W. Saoudi, W. Taamalli, M. Badri, O. Z. Talbi, C. Abdelly
Context Identification of salt-tolerant genetic resources is of high importance due to the constant increase in salt-affected areas. Aims This study was conducted to assess genetic variation in salt response among and within Tunisian sea barley populations and to identify useful genotypes for future breeding programmes directed towards improving salinity tolerance. Methods The salinity response of 141 lines from 10 natural populations of Hordeum marinum ssp. marinum was characterised at a morphophysiological level, following exposure to 200 mM sodium chloride for 90 days. Key results ANOVA revealed significant differences in growth and ion accumulation between and within populations in response to salinity. The Sebkhet Ferjouna population was less affected than Sidi Othman and Tabarka; however, it accumulated relatively higher sodium and lower potassium and potassium/sodium ratio. Stress Tolerance Index (STI) and Salt Tolerance (ST) values varied significantly among populations and lines. STI was positively correlated with potassium and negatively correlated with sodium content in roots and leaves, whereas no evidence of a relationship between both cations and ST was observed. Conclusions SO7, SO28, LB5, LB25, TB1, MT3 and BK12 with high values of STI were identified as high yielding lines in control and salt stress conditions, whereas MT3, BK12, MT17, BF10, SL8, SL16 and SF32, with the highest values of ST, were characterised by a small yield loss and low sensitivity when exposed to salinity. Implications These lines constitute a genetic resource with desirable adaptation characteristics for breeding programmes towards salinity tolerance in cultivated cereals.
{"title":"Genetic variation in growth, ionic accumulation and salt tolerance indices under long-term salt stress in halophytic Tunisian sea barley (Hordeum marinum ssp. marinum)","authors":"W. Saoudi, W. Taamalli, M. Badri, O. Z. Talbi, C. Abdelly","doi":"10.1071/cp23199","DOIUrl":"https://doi.org/10.1071/cp23199","url":null,"abstract":"Context Identification of salt-tolerant genetic resources is of high importance due to the constant increase in salt-affected areas. Aims This study was conducted to assess genetic variation in salt response among and within Tunisian sea barley populations and to identify useful genotypes for future breeding programmes directed towards improving salinity tolerance. Methods The salinity response of 141 lines from 10 natural populations of Hordeum marinum ssp. marinum was characterised at a morphophysiological level, following exposure to 200 mM sodium chloride for 90 days. Key results ANOVA revealed significant differences in growth and ion accumulation between and within populations in response to salinity. The Sebkhet Ferjouna population was less affected than Sidi Othman and Tabarka; however, it accumulated relatively higher sodium and lower potassium and potassium/sodium ratio. Stress Tolerance Index (STI) and Salt Tolerance (ST) values varied significantly among populations and lines. STI was positively correlated with potassium and negatively correlated with sodium content in roots and leaves, whereas no evidence of a relationship between both cations and ST was observed. Conclusions SO7, SO28, LB5, LB25, TB1, MT3 and BK12 with high values of STI were identified as high yielding lines in control and salt stress conditions, whereas MT3, BK12, MT17, BF10, SL8, SL16 and SF32, with the highest values of ST, were characterised by a small yield loss and low sensitivity when exposed to salinity. Implications These lines constitute a genetic resource with desirable adaptation characteristics for breeding programmes towards salinity tolerance in cultivated cereals.","PeriodicalId":517535,"journal":{"name":"Crop & Pasture Science","volume":"9 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140744419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Context Arsenic (As) is a noxious metalloid for plants, animals and humans. Elevated levels of As in soils may cause it to accumulate to above-permissible levels in wheat grains, posing a threat to human health. Moreover, vulnerable population groups in developing countries have inadequate dietary zinc (Zn) linked to cereal-based diets. Aims The present study evaluated the effect of soil Zn application on accumulation of As and Zn in grains of two Zn-biofortified wheat (Triticum aestivum L.) cultivars (Akbar-2019 and Zincol-2016). Methods Wheat plants were grown on an alkaline calcareous soil spiked with three levels of As (0, 5 and 25 mg kg−1). Before sowing, two rates of Zn (0 and 8 mg kg−1) were also applied to the soil. Key results Arsenic spiking in soil decreased plant dry matter yield, chlorophyll pigments, and phosphorus (P) and Zn accumulation, and increased As accumulation in wheat. By contrast, soil Zn application enhanced crop yield and increased P and Zn accumulation, with a simultaneous decrease in As accumulation in both cultivars. Compared with the Zn control, soil Zn application decreased grain As concentration by 26%, 30% and 32% for plants grown in soil spiked with 0, 5 and 25 mg As kg−1, respectively. Conclusions Applying Zn to As-spiked soil mitigates the harmful effects of As by increasing Zn and decreasing As concentrations in wheat, resulting in improved grain quality for human consumption. Implications Zinc application to crop plants should be recommended for addressing the health implications associated with As-contaminated crops and human Zn deficiency.
