scholarly journals AGRONOMIC PERFORMANCE OF IMPROVED MAIZE (Zea mays) CULTIVARS IN SOUTHERN CHAD

2020 ◽  
Vol 8 (6) ◽  
pp. 789-798
Author(s):  
Gapili Naoura ◽  
◽  
Nadjiam Djirabaye ◽  
Hortense Noëlle Apala Mafouasson ◽  
Mamahat Alhabib Hassane ◽  
...  
Keyword(s):  
High Performance ◽  
Block Design ◽  
Environment Interaction ◽  
Days To Flowering ◽  
High Performing ◽  
Maize Cultivars ◽  
Genotype Environment Interaction ◽  
Randomized Complete Block Design ◽  
Ear Height ◽  
New Cultivars

This study was carried out to identify high-performing maize cultivars adapted to the environmental conditions of Southern Chad. Twelve new cultivars associated with two local cultivars often used by farmers in Southern Chad were evaluated in three different environments in a randomized complete block design (RCBD) with three replications. The analysis of variance showed significant differences (p<0.001) between cultivars for the measured traits except for plant height (p=0.157) and ear height (p=0.624). Genotype × environment interaction was also reported significant among cultivars only for days to flowering and number of kernels per row, but yield did not show any statistical difference, although assessed cultivars differed in their relative main performance across the three sites. Potential grain yield showed a negative correlation with days to flowering, ear height, and days to silking. The study revealed different yield performances for the assessed cultivars across different environments. The cultivar 2013 TZEE WPOP DT STR was the highest yield producing cultivars at the combined sites. The cultivars IWD C2 SYN, TZEE WPOP DT C5 STR C5, 2011 TZE YDT STR SYN, and DTE STR YSYN POP C4 showed high-performance cultivars across the different environments and can be therefore recommended for release as new cultivars to farmers of Southern Chad.

scholarly journals Green ear yield and grain yield of maize cultivars in competition with weeds

2010 ◽  
Vol 28 (1) ◽  
pp. 77-85 ◽  
Author(s):  
P.S.L. Silva ◽  
K.M.B. Silva ◽  
P.I.B. Silva ◽  
V.R. Oliveira ◽  
J.L.B. Ferreira
Keyword(s):  
Grain Yield ◽  
Plant Height ◽  
Block Design ◽  
Corn Yield ◽  
Modern Agriculture ◽  
Maize Cultivars ◽  
Randomized Complete Block Design ◽  
Ear Height ◽  
Herbicide Use ◽  
Ground Part

The reduction in herbicide use is one of the greatest interests for modern agriculture and several alternatives are being investigated with this objective, including the adoption of cultivars that suppress weeds. The objective of this study was to verify if maize cultivars develop differently, in competition with weeds, to produce green ears and grain. Randomized complete block design was used, with split-plots and five replications. Cultivars DKB 390, DKB 466, DKB 350, AG 7000, AG 7575 and Master, were evaluated in the plots, without weeding and two weedings (at 22 and 41 days after sowing) in sub plots. Twenty-one species were identified in the experimental area, the most frequent being Gramineae (Poaceae), Euphorbiaceae, Leguminosae (Fabaceae) and Convolvulaceae species. There was no difference in the dry biomass above-ground part of the weeds in the plots of the evaluated cultivars. The cultivars behaved similarly in treatments with or without hoeing, except for plant height and ear height evaluations. Without hoeing, plant height increased in cultivar DKB 390, while plant height and ear height decreased in cultivar AG 7575. In the other cultivars, these traits did not change under weed control. The presence of weeds decreased the values of all traits employed to assess green corn yield, with the exception of the total number of green ears and grain yield.

Evaluation of sugarcane genotypes with respect to sucrose yield across three crop cycles using GGE biplot analysis

2021 ◽  
pp. 1-13
Author(s):  
Aliya Momotaz ◽  
Per H. McCord ◽  
R. Wayne Davidson ◽  
Duli Zhao ◽  
Miguel Baltazar ◽  
...  
Keyword(s):  
Block Design ◽  
Genotype By Environment Interaction ◽  
Environment Interaction ◽  
Gge Biplot ◽  
Genotype By Environment ◽  
Biplot Analysis ◽  
Genotype Environment Interaction ◽  
Area 5 ◽  
Randomized Complete Block Design ◽  
Main Effects

