Cultivar Trials Research Articles

Integrating Environmental Covariates into Adaptability and Stability Analyses: A Structural Equation Modeling Approach for Cotton Breeding

Breeding programs rely on genotype-by-environment interaction (GEI) to recommend cultivars for specific locations. GEI describes how different genotypes perform under varying environmental conditions. Several methods were proposed to assess adaptability and stability across environments. These methods utilize various statistical approaches like parametric and non-parametric regression, multivariate analysis techniques, and even Bayesian frameworks and artificial intelligence. The accessibility of environmental data through platforms like NASA POWER allows breeders to integrate this information into a breeding process. It has been done by using multi-omics integration models that combine data across various biological levels to create accurate predictive models. In the context of phenotypic adaptability and stability analysis, structural equation modeling (SEM) offers an interesting approach to integrating environmental covariates. This work aimed to propose a novel approach that integrates weather information into adaptability and stability analysis, combining SEM with the established Eberhart and Russell model. Additionally, a user-friendly applet, denoted ECERSEM-AdaptStab, was made available to perform the analysis. This approach utilized data from 12 cotton cultivar trials conducted across two growing seasons at 19 sites. This approach successfully integrated environmental covariates into a phenotypic adaptability and stability analysis of cotton cultivars. Specifically, the genotypes TMG 41 WS, IMA CV 690, DP 555 BGRR, BRS 286 and BRS 369 RF were recommended for favorable environments, while the genotypes TMG 43 WS, IMA 5675 B2RF, IMA 08 WS, NUOPAL, DELTA OPAL, BRS 335, and BRS 368 RF are more suitable for unfavorable environments.

Analysis of Pearl Millet's G x E Interaction with the Proposed New Index

Developing cultivars that are stable in a variety of conditions has been a problem for plant breeders. The environment can have an impact on a cultivar's phenotypic performance, or different environments can have different effects on different cultivars. Variance resulting from a combination of an individual's genetic composition and the environment in which they were raised is referred to as the genotype-environment interaction. Reducing genotype-environment interaction through breeding stable genotypes facilitates selection of stable, high-yielding genotypes. In multi-environment cultivar trials, AMMI and GGE biplot analyses are frequently utilized to explain G×E interactions. In order to assess breeding material effectively, India's pearl millet agriculture has been split into three main zones, A1, A, and B, based on climatic circumstances. Using AMMI and GGE biplot analysis, the current study assessed the G×E interaction in pearl millet genotypes from Zone-B in India. Based on normalized grain yield and ASV indices, a new weighted index (WI) has been developed to assess stable and high-yielding genotypes. For this zone, the three interaction principal component axes (IPCA1, IPCA2, and IPCA3) have been found to be important. The indices YSI and WI have been used to identify both the high-yield and most stable genotypes, while the AMMI Stability Value (ASV) and Stability Index have been used to find the most stable genotypes. Based on WI, the genotypes G24 and G13 have been identified stable and high yielding genotypes for zone-B.

Relações lineares em genótipos de girassol no estado do Rio Grande do Sul, Brasil

ABSTRACT: The state of Rio Grande do Sul (RS) is the third largest sunflower producer in Brazil. This study verified the existence of linear relationships between grain yield, oil content, and oil yield in sunflower (Helianthus annuus L.) genotypes evaluated in RS. The data on grain yield (GY), oil content (OC), and oil yield (OY) were obtained from 73 sunflower cultivar trials in 21 municipalities in RS from 1999 to 2018. Scatter diagrams were createdto investigate the relationships between the variables GY, OC, and OY. Then, Pearson’s linear correlation coefficient (r) was calculated between the variables, and the Student’s t-test was performed at a 5% significance level. There is a positive and significant linear relationship between PG and OY. However, no linear relationship was found between grain yield and oil content in sunflower genotypes. Additionally, a positive linear association of high magnitude (r = 0.9672) was observed between grain yield and oil yield, while a low magnitude (r = 0.2245) was found between oil content and oil yield.