{"title":"Soil zinc application decreases arsenic and increases zinc accumulation in grains of zinc-biofortified wheat cultivars","authors":"Ammara Basit, Shahid Hussain","doi":"10.1071/cp23275","DOIUrl":"https://doi.org/10.1071/cp23275","url":null,"abstract":"Context Arsenic (As) is a noxious metalloid for plants, animals and humans. Elevated levels of As in soils may cause it to accumulate to above-permissible levels in wheat grains, posing a threat to human health. Moreover, vulnerable population groups in developing countries have inadequate dietary zinc (Zn) linked to cereal-based diets. Aims The present study evaluated the effect of soil Zn application on accumulation of As and Zn in grains of two Zn-biofortified wheat (Triticum aestivum L.) cultivars (Akbar-2019 and Zincol-2016). Methods Wheat plants were grown on an alkaline calcareous soil spiked with three levels of As (0, 5 and 25 mg kg−1). Before sowing, two rates of Zn (0 and 8 mg kg−1) were also applied to the soil. Key results Arsenic spiking in soil decreased plant dry matter yield, chlorophyll pigments, and phosphorus (P) and Zn accumulation, and increased As accumulation in wheat. By contrast, soil Zn application enhanced crop yield and increased P and Zn accumulation, with a simultaneous decrease in As accumulation in both cultivars. Compared with the Zn control, soil Zn application decreased grain As concentration by 26%, 30% and 32% for plants grown in soil spiked with 0, 5 and 25 mg As kg−1, respectively. Conclusions Applying Zn to As-spiked soil mitigates the harmful effects of As by increasing Zn and decreasing As concentrations in wheat, resulting in improved grain quality for human consumption. Implications Zinc application to crop plants should be recommended for addressing the health implications associated with As-contaminated crops and human Zn deficiency.","PeriodicalId":517535,"journal":{"name":"Crop & Pasture Science","volume":"27 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140367045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Context Spring-sown forage brassicas are commonly used to fill feed gaps in high-rainfall temperate livestock systems, but they have wider potential as an autumn-sown forage in drier environments within Australia’s crop–livestock zone. Aims We modelled the production potential of autumn-sown forage brassicas grown in diverse environments and tested their ability to alter the frequency and magnitude of feed gaps. Methods Long-term production potential was simulated in APSIM for four forage brassica genotypes, compared with forage wheat and dual-purpose canola across 22 diverse agro-climatic locations. For seven regions, the change in frequency and magnitude of forage deficits from adding forage brassicas to representative forage–livestock systems was predicted. Key results Across locations, median yields of forage brassicas ranged from 7 to 19 t DM/ha, and their annual metabolisable-energy yield was higher than that of forage wheat at most sites and nearly always exceeded dual-purpose canola. Forage brassicas performed better than forage wheat in later-sowing events (late April to early May) and maintained growth and quality later into spring. At five of the seven regions, adding 15% of farm forage area to forage brassicas reduced the frequency and magnitude of feed deficits by 35–50% and 20–40%, respectively. However, they were less beneficial where winter–spring feed gaps are uncommon. Conclusions We demonstrated that autumn-sown forage brassicas can be reliable and productive contributors to the feed base in drier environments and are a suitable alternative to forage cereals. Implications Forage brassicas can help reduce feed gaps and improve livestock production in a range of production systems spanning Australia’s crop–livestock zone.