Summary The experiment was carried out in three crop cycles as plant cane, first ratoon, and second ratoon at five locations on Florida muck soils (histosols) to evaluate the genotypes, test locations, and identify the superior and stable sugarcane genotypes. There were 13 sugarcane genotypes along with three commercial cultivars as checks included in this study. Five locations were considered as environments to analyze genotype-by-environment interaction (GEI) in 13 genotypes in three crop cycles. The sugarcane genotypes were planted in a randomized complete block design with six replications at each location. Performance was measured by the traits of sucrose yield tons per hectare (SY) and commercial recoverable sugar (CRS) in kilograms of sugar per ton of cane. The data were subjected to genotype main effects and genotype × environment interaction (GGE) analyses. The results showed significant effects for genotype (G), locations (E), and G × E (genotype × environment interaction) with respect to both traits. The GGE biplot analysis showed that the sugarcane genotype CP 12-1417 was high yielding and stable in terms of sucrose yield. The most discriminating and non-representative locations were Knight Farm (KN) for both SY and CRS. For sucrose yield only, the most discriminating and non-representative locations were Knight Farm (KN), Duda and Sons, Inc. USSC, Area 5 (A5), and Okeelanta (OK).

scholarly journals AMMI and GGE Biplot Analysis for Stability of Yield in Mid-early Pigeonpea [Cajanus cajan (L.) Millspaugh] Genotypes

2022 ◽  
Author(s):  
P. Jagan Mohan Rao ◽  
N. Sandhyakishore ◽  
S. Sandeep ◽  
G. Neelima ◽  
A. Saritha ◽  
...  
Keyword(s):  
Block Design ◽  
High Yield ◽  
Environment Interaction ◽  
Gge Biplot ◽  
Genotype By Environment ◽  
Genotype Environment Interaction ◽  
Single Location ◽  
Randomized Complete Block Design ◽  
Advanced Stages ◽  
Superior Genotypes

Background: The genotype × environment interaction greatly influences the success of breeding and in multi-location trials complicates the identification of superior genotypes for a single location, due to magnitude of genotype by location interaction are often greater than genotype by year interaction. This necessitates genotype evaluation in multi environments trials in the advanced stages of selection. Methods: Nine elite pigeonpea genotypes of mid-early duration were evaluated in six diverse locations in randomized complete block design with three replications during kharif, 2019 to ascertain the stable genotypes, environments discrimination and genotype by environment crossovers using AMMI and GGE biplot stability models. Result: The results in the present investigation revealed that first two principal components explained 73.4% of variation interaction, while, 80.50% in GGE biplot. Both the models identified WRGE-126 (G6) as stable performer with high yield (1733 kg ha-1) and among the locations Tandur (E1) measured as the ideal environment. Whereas, the environments, Adilabad (E3) and Warangal (E4) were observed representative with better discriminating ability.

scholarly journals Phenotypic stability of hybrids of Gália melon in Rio Grande do Norte state, Brazil

2011 ◽  
Vol 83 (4) ◽  
pp. 1421-1434 ◽  
Author(s):  
Glauber H.S. Nunes ◽  
Haroldo Santos Júnior ◽  
Leilson C. Grangeiro ◽  
Francisco Bezerra Neto ◽  
Carlos T.S. Dias ◽  
...  
Keyword(s):  
Block Design ◽  
Rio Grande ◽  
Soluble Solids ◽  
Environment Interaction ◽  
Industrial Complex ◽  
Phenotypic Stability ◽  
High Productivity ◽  
Genotype Environment Interaction ◽  
Randomized Complete Block Design ◽  
Main Effect

The objectives of this study were to determine the importance of simple and complex components of the interaction genotype × environment and to evaluate the adaptability and stability of Gália melon hybrids. Nine hybrids were tested in twelve environments of Rio Grande Norte State from 2000 to 2001. The experiments were carried out in a randomized complete block design with three replications. The statistical methods of Toler and Burrows, Wricke and AMMI (Additive Main effect and Multiplicative Interaction) were used to study the adaptability and stability. The complex component is responsible for most of the genotype × environment interaction for the yield and content of solids soluble of fruits. The environments associated with Mossoró and Assu municipalities are the most suitable to evaluate melon hybrids in the state. The hybrid DRG 1537 was the most likely to be grown in the Agro-industrial Complex Mossoró-Assu due to its stability, high productivity and high content of soluble solids.

scholarly journals Genotype and environment interaction on soybean yield in Mato Grosso State, Brazil

2006 ◽  
Vol 41 (5) ◽  
pp. 785-791 ◽  
Author(s):  
José Francisco Ferraz de Toledo ◽  
Cláudio Guilherme Portela de Carvalho ◽  
Carlos Alberto Arrabal Arias ◽  
Leones Alves de Almeida ◽  
Rodrigo Luis Brogin ◽  
...  
Keyword(s):  
Block Design ◽  
Environment Interaction ◽  
Mato Grosso ◽  
Soybean Yield ◽  
Cultivar Development ◽  
Genotype Environment Interaction ◽  
Sowing Dates ◽  
Randomized Complete Block Design ◽  
North And South ◽  
Made In