Registration of ‘Successor’ barley: A two‐row, spring‐habit, feed cultivar with tolerance to imidazolinone herbicides and adaptation to dryland production

Abstract‘Successor’ (Reg. no. CV‐377, PI 702593), experimental designation DH190481, is a two‐row spring barley (Hordeum vulgare L.) released by Oregon Agricultural Experiment Station in 2023. It is notable for tolerance to imidazolinone herbicides and can be planted in a rotation with crops that are treated with these chemicals. Successor is well adapted to dryland production in the Pacific Northwest and is being released as a feed cultivar. This assessment evaluated the cultivar in a multi‐environment cultivar trial in eastern Oregon and Washington and in an on‐farm trial at a commercial partner. It showed strong performance and matched or exceeded expectations set by the only other currently available imidazolinone‐tolerant cultivar adapted to the target growing region, Survivor.

Productivity of a trial of thirteen asparagus genotypes in their eighth year within the IV International Asparagus Cultivar Trial (ISHS)

Productivity of a trial of thirteen asparagus genotypes in their eighth year within the IV International Asparagus Cultivar Trial (ISHS)

Yield, packout and fruit quality results from four lemon cultivar trials in California

Yield, packout and fruit quality results from four lemon cultivar trials in California

Optimizing multi-environment testing in potato breeding: using heritability estimates to determine number of replications, sites, and years for field trials

Multi-environment trials (METs) of potato breeding clones and cultivars allow to precisely determine their performance across testing sites over years. However, these METs may be affected by the genotype × environment interaction (GEI) as noted in tuber yield. Furthermore, trials are replicated several times to optimize the predictive value of the data collected because knowledge on spatial and temporal variability of testing environments is often lacking. Hence, the objectives of this research were to use components of variance from METs to estimate broad sense heritability (H2) based on best linear unbiased predictors and use these estimates to determine the optimum number of sites, years, and replications for testing potato breeding clones along with cultivars. The data were taken from METs in southern and northern Sweden comprising up to 256 breeding clones and cultivars that underwent testing using a simple lattice design of 10-plant plots across three sites over 2 years. Percentage starch in the tuber flesh had the largest H2 in each testing environment (0.850–0.976) or across testing environments (0.905–0.921). Total tuber weight per plot also exhibited high H2 (0.720–0.919) in each testing environment or across them (0.726–0.852), despite a significant GEI. Reducing sugar content in the tuber flesh had the lowest, but still medium H2 (0.426–0.883 in each testing environment; 0.718–0.818 across testing environments). The H2 estimates were smaller when their variance components were disaggregated by year and site, instead of lumping them as environments. Simulating H2 with genetic, site, year, site × year, genetic × site, genetic × year, genetic × site × year, and residual variance components led to establish that two replicates at each of two sites in 2-year trials will suffice for testing tuber yield, starch and reducing sugars. This article provides a methodology to optimize the number of testing size and years for METs of potato breeding materials, as well as tabulated information for choosing the appropriate number of trials in same target population of environments.

Corn and Soybean Production – 2022 Summary

Soybean and corn varieties were tested in replicated field trials at the Southeast Research and Extension Center in Parsons through the Kansas State University variety testing program. In total, nine corn varieties and three maturity checks were tested. Fourteen full season and ten double-cropped soybean varieties were tested, with three maturity checks. Additionally, sorghum and sunflower varieties were tested. The 2022 summer crop growing season was challenging. High temperatures and low rainfall reduced crop production. Crop production was severely impacted by the hot, dry conditions, both across the state and in the cultivar trials at Parsons. No yield results are available for the variety tests from Parsons.

Analyzing the impact of extreme heat events and drought on wheat yield and protein concentration, and adaptation strategies using long-term cultivar trials under semi-arid conditions

Extreme weather events, lower precipitation and higher temperatures play a relevant role in the assessment of wheat yield and protein concentration under future weather conditions in Mediterranean environments. To explore this topic, a dataset of long-term wheat cultivar trials carried out in 17 locations in Andalusia, southern Spain, between 1990 and 2017, and covering a wide range of weather conditions, has been analyzed.The occurrence of maximum temperatures surpassing 32.5°C during heading showed significant correlations with yield, and generated reductions of up to 30% of the maximum observed yield. Similarly, water stress up to 20 days after heading or numerous days with both high temperatures and water stress up to 45 days after heading, also showed significant correlations with yield, and generated reductions of up to 23% and 41%, respectively. Moreover, irrigation showed a very relevant role, with the minimum relative yield increasing from 9% under rainfed conditions to 56% with irrigation supply higher than 150mm. For protein concentration, frequent joint events combining mild temperatures and severe water stresses around heading showed increases of 3 %-units. The future weather conditions projected for southern Spain will enhance risk of yield reduction and protein concentration increases, with a high spatial variability.Earlier sowing dates reduce the coincidence of extreme weather events with critical crop development stages, and thus the effects on yield and protein concentration, even identifying conditions that the impact was fully reversed. Similarly, irrigation during heading mitigated the negative effects of water stress on yield and the positive effects on protein concentration.The combination of long-term cultivar trials under semi-arid weather conditions, modeling and future climate projections constitutes an excellent tool for the assessment of vulnerable/suitable areas, and for the identification of site-specific adaptation measures to ensure the sustainability of wheat-growing areas in southern Europe.