{"title":"Forage brassicas can enhance the feed base and mitigate feed gaps across diverse environments","authors":"Lucinda J. Watt, Lindsay W. Bell","doi":"10.1071/cp23333","DOIUrl":"https://doi.org/10.1071/cp23333","url":null,"abstract":"Context Spring-sown forage brassicas are commonly used to fill feed gaps in high-rainfall temperate livestock systems, but they have wider potential as an autumn-sown forage in drier environments within Australia’s crop–livestock zone. Aims We modelled the production potential of autumn-sown forage brassicas grown in diverse environments and tested their ability to alter the frequency and magnitude of feed gaps. Methods Long-term production potential was simulated in APSIM for four forage brassica genotypes, compared with forage wheat and dual-purpose canola across 22 diverse agro-climatic locations. For seven regions, the change in frequency and magnitude of forage deficits from adding forage brassicas to representative forage–livestock systems was predicted. Key results Across locations, median yields of forage brassicas ranged from 7 to 19 t DM/ha, and their annual metabolisable-energy yield was higher than that of forage wheat at most sites and nearly always exceeded dual-purpose canola. Forage brassicas performed better than forage wheat in later-sowing events (late April to early May) and maintained growth and quality later into spring. At five of the seven regions, adding 15% of farm forage area to forage brassicas reduced the frequency and magnitude of feed deficits by 35–50% and 20–40%, respectively. However, they were less beneficial where winter–spring feed gaps are uncommon. Conclusions We demonstrated that autumn-sown forage brassicas can be reliable and productive contributors to the feed base in drier environments and are a suitable alternative to forage cereals. Implications Forage brassicas can help reduce feed gaps and improve livestock production in a range of production systems spanning Australia’s crop–livestock zone.","PeriodicalId":517535,"journal":{"name":"Crop & Pasture Science","volume":"134 18","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140369786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
T. Singhal, C. Satyavathi, S. P. Singh, M. Sankar, M. M., T. R, Sunaina Yadav, C. Bharadwaj
Context Micronutrient enrichment of pearl millet (Pennisetum glaucum (L.) R.Br.), an important food source in arid and semi-arid Asia and Africa, can be achieved by using stable genotypes with high iron and zinc content in breeding programs. Aims We aimed to identify stable expression of high grain iron and zinc content in pearl millet lines across environments. Methods In total, 29 genotypes comprising 25 recombinant inbred lines (RILs), two parental lines and two checks were grown and examined from 2014 to 2016 in diverse environments. Best performing genotypes were identified through genotype + genotype × environment interaction (GGE) biplot and additive main-effects and multiplicative interaction (AMMI) model analysis. Key results Analysis of variance showed highly significant (P < 0.01) variations. The GGE biplot accounted for 87.26% (principal component 1, PC1) and 9.64% (PC2) of variation for iron, and 87.04% (PC1) and 6.35% (PC2) for zinc. On the basis of Gollob’s F validation test, three interaction PCs were significant for both traits. After 1000 validations, the real root-mean-square predictive difference was computed for model diagnosis. The GGE biplot indicated two winning RILs (G4, G11) across environments, whereas AMMI model analysis determined 10 RILs for iron (G12, G23, G24, G7, G15, G13, G25, G11, G4, G22) for seven for zinc (G14, G15, G4, G7, G11, G4, G26) as best performers. The most stable RILs across environments were G12 for iron and G14 for zinc. Conclusions High iron and zinc lines with consistent performance across environments were identified and can be used in the development of biofortified hybrids. Implications The findings suggest that AMMI and GGE, as powerful and straightforward techniques, may be useful in selecting better performing genotypes.