The objective of this work was to investigate the genotype-environment interaction in Mato Grosso State, MT. The relative importance of locations, years, sowing dates and cultivars and their interactions was analyzed from data collected in regional yield trials performed in a randomized complete block design with four replications, from 1994-1995 through 1999-2000, in nine locations and two sowing dates. Individual and pooled analyses of variance over years and locations were performed. Complementary analyses of variances partitioned MT State in two main and five smaller regions, respectively: North and South of Cuiabá; and MT-South-A (Pedra Preta area), MT-South-B (Rondonópolis and Itiquira), MT-East (Primavera do Leste and Campo Verde), MT-Central (Nova Mutum, Lucas do Rio Verde and Sorriso) and MT-Parecis (Campo Novo dos Parecis and Sapezal). Locations are relatively more important than years for yield testing soybeans in the MT State, therefore, investment should be made in increasing locations rather than years to improve experimental precision. Partitioning the MT State into regions has little impact on soybean yield testing results and, consequently, on the efficiency of the soybean breeding program in the State. Breeding genotypes with broad adaptation for the MT State is an efficient strategy for cultivar development.

scholarly journals Genotype-environment interaction in common bean cultivars with carioca grain, recommended for cultivation in Brazil in the last 40 years

2015 ◽  
Vol 15 (4) ◽  
pp. 244-250 ◽  
Author(s):  
Leiri Daiane Barili ◽  
Naine Martins do Vale ◽  
Adalgisa Lelis do Prado ◽  
José Eustáquio de Souza Carneiro ◽  
Fabyano Fonseca e Silva ◽  
...  
Keyword(s):  
Grain Yield ◽  
Common Bean ◽  
Block Design ◽  
Environment Interaction ◽  
Ge Interaction ◽  
Breeding Programs ◽  
The Past ◽  
Genotype Environment Interaction ◽  
Randomized Block Design ◽  
New Cultivars

Abstract The purpose of this study was to analyze the effect of genotype-environment interaction (GE) on common bean cultivars with carioca grain (cream-colored beans with light brown stripes), recommended for cultivation by different Brazilian research institutions in the last 40 years. The experiments were carried out with 40 cultivars in four different environments (Coimbra and Viçosa, in the dry and winter seasons of 2013) using a randomized block design with three replications. The results showed an effective increase in grain yield resulting from the use of new cultivars from different Brazilian breeding programs in the past four decades. In addition, the analysis of the GE interaction indicated that the cultivars recommended after 2005 combined high mean grain yield, wide adaptability and high or stability.

scholarly journals ADAPTABILITY AND STABILITY FOR IRON AND ZINC IN COWPEA BY AMMI ANALYSIS

2021 ◽  
Vol 34 (3) ◽  
pp. 590-598
Author(s):  
CARLOS ENRIQUE CARDONA-AYALA ◽  
HERMES ARAMENDIZ-TATIS ◽  
MIGUEL MARIANO ESPITIA CAMACHO
Keyword(s):  
Genetic Improvement ◽  
Block Design ◽  
Environment Interaction ◽  
Improvement Program ◽  
Genotype Environment Interaction ◽  
Randomized Complete Block Design ◽  
Ammi Analysis ◽  
Iron And Zinc ◽  
Ammi Model ◽  
Main Effects

ABSTRACT Iron and zinc deficiency is one of the main problems affecting vulnerable populations in the Colombian Caribbean, thereby generating malnutrition from the consumption of foods with low content of essential minerals. The objective of this study was to evaluate the genotype-environment interaction for iron and zinc accumulation in grains in 10 cowpea bean genotypes by additive main effects and multiplicative interaction (AMMI) model and to select the most stable ones to stimulate their planting or as parents in the genetic improvement program. Nine promising lines and a commercial control were evaluated using the randomized complete block design with 10 treatments and four replications in 10 environments of the northern Colombia in the second semester of 2017 and first of 2018. The adaptability and stability analysis was done using AMMI model. The results showed highly significant differences at the level of environments, genotypes, and genotype-environment interaction for iron and zinc, demostrating a differential adaptability of genotypes in the test environments. Genotypes 2 and 3 expressed greater adaptability and stability for iron contents in the seed; while genotype 1, recorded it for zinc contents. These three genotypes outperformed the commercial control and, therefore, can be recommended for planting or be used as parents in the genetic improvement program.

scholarly journals Elucidation of Genotype × Environment Interaction for Identification of Stable Genotypes to Grain Yield of Rice (Oryza sativa L.) Varieties in Bangladesh Rainfed Condition

2021 ◽  
Vol 24 (1) ◽  
pp. 59-71
Author(s):  
SK Debsharma ◽  
PR Roy ◽  
RA Begum ◽  
KM Iftekharuddaula
Keyword(s):  
Grain Yield ◽  
Oryza Sativa L ◽  
Block Design ◽  
Environment Interaction ◽  
Rainfed Condition ◽  
Ecological Zones ◽  
Commercial Cultivation ◽  
Genotype Environment Interaction ◽  
Randomized Complete Block Design ◽  
Sources Of Variation