Tomato cultivar trials for productivity, quality, and quality perception in organic farming system

Tomato cultivar trials for productivity, quality, and quality perception in organic farming system

Genotype selection for fiber quality traits in cotton in the Brazilian Northeast

AbstractThe search for cotton (Gossypium hirsutum L.) genotypes gathering high yield and fiber quality is the main objective of breeding programs. The objectives of this study were: (a) to verify which effects contribute the largest fraction of the total phenotypic variance of cotton fiber quality traits and (b) to recommend the best genotypes for these traits. Eight competition trials of cotton cultivars were carried out between the 2017 and 2019 seasons. Field trials were carried out in Alagoinha (crops seasons 2017, 2018, and 2019) and Barbalha (2017 and 2018) in a randomized block design with three repetitions. Fifteen genotypes developed by the cotton plant breeding program of Embrapa Algodão were evaluated. The following fiber quality traits were evaluated: fiber percentage (FP), average boll weight (BW), upper‐half mean length, fiber uniformity (UNIF), short fiber index (SFI), fiber strength (STR), elongation (ELG), micronaire (MIC), and fiber maturity. Genotypic values (GVs) for the evaluated traits were estimated. The total phenotypic variance of the fiber quality traits evaluated is mostly composed of genotypic effects. Only the traits FP, BW, and ELG showed significant genotypes × sites interaction. The genotype G1 has high GVs for the traits FP, BW, fiber length, and fiber uniformity. The G15 stood out by gathering high values for UNIF, SFI, and STR.

Value of Hordeum vulgare L. genotypes in terms of yield and its stability

Our purpose was to determine the value of spring barley (Hordeum vulgare L.) cultivars and lines in terms of yield and its stability. The GGE biplot analysis of competitive cultivar trial data was used. Due to the GGE biplot, the relationships between the barley cultivars and lines under investigation with the environment (years of their cultivation) were visualised. The mega-environment of 2018 and 2020 was the most optimal one for yields from the cultivars, especially Grace, Amil, Troian and Talisman Myronivskyi, while the 2019 environment for Avhur, Margret and Khors. The GGE biplot ranking graphically described the genotypes by average yield and its stability over the three years: Grace, Margret, Amil, Troian, Datcha, Avhur, Khors, Ahrarii, Talisman Myronivskyi and Herkules were high-yielding cultivars; naked cultivars Merlin, Gatunok and Akhiles gave the lowest yields; Grace, Gladys, Gatunok, Yavir, Kontrast and Khors were highly stable cultivars; Amil, Avhur, KWS Bambina and Rezerv were low stable. Of the high-yielding cultivars, Grace and Khors were the most stable ones. The GGE biplot also visualised the comparison of the genotypes with the hypothetical ‘ideal’ genotype by the highest ‘breeding value’: Grace was the best (5.43 t ha–1), Troian was the second best (5.31 t ha–1), followed by Margret (5.27 t ha–1), Avhur, Ahrarii, Krechet and Herkules (5.00–5.22 t ha–1). As a conclusion of the identified patterns, we established the practical and breeding value of the high-yielding and stable cultivars, Grace (5.43 t ha–1) and Khors (5.22 t ha–1), for conditions of different years, as well as the high-yielding and highly responsive cultivars, Amil (5.37 t ha–1) and Avhur (5.22 t ha–1), for the most optimal growing conditions.