{"title":"Elucidating genotype × environment interactions for grain iron and zinc content in a subset of pearl millet (Pennisetum glaucum) recombinant inbred lines","authors":"T. Singhal, C. Satyavathi, S. P. Singh, M. Sankar, M. M., T. R, Sunaina Yadav, C. Bharadwaj","doi":"10.1071/cp23120","DOIUrl":"https://doi.org/10.1071/cp23120","url":null,"abstract":"Context Micronutrient enrichment of pearl millet (Pennisetum glaucum (L.) R.Br.), an important food source in arid and semi-arid Asia and Africa, can be achieved by using stable genotypes with high iron and zinc content in breeding programs. Aims We aimed to identify stable expression of high grain iron and zinc content in pearl millet lines across environments. Methods In total, 29 genotypes comprising 25 recombinant inbred lines (RILs), two parental lines and two checks were grown and examined from 2014 to 2016 in diverse environments. Best performing genotypes were identified through genotype + genotype × environment interaction (GGE) biplot and additive main-effects and multiplicative interaction (AMMI) model analysis. Key results Analysis of variance showed highly significant (P < 0.01) variations. The GGE biplot accounted for 87.26% (principal component 1, PC1) and 9.64% (PC2) of variation for iron, and 87.04% (PC1) and 6.35% (PC2) for zinc. On the basis of Gollob’s F validation test, three interaction PCs were significant for both traits. After 1000 validations, the real root-mean-square predictive difference was computed for model diagnosis. The GGE biplot indicated two winning RILs (G4, G11) across environments, whereas AMMI model analysis determined 10 RILs for iron (G12, G23, G24, G7, G15, G13, G25, G11, G4, G22) for seven for zinc (G14, G15, G4, G7, G11, G4, G26) as best performers. The most stable RILs across environments were G12 for iron and G14 for zinc. Conclusions High iron and zinc lines with consistent performance across environments were identified and can be used in the development of biofortified hybrids. Implications The findings suggest that AMMI and GGE, as powerful and straightforward techniques, may be useful in selecting better performing genotypes.","PeriodicalId":517535,"journal":{"name":"Crop & Pasture Science","volume":"12 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140284060","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Arushi Arora, Deepak Bhamare, A. K. Das, Shubhank Dixit, Sreya Venadan, Y. K. R., Ramesh Kumar, Dharam Paul, J. C. Sekhar, Sunil Neelam, Sudip Nandi, M. C. Kamboj, S. Rakshit
Context Amylose is a type of resistant starch with numerous health benefits and industrial applications. Starch from maize (Zea mays L.) usually has an amylose content of ~25%. Aims The aim was to develop high-amylose maize genotypes suitable for human consumption and adapted to Indian conditions. Methods Marker-assisted backcross breeding was used to transfer the mutant ae1 allele from a high-amylose donor from the USA into the three parents (HKI 1344, HKI 1378, HKI 1348-6-2) of two high-yielding white maize hybrids (HM5 and HM12) grown in India. Key results In converted lines, amylose content was 40.40–58.10% of total kernel starch, compared with 22.25–26.39% in parents. The percentage increase in amylose content was 63.70–153.03%. There was a significant amount of background recovery in each backcross generation: 66.80–79% in BC1F1, 72.85–88.60% in BC2F1, and 84.45–93.70% in BC2F2. Overall, the total kernel starch content was reduced (by ~22%) in the ae1-introgressed families. Conclusions The converted lines developed in the study are enriched with kernel amylose while showing significant background recovery. Implications The high-amylose lines developed may be highly beneficial for diabetic patients and in the bioplastics industry, and should be suitable for growing under Indian conditions.