The research was evaluated in seven ecological zones throughout the country following randomized complete block design with three replications in each location. The combined analysis of variance for grain yield indicated that the differences among all sources of variation were highly significant (P<0.01). Environment (E), Genotype (G) and G × E interaction effects explained by 25.54%, 17.02% and 48.97% for inbred and 35.26%, 17.03%, 31.23% for hybrid of the total sum of square, respectively. Locations E2 (Chattogram); E3 (Dhaka) for inbred and E2 (Chattogram); E4 (Khulna); E5 (Rajshahi); E7 (Sylhet) for hybrid varieties were found most discriminating and more informative among all. Ideal environment was found in E6 (Rangpur) for inbred and E4 (Khulna) for hybrid varieties. According to GGE mean and stability biplot, the most stable genotypes were G18 (BRRI dhan34); G26 (BRRI dhan52); G28 (BRRI dhan57); G19 (BRRI dhan37); G13 (BR25); G27 (BRRI dhan56); G21 (BRRI dhan39) for inbred and G2 (BADC hybrid dhan-2); G4 (BADC hybrid dhan-6); G5 (Bayer hybrid dhan-4) for hybrid compared to the other genotypes. The ideal genotypes were found G18 (BRRI dhan34) for inbred and G26 (BRRI hybrid dhan6) for hybrid varieties. In summary, we identified stable genotypes adapted across the environments for grain yield. These genotypes can be used as commercial cultivation with sustainable production as well as a parent/pre-breeding material in future rice breeding program. Bangladesh Rice J. 24 (1): 59-71, 2020

scholarly journals Genotype × environment interaction of quality protein maize grain yield in Nepal

2016 ◽  
Vol 2 (1) ◽  
pp. 66-73
Author(s):  
Jiban Shrestha ◽  
Chitra Bahadur Kunwar ◽  
Jharana Upadhyaya ◽  
Maiya Giri ◽  
Ram Bahadur Katuwal ◽  
...  
Keyword(s):  
Grain Yield ◽  
Block Design ◽  
Quality Protein Maize ◽  
Environment Interaction ◽  
Maize Grain Yield ◽  
Genotype Environment Interaction ◽  
Maize Genotypes ◽  
Randomized Complete Block Design ◽  
Maize Grain

In order to determine G × E interaction of quality protein maize grain yield, six maize genotypes were evaluated under different environments of three Terai (Chitwan, Surkhet and Doti) and four mid hill (Dhankuta, Lalitpur, Dolakha and Kaski) districts of Nepal during summer seasons of 2014 and 2015. The experiments were conducted using randomized complete block design along with three replications. The  genotypes namely S99TLYQ-B, S99TLYQ-HG-AB and S03TLYQ-AB-01 were identified high yielding and better adapted genotypes for Terai environments with grain yield of  4199 kg ha-1, 3715 kg ha-1, and 3336 kg ha-1 respectively and  S99TLYQ-B and S03TLYQ-AB-01 for mid hill environments with grain yield of  4547 kg ha-1 and 4365 kg ha-1 respectively. Therefore, these genotypes can be suggested for cultivation in their respective environments in the country.

scholarly journals Genotype X Environment Interaction of Food Barley

2015 ◽  
Vol 21 ◽  
pp. 41-48
Author(s):  
Gebremedhin Welu
Keyword(s):  
Grain Yield ◽  
Block Design ◽  
Genotype X Environment Interaction ◽  
Environment Interaction ◽  
Genotype X Environment ◽  
Genotype Effect ◽  
Environment Effects ◽  
Randomized Complete Block Design ◽  
Barley Genotypes

The objective of this experiment was to estimate the magnitude of genotype X environment interaction on grain yield and yield related traits. Twelve varieties of food barley were included in the study planted in randomized complete block design with three replications. The ANOVA of combined and individual location revealed significant differences among the food barley genotypes for grain yield and other traits. The results of ANOVA for grain yield showed highly significant (p≤0.01) differences among genotypes evaluated for grain yield at Maychew and significant (p≤0.05) differences in Korem, Alage and Mugulat. The ANOVA over locations showed a highly significant (p≤0.01) variation for the genotype effect, environment effects, genotype X environment interaction (GEI) effect and significant (p≤0.05) variation for GEI effect of yield and for most of the yield related traits of food barley genotypes. Haftysene, Yidogit, Estayish and Basso were the genotypes with relatively high mean grain yield across all locations and they are highly performing genotypes to the area. Among locations, the highest mean grain yield was recorded at Korem and it was a suited environment to all the genotypes whereas Mugulat is unfavoured one. ECOPRINT 21: 41-48, 2014DOI: http://dx.doi.org/10.3126/eco.v21i0.11903

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