Strawberry Cultivar Trials for Yield and Fruit Quality in Subtropical Southern Florida

Strawberry (Fragaria ×ananassa) is grown during the winter months in subtropical southern Florida and must thrive in higher than average temperatures and limestone soils. This is the first strawberry cultivar trial in southern Florida to include ‘Florida Beauty’, ‘Florida Brilliance’, ‘Strawberry Festival’, ‘Florida Radiance’, ‘Sensation FL127’, and ‘Winterstar’. Overall, ‘Strawberry Festival’ and ‘Sensation FL127’ were the top yielding cultivars, with the highest average total yields of 0.7 and 0.8 kg/plant fresh fruit, respectively. ‘Sensation FL127’ had a 36% greater late-season marketable yield compared with ‘Strawberry Festival’. ‘Sensation FL127’ consistently had the greatest soluble solids content (7.6% to 8.7%). Overall, this study demonstrates significant differences in yield and fruit quality among the cultivars tested in southern Florida.

Effects of Fusarium Wilt on Cotton Cultivars with and without Meloidogyne Incognita Resistance in Fields.

Cotton (Gossypium hirsutum) cultivar trials were conducted in four fields (6 trials total) with Meloidogyne incognita (Mi)/Fusarium oxysporum f. sp. vasinfectum (Fov) from 2019 to 2021. Cotton cultivars were divided into groups based on company/Mi resistance: S = susceptible to Mi; R-FM, R-DP, and R-PHY = resistance to Mi in FiberMax®, Deltapine®, and Phytogen® cultivars, respectively; ST 4946GLB2 (moderate resistance to Mi and observed field tolerance to Fov); and ST 5600B2XF (resistance to Mi). The S and R-FM groups had the highest transformed Mi densities LOG10(Mi + 1) (LMi = 3.22 and 3.01, respectively), while R-DP and R-PHY had the lowest LMi (2.21 and 1.85, respectively). Plant mortality (%) was higher for R-DP (28.1%) than for all other groups except ST 5600B2XF (24.8%). Mi-susceptible cultivars averaged 23.3% mortality. Relative yield (0-1 scale) was higher for ST 4946GLB2 (0.706) and R-PHY (0.635) than for R-DP (0.530), ST 5600B2XF (0.578), and S (0.491). All groups except R-DP averaged higher relative yield than the susceptible cultivars. ST 4946GLB2 had the lowest mortality (16.5%) and highest relative yield, while R-DP cultivars had the highest mortality and no difference in relative yield from the Mi-susceptible cultivars. The group of R-DP cultivars had excellent Mi resistance but were susceptible to Fov. No cultivars were identified with high resistance to Fov.

DNA-Based Quantification ofFusarium oxysporumf. sp.vasinfectumin Environmental Soils to Describe Spatial Variation in Inoculum Density

Fusarium wilt of cotton, caused by the soilborne fungal pathogen Fusarium oxysporum f. sp. vasinfectum (FOV), occurs in regions of the United States where cotton (Gossypium spp.) is grown. Race 4 of this pathogen (FOV4) is especially aggressive, and does not require the co-occurrence of the root knot nematode (Meloidogyne incognita) to infect cotton. Its sudden appearance in far-west Texas in 2016 after many years of being restricted to California is of great concern, as is the threat of its continued spread through the cotton-producing regions of the United States. The aim of this research was to analyze the spatial variability of FOV4 inoculum density in the location where FOV4 is locally emerging, using quantitative and droplet digital PCR methods. Soil samples collected from a field with known FOV4 incidence in Fabens, Texas, were analyzed. Appreciable variation in inoculum density was found to occur at spatial scales smaller than the size of plots involved in cultivar trial research, and was spatially autocorrelated (Moran's I, Z = 17.73, P < 0.0001). These findings indicate that, for cultivar trials, accounting for the spatial distribution of inoculum, either by directly quantifying it or through the use of densely distributed calibration checks, is important to the interpretation of results.

Low Temperature Is Critical for Jujube Grafting Success in Frost-prone Northern New Mexico

The increased popularity of jujube (Ziziphus jujuba) combined with the difficulty of grafting have limited supplies of grafted trees in the United States. From 2011 to 2020, grafting was practiced for cultivar amplification after importation and cultivar trials in frost-prone northern New Mexico. Grafting success was related to not only grafting techniques but also climate factors. Bark grafting, whip/tongue grafting, and cleft grafting were commonly used in nurseries. Low temperatures had a critical role in jujube grafting success in marginal regions and were more important than the grafting technique. If frost occurs before or near the leafing time, then grafting should be delayed until the rootstocks are determined to be healthy and alive. If frost occurs after grafting, then grafting failure and/or thin and small plant percentages increased. If only branchlets appear after grafting, then pinching branchlets could stimulate new shoot growth.