{"title":"Development of high-amylose maize (Zea mays L.) genotypes adapted to Indian conditions through molecular breeding","authors":"Arushi Arora, Deepak Bhamare, A. K. Das, Shubhank Dixit, Sreya Venadan, Y. K. R., Ramesh Kumar, Dharam Paul, J. C. Sekhar, Sunil Neelam, Sudip Nandi, M. C. Kamboj, S. Rakshit","doi":"10.1071/cp23343","DOIUrl":"https://doi.org/10.1071/cp23343","url":null,"abstract":"Context Amylose is a type of resistant starch with numerous health benefits and industrial applications. Starch from maize (Zea mays L.) usually has an amylose content of ~25%. Aims The aim was to develop high-amylose maize genotypes suitable for human consumption and adapted to Indian conditions. Methods Marker-assisted backcross breeding was used to transfer the mutant ae1 allele from a high-amylose donor from the USA into the three parents (HKI 1344, HKI 1378, HKI 1348-6-2) of two high-yielding white maize hybrids (HM5 and HM12) grown in India. Key results In converted lines, amylose content was 40.40–58.10% of total kernel starch, compared with 22.25–26.39% in parents. The percentage increase in amylose content was 63.70–153.03%. There was a significant amount of background recovery in each backcross generation: 66.80–79% in BC1F1, 72.85–88.60% in BC2F1, and 84.45–93.70% in BC2F2. Overall, the total kernel starch content was reduced (by ~22%) in the ae1-introgressed families. Conclusions The converted lines developed in the study are enriched with kernel amylose while showing significant background recovery. Implications The high-amylose lines developed may be highly beneficial for diabetic patients and in the bioplastics industry, and should be suitable for growing under Indian conditions.","PeriodicalId":517535,"journal":{"name":"Crop & Pasture Science","volume":"2 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140395784","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sorour Arzhang, Reza Darvishzadeh, H. Alipour, Hamid Hatami Maleki, Sara Dezhsetan
Context Maize (Zea mays L.) is one of the most economically important plants of the cereal family; it has value as human food, livestock feed, and as a component of industrial products. Aims This study focused on genetic diversity and existence of genetic divergence among promising maize inbred lines in Iran. Methods A commercial maize 600K SNP (single-nucleotide polymorphism) array was used to inspect genetic variability among 93 maize inbred lines. Key results The rate of transition mutation was twice as high as transversion mutation, and the density of detected SNPs was greater close to telomere regions of maize chromosomes. Considering the fluctuation of observed, expected and total heterozygosity and fixation index values across maize chromosomes, as well as polymorphism information content values, there is a high level of genetic variability among the studied maize panel. In addition, discriminant analysis of the principal components revealed four subpopulations in which the subpopulation ‘Line’ was distinct from other subpopulations and had no genomic overlap with them. Selection signature analysis revealed 177 regions harbouring 75 genes that differentiate among subgroups. Detected genes had a role in the mitogen-activated protein kinase signalling pathway, spliceosome, protein processing in endoplasmic reticulum, and hormone signal transduction. Conclusions We conclude that remarkable genetic diversity and differentiation exists among the studied maize subpopulations. The most differentiated SNPs among the subpopulations were associated with important biological processing genes and pathways. Implications The findings provide valuable insights for future maize breeding programs through exploitation of heterosis, as well as marker-assisted selection.
{"title":"Genetic variability of maize (Zea mays) germplasm from Iran: genotyping with a maize 600K SNP array and genome-wide scanning for selection signatures","authors":"Sorour Arzhang, Reza Darvishzadeh, H. Alipour, Hamid Hatami Maleki, Sara Dezhsetan","doi":"10.1071/cp23288","DOIUrl":"https://doi.org/10.1071/cp23288","url":null,"abstract":"Context Maize (Zea mays L.) is one of the most economically important plants of the cereal family; it has value as human food, livestock feed, and as a component of industrial products. Aims This study focused on genetic diversity and existence of genetic divergence among promising maize inbred lines in Iran. Methods A commercial maize 600K SNP (single-nucleotide polymorphism) array was used to inspect genetic variability among 93 maize inbred lines. Key results The rate of transition mutation was twice as high as transversion mutation, and the density of detected SNPs was greater close to telomere regions of maize chromosomes. Considering the fluctuation of observed, expected and total heterozygosity and fixation index values across maize chromosomes, as well as polymorphism information content values, there is a high level of genetic variability among the studied maize panel. In addition, discriminant analysis of the principal components revealed four subpopulations in which the subpopulation ‘Line’ was distinct from other subpopulations and had no genomic overlap with them. Selection signature analysis revealed 177 