Analyzes of plant growth throughout the crop vegetative cycle are important to know the dynamics of the plant development. Thus the objective of this work was to study the development ofpotatogenotypes throughout the crop cycle, in three environments. Experiments were conducted in Canoinhas-SC, Pelotas-RS, and Brasília-DF, Brazil, in the 2018 crop season. A randomized complete block experimental design with three replicates was used. Traits related to different plant parts of clones F183-08-01 and F50-08-01 and the cv. Asterix were evaluated as a function of time and, at the end of the cycle, for tuber yield. The two clones were found to have high tuber yields, but later development than ‘Asterix’; consequently, its management must be adapted to this trait. Leaf mass, leaf number, leaf area index and root mass plus stems were correlated with each other, and leaf area index, leaf number and leaf mass can be quantified through only one of these traits, due to the high correlation between them. There were also positive and significant correlations between the height of the tallest stem and the root plus stem mass and the tuber mass, indicating that more vigorous plants have higher tuber yield.
For multicategoric data (Table 1), a dissimilarity matrix was obtained based on a coefficient of simple matching. Sweet potato is a hexaploid species (Azevedo et al., 2015); there are many different band patterns. From the presence and absence of each DNA fragment, the dissimilarity matrix was designed with a Jaccard similarity coefficient (Jaccard, 1901). For multicategoric, molecular and combined data, a cutoff equal to the average dissimilarity was performed. The R program (R Core Team, 2014) and ade4 package (Dray & Dufour, 2007) were used for the estimates of dissimilarity matrices. To combine molecular and multicategoric data, an algebraic sum of these two matrices was calculated (Alves et al., 2013), generating a new matrix for joint analysis. The correlation between matrices and their significance were estimated by Mantel test with 1,000 permutations using package ade4 with ‘mantel.rtest’ function in R software (R Core Team, 2014). To obtain the dendrogram, the unweighted pair group method with arithmetic mean (UPGMA) grouping method was used, with ‘hclust’ function.
Malondialdehyde (MDA) results from lipid peroxidation in cells and this product remains an important indicator of oxidative stress in several studies with plants (Chen et al. 2017). The increase in Si concentration in the presence of Al decreased shoot MDA concentration in both genotypes (Fig. 5). Thus, Si significantly mitigated the damage caused by Al in the lipid membrane, suggesting that plants growing in the presence of Si operate with metabolic pathways that remove more oxygen radicals in this organ. Shi et al. (2010) observed that Si promoted a decrease in peroxidation of membrane lipids by the activation of the enzymatic and non-enzymatic antioxidant system, possibly by preventing MDA accumulation in shoots. Si caused lower reduction in the growthof this organ. These data also suggest that Si application in potato plants can effectively increase the defense capability ofpotato plants against oxidative stress induced by Al toxicity.
Within each genotype, the increased Si concentration did not alleviate the toxic effect of Al in the shoot. However, in the roots of the Al-tolerant genotype, Si mitigated the toxic effects of Al in comparison to the treatment in which only Al was present in the nutrient solution. Probably, Si is operating on the chelation and/or internal Al compartmentalization in this genotype, as the acid pH of the nutrient solution used in this study (pH 4.5) impedes the formation of hydroxyaluminosilicate complexes in the solution, because only low concentrations of Al hydroxide are found in solutions with low pH (Kidd et al. 2001). The role of Si in the tolerance of plants to biotic and abiotic stresses can be attributed to changes in the properties of the cell wall. The esterification of cell wall components by Si can reduce the Al bond in the cell wall, causing a minor negative effect of this metal on the roots. Also, it has been reported that the inhibition of root growthof corn plants exposed to Al was lower in plants pre-treated with Si (Kidd et al. 2001).
The objective of this paper was to determine the association of a SNP in the m-calpain gene at position 316 with growth and quality of meat traits of steers grown on pasture. Fifty-nine Brangus and 20 Angus steers were genotyped for CAPN1 316. Warner Bratzler shear force was measured in l. lumborum samples after a 7-day aging period. A multivariate analysisof variance was performed, including shear force (WBSF), final weight (FW), average daily gain (ADG), backfat thickness (BFT), average monthly fat thickness gain (AMFTG), rib-eye area (REA), and beef rib-eye depth (RED) as dependent variables. The CAPN1 316 genotype was statistically significant. Univariate analyses were done with these variables. The marker genotype was statistically significant (p < 0.05) for WBSF (kg: CC: 4.41 ± 0.57; CG: 5.58 ± 0.20; GG: 6.29 ± 0.18), FW (kg: CC: 360.23 ± 14.71; CG: 381.34 ± 5.26; GG: 399.23 ± 4.68), and ADG (kg/d: CC: 0.675 ± 0.046; CG: 0.705 ± 0.016; GG: 0.765 ± 0.014) Shear force, final weight and average daily gain were significantly different according to the CAPN1 316 marker genotypes. The marker genotype was sta- tistically significant in the multivariate analysis (p = 0.001). The first characteristic root explained 89% of the differ- ences among genotypes. WBSF, FW and ADG were the most important traits in the first vector, indicating that animals with the marker genotype for lowest WBSF also have the lowest FW and ADG.