Effect of Nitrogen on the Properties of Flax (Linum usitatissimum L.) Plants and Fibres.

This paper presents a three-year study of the influence of different amounts of nitrogen on the properties of flax plants and fibres. At the same time, the acclimatization ability of five different cultivars of fibre flax was estimated through the valorisation of their morphological (technical stem length, stem thickness) and physical-mechanical properties of the fibres (length, fineness, tenacity). Cultivar trials with fibre flax were set up across three years (2008–2010) at the following locations: the experimental fields of the Faculty of Agriculture in Zagreb on anthropogenized Eutric Cambisol and the College of Agriculture at Križevci on pseudogley on level terrain. The selected cultivars were fertilized without and with different nitrogen rates (0, 30, 60 and 90 kg/ha) in different time. The trials were carried out according to the RCBD in four replications. According to the results of the three-year study of flax and fibres, significant differences were established among the cultivars and among the added nitrogen rates under study. Based on the results of the morphological and textile-technological properties of flax, the cultivars Viola and Agatha achieved higher values at the location of Križevci, where it was not necessary to add more than 30 kg N/ha.

Crop Production Summary - 2021

Soybean and corn varieties were tested in replicated field trials at the Southeast Research and Extension Center in Parsons through the Kansas State University variety testing program. In total, 26 corn varieties and 28 soybean varieties were tested. Weather during 2021 was near average for both rainfall and temperature, though there were periods of high rainfall and high temperatures. Corn and soybean production was also near average, both across the state and in the cultivar trials at Parsons.

AGRONOMIC PERFORMANCE OF FORAGE CORN CULTIVARS IN HIGH AND LOW PHOSPHORUS

Silage produced with the entire corn plant (Zea mays L.) has been an increasingly widespread alternative as bulky food for ruminants. One of the main care in crop management with a view to silage production is related to fertilization. In tropical soils (such as those in the south of the state of Pará) phosphorus is the most limiting nutrient for agricultural production. Because of the above, the present work aims to know the agronomic performance of forage corn cultivars in high and low phosphorus in the South of the state of Pará. For this, two competition trials of maize cultivars under contracting conditions of phosphorus (P) were carried out: high P (100 kg ha-1 from P2O5) and low P (50 kg ha-1 from P2O5), using as a source the simple superphosphate (18% from P2O5). The experimental design was randomized blocks with fourteen treatments and three replications. The treatments were composed of fourteen cultivars, eleven of these were the hybrids: AG1051, AG8088, BM3061, BR2022, BR205, BR206, BRS3046, CR-120, M274, ORION, and PR27D28, and the other three were open pollination populations (PPA): AL BANDEIRANTE, ANHEMBI, and CATIVERDE. The variables evaluated were: height of insertion of the ear (AE) and plant height (AP), total weight per plant (PPT), the weight of the cob with straw (PESP), and weight of the ear without straw (PESP). The medium was compared by the test of groups of Scott and Knott, the 5% of significance, using the program SISVAR. Considering the overall performance of the cultivars, in all traits evaluated in the two trials, the sum of their results points to the cultivar BRS3046 as the most promising for silage production. The high test P, as expected, has been used about the low P.

Influential Points in Adaptability and Stability Methods Based on Regression Models in Cotton Genotypes

The aim of this work was to answer the following question: can influential points modify the recommendation of genotypes, based on regression methods, in the presence of genotype × environment (G × E)? Therefore, we compared the parameters of the adaptability and stability of three methodologies based on regression in the presence of influential points. Specifically, were evaluated methods based on simple, non-parametric and quantile (τ = 0.50) regressions. The dataset used in this work corresponds to 18 variety trials of cotton cultivars that were conducted in the 2013–2014 and 2014–2015 crop seasons. The evaluated variable was the cotton fiber yield (kg/ha). Once we noticed that the effect of G × E interaction is significant, the statistical procedures adopted for the adaptability and stability analysis of the genotypes. To verify the presence of a possible influential point, we used the leverage values, studentized residuals (SR), DFBETAS and Cook’s distance. As a result, the influential points can modify the recommendation of genotypes, based on regression methods, in the presence of G × E interaction. The non-parametric and quantile (τ = 0.50) regressions, which are based on median estimators, are less sensitive to the presence of influential points avoiding misleading recommendations of genotypes in terms of adaptability.