regions harbouring 75 genes that differentiate among subgroups. Detected genes had a role in the mitogen-activated protein kinase signalling pathway, spliceosome, protein processing in endoplasmic reticulum, and hormone signal transduction. Conclusions We conclude that remarkable genetic diversity and differentiation exists among the studied maize subpopulations. The most differentiated SNPs among the subpopulations were associated with important biological processing genes and pathways. Implications The findings provide valuable insights for future maize breeding programs through exploitation of heterosis, as well as marker-assisted selection.","PeriodicalId":517535,"journal":{"name":"Crop & Pasture Science","volume":"16 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140286026","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. Sgarbossa, A. D. Lúcio, J. Da Silva, Braulio Otomar Caron, M. Diel, Tiago Olivoto, C. Nardini, O. Alessi, D. Lambrecht
Context Path analysis (PA) is a widely used multivariate statistical technique. When performing PA, the effects of the parameters of the mathematical model relating to the experimental design are disregarded, working only with the average effects of the treatments. Aims We aimed to analyse the implications of statistical assumptions, and of removing mathematical model parameters, on the PA results in oat. Methods A field study was conducted in southern Brazil in five crop years. The experimental design employed was a two-factor 22 × 5 randomised complete block design, characterised by 22 cultivars and five fungicide applications, with three repetitions. Six explanatory variables were measured, panicle length, panicle dry mass, panicle spikelet number, panicle grain number, panicle grain dry mass, and harvest index, and the primary variable yield. Initially, normality and multicollinearity diagnoses were carried out and correlation coefficients were calculated. The PA was performed in three ways: traditional, with measures to address multicollinearity (ridge), and traditional with eliminating variables. Key results and conclusions The occurrence of multicollinearity resulted in obtaining path coefficients without biological application. Removing the model’s parameters modifies the path coefficients, with average changes of 10.5% and 13.3% in the direction, and 24.7% and 23.0% in the magnitude, of the direct and indirect effects, respectively. Implications This new approach makes it possible to remove the influences of treatments and experimental design from observations and, consequently, from path coefficients and their interpretations. Therefore, the researcher will reduce possible bias in the coefficient estimates, highlighting the real relationship between the variables, and making the results and interpretations more reliable.
{"title":"Multivariate assumptions and effect of model parameters in path analysis in oat crop","authors":"J. Sgarbossa, A. D. Lúcio, J. Da Silva, Braulio Otomar Caron, M. Diel, Tiago Olivoto, C. Nardini, O. Alessi, D. Lambrecht","doi":"10.1071/cp23135","DOIUrl":"https://doi.org/10.1071/cp23135","url":null,"abstract":"Context Path analysis (PA) is a widely used multivariate statistical technique. When performing PA, the effects of the parameters of the mathematical model relating to the experimental design are disregarded, working only with the average effects of the treatments. Aims We aimed to analyse the implications of statistical assumptions, and of removing mathematical model parameters, on the PA results in oat. Methods A field study was conducted in southern Brazil in five crop years. The experimental design employed was a two-factor 22 × 5 randomised complete block design, characterised by 22 cultivars and five fungicide applications, with three repetitions. Six explanatory variables were measured, panicle length, panicle dry mass, panicle spikelet number, panicle grain number, panicle grain dry mass, and harvest index, and the primary variable yield. Initially, normality and multicollinearity diagnoses were carried out and correlation coefficients were calculated. The PA was performed in three ways: traditional, with measures to address multicollinearity (ridge), and traditional with eliminating variables. Key results and conclusions The occurrence of multicollinearity resulted in obtaining path coefficients without biological application. Removing the model’s parameters modifies the path coefficients, with average changes of 10.5% and 13.3% in the direction, and 24.7% and 23.0% in the magnitude, of the direct and indirect effects, respectively. Implications This new approach makes it possible to remove the influences of treatments and experimental design from observations and, consequently, from path coefficients and their interpretations. Therefore, the researcher will reduce possible bias in the coefficient estimates, highlighting the real relationship between the variables, and making the results and interpretations more reliable.","PeriodicalId":517535,"journal":{"name":"Crop & Pasture Science","volume":"56 22","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140400143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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