interaction (GxE) were significant with the largest contribution of 28.70% by the environment while the interaction and genotype fractionscaptured 20.20% and 12.40%, respectively. The percentage contribution of the main effects and GxE to total sum of squares (TSS) for traits was not consistent. The Genotype plus Genotype-by-Environment (GGE) analysis summarized 91.30% of the variation in genotype performance across environment. The cultivation environments were separated into two, with IT 95M 118 as the vertex genotype in the Ayetoro while TVU 8905 was the topmost genotype in Ago-Iwoye. The two genotypes recorded the highest grain weight per plant (GWPP) but were also the most unstable The stable genotypes IT 95M 120 and IT 86 D 716 flowered relatively late compared to others, are taller, had higher vegetative score and are low grain producers. Key words: AMMI, drought, GGE, stability, Vigna unguiculata

scholarly journals AMMI model in the analysis of genotype by environment interaction of conventionally and organically grown onion

Genetika ◽  
2016 ◽  
Vol 48 (3) ◽  
pp. 1027-1038
Author(s):  
Milka Brdar-Jokanovic ◽  
Zdenka Girek ◽  
Milan Ugrinovic ◽  
Vladimir Sikora ◽  
Ivica Djalovic ◽  
...  
Keyword(s):  
Production Systems ◽  
Farmyard Manure ◽  
Vegetation Period ◽  
Genotype By Environment Interaction ◽  
Environment Interaction ◽  
Mineral Fertilization ◽  
Environment Analysis ◽  
Genotype By Environment ◽  
Ammi Model ◽  
The Stability

This study was aimed to assess the stability of direct yield components (bulb weight and number plot-1) and other yield contributing characteristics (bulb diameter, height and index, neck diameter and length, plant height, emergence and vegetation period) in five commercial onion cultivars grown in conventional and organic environments, by employing additive main effect and multiplicative interaction (AMMI) statistical model in data analysis. The two-year field trial organized in complete randomized blocks included the plots maintained in four regimes: mineral fertilization (conventional), without fertilization, fertilization with farmyard manure and with bacterial fertilizer (organic). Each treatment by year combination was considered as an environment. Analysis of variance of AMMI model calculated for the investigated traits showed that all sources of variation (genotypes, environments, genotype by environment interaction) were highly significant. The largest proportions of the total sum of squares were encompassed by environments, except for emergence and bulb index with the pronounced effect of genotypes (67.26 and 52.54%, respectively) and neck length with the genotype by environment interaction amounting 44.59%. Generally, the effects of the interactions were in the common range. The AMMI model with two axes was concluded as the best model for the investigated traits. Onions grown in conventional system outperformed the organic ones. However, good performance of the genotypes was accompanied with low stability across the environments and vice versa. Therefore breeding programs intended to develop cultivars adapted to alternative production systems should rely on the experiments set in the corresponding environments that include various combinations of genotypes and agro-technical procedures based on the principles of organic agriculture.

Evaluation of Acoustic Analyses of Voice in Nonoptimized Conditions

2020 ◽  
Vol 63 (12) ◽  
pp. 3991-3999
Author(s):  
Benjamin van der Woerd ◽  
Min Wu ◽  
Vijay Parsa ◽  
Philip C. Doyle ◽  
Kevin Fung
Keyword(s):  
Repeated Measures ◽  
Voice Quality ◽  
Data Sets ◽  
Acoustic Measurements ◽  
Sample Collection ◽  
Experimental Conditions ◽  
Environment Analysis ◽  
Acoustic Measures ◽  
Recording Conditions ◽  
Cepstral Peak Prominence

Objectives This study aimed to evaluate the fidelity and accuracy of a smartphone microphone and recording environment on acoustic measurements of voice. Method A prospective cohort proof-of-concept study. Two sets of prerecorded samples (a) sustained vowels (/a/) and (b) Rainbow Passage sentence were played for recording via the internal iPhone microphone and the Blue Yeti USB microphone in two recording environments: a sound-treated booth and quiet office setting. Recordings were presented using a calibrated mannequin speaker with a fixed signal intensity (69 dBA), at a fixed distance (15 in.). Each set of recordings (iPhone—audio booth, Blue Yeti—audio booth, iPhone—office, and Blue Yeti—office), was time-windowed to ensure the same signal was evaluated for each condition. Acoustic measures of voice including fundamental frequency ( f o ), jitter, shimmer, harmonic-to-noise ratio (HNR), and cepstral peak prominence (CPP), were generated using a widely used analysis program (Praat Version 6.0.50). The data gathered were compared using a repeated measures analysis of variance. Two separate data sets were used. The set of vowel samples included both pathologic ( n = 10) and normal ( n = 10), male ( n = 5) and female ( n = 15) speakers. The set of sentence stimuli ranged in perceived voice quality from normal to severely disordered with an equal number of male ( n = 12) and female ( n = 12) speakers evaluated. Results The vowel analyses indicated that the jitter, shimmer, HNR, and CPP were significantly different based on microphone choice and shimmer, HNR, and CPP were significantly different based on the recording environment. Analysis of sentences revealed a statistically significant impact of recording environment and microphone type on HNR and CPP. While statistically significant, the differences across the experimental conditions for a subset of the acoustic measures (viz., jitter and CPP) have shown differences that fell within their respective normative ranges. Conclusions Both microphone and recording setting resulted in significant differences across several acoustic measurements. However, a subset of the acoustic measures that were statistically significant across the recording conditions showed small overall differences that are unlikely to have clinical significance in interpretation. For these acoustic measures, the present data suggest that, although a sound-treated setting is ideal for voice sample collection, a smartphone microphone can capture acceptable recordings for acoustic signal analysis.

Improved Plant Diversity as a Strategy to Increase Available Soil Phosphorus

2019 ◽  
Vol 103 (1) ◽  
pp. 43-45 ◽  
Author(s):  
Carlos Crusciol ◽  
João Rigon ◽  
Juliano Calonego ◽  
Rogério Soratto
Keyword(s):  
Crop Yields ◽  
Soil Phosphorus ◽  
Cropping System ◽  
P Availability ◽  
P Fractions ◽  
Crop Species ◽  
Soil P ◽  
Residue Decomposition ◽  
Available Soil Phosphorus ◽  
Crop Residue Decomposition

Some crop species could be used inside a cropping system as part of a strategy to increase soil P availability due to their capacity to recycle P and shift the equilibrium between soil P fractions to benefit the main crop. The release of P by crop residue decomposition, and mobilization and uptake of otherwise recalcitrant P are important mechanisms capable of increasing P availability and crop yields.

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