Grain yield and yield components were evaluated at harvesting in the 2015 and 2015/2016 growing seasons. Then, an analysisof variance and F test were performed for all variables. The analysisof variance was performed considering the effects ofgenotypes. For the significant data, the LSD test (p < 0.05) was performed. These analyses were carried out using the SAS statistical software. Data of common bean biomass accumulation and nutrient accumulation in leaves, during the common bean life cycle, were subjected to a process of curve fitting to a polynomial model. In addition, a Person’s correlation of nutrients accumulation in common bean leaves was performed with number of pods per plant, number of grains per pod, mass of 100 grains and grain yield.
At harvest, grain yield, shoot dry weight and panicle numbers were determined. Plant material (shoot and grain) was dried in a forced-draft oven at about 70°C until constant weight and milled. Ground material was digested with 2:1 mixture of nitric and perchloric acids for chemical analysis. Micronutrients Zn, Cu, Fe and Mn were then analyzed by atomic absorption spectrophotometry. Grain harvest index (GHI), Zn harvest index (ZnHI) and apparent Zn recovery efficiency (ARE-Zn) were calculated with the following equations:
Several relevant characteristics may still be included in the selection of drought-tolerant genotypes, such as root depth and volume, leaf chlorophyll content, leaf water potential, leaf temperature, stay-green trait, leaf area index and plant growthanalysis. These traits might be correlated with crop yield (Zheng et al. 2009, Ali et al. 2017). The interval between male and female flowering has also been suggested as a critical phenotypic characteristic of the flowering process, as it relates to the number of grains per ear and yield stability under stress (Araus et al. 2012).
evaluated the total and marketable tuber yield, total and marketable tuber number, percentage of marketable tuber dry weight, average marketable tuber weight and plant growth period. The experimental design was randomized blocks in split plot scheme, with fertilizer doses allocated as main plots and genotypes as subplots, with three replications. We did not observe significant interaction for any analyzed variable. The clone CL 02-05 showed higher total and marketable tuber yield compared to the other cultivars, mainly due to its higher production of tuber number. However, we observed a high amount of tubers not suited for commercialization from the clone CL 02-05. Cultivar BRS Camila produced fewer marketable tubers than cultivar Ágata in crop season 2014/15, but without difference in marketable yield. On the other hand, plants of cultivar BRS Camila had a longer growth period of 7 days and the tubers of this cultivar accumulated higher percentage of dry weight compared to cultivar Ágata. The new tested genotypes had yield response similar to cultivar Ágata when submitted to doses of 4-14-8 NPK fertilizer. Therefore, the fertilization management of these new genotypes may be similar to that used with cultivar Ágata.
The fraction of transpirable soil water (FTSW) ap- proach has been widely used for the evaluation of plant response to water deﬁ cit (Bindi et al., 2005; Davatgar et al., 2009; Muchow and Sinclair, 1991; Ray and Sin- clair, 1997). The FTSW threshold indicates the timing of stomatal clossure in response to soil water deﬁ cit (Ray and Sinclair, 1997; Sinclair and Ludlow, 1986) and the degree of tolerance to water deﬁ cit. Genotypes with delayed wilting during a soil drying cycle have a high FTSW threshold (Devi et al., 2009). The FTSW thresh- old has been determined for many annual agricultural crops (Amir and Sinclair, 1991; Davatgar et al., 2009; Devi et al., 2009; Gholipoor et al., 2012; Lecoeur and Sinclair, 1996; Muchow and Sinclair, 1991; Ray and Sin- clair, 1997; Sinclair and Ludlow, 1986), some perennial fruit crops, grapevine (Vitis vinifera) (Bindi et al., 2005), and some forest crops, Eucalyptus grandis and Eucalyptus saligna (Martins et al., 2008). Recently, researchers have shown genetic variations in FTSW threshold among cul- tivars of the same crop, such as soybean (Glycine max) (Hufstetler et al., 2007), peanut (Arachis hypogaea) (Devi et al., 2009), pearl millet (Pennisetum glaucum) (Kholova et al., 2010) and sorghum (Sorghum bicolor) (Gholipoor et al., 2012).
Brazil is the largest world producer of papaya and the third largest exporter despite of only 1.5 to 2.0% of its production is exported. Such an underexplored exportation potential highlight the necessity for physiological studies on new cultivars and hybrids to verify their agronomic and commercial viability. Two Brazilian states, Bahia and Espirito Santo, are responsible for 80% of national production. Papaya can also be an agricultural alternative to north / northeast of Rio de Janeiro, because the region is close to consumer centers and have similar environmental conditions of the most productive regions. Nevertheless, it is worth to develop cultivars that can express the highest yield potential in this region. The aim of this work was to characterize physiologically two hybrids developed for the north/northeast of Rio de Janeiro (UENF/Caliman 01 and JS12) in comparison with three top commercial genotypes (Golden, Sunrise Solo 7212 and Tainung) of Carica papaya L.. The cv. Golden presented the lowest shoot and root growth, the lowest height, shrunk diameter, specific leaf weight, less efficiency in electrons transport per sample area and show the lowest ability to synthesized total chlorophylls in comparison with the others genotypes. At noon, this genotype showed higher stomatal conductance, related to the leaf-air vapor pressure deficit, which lead to higher transpiration rate and intrinsic water use efficiency. No differences were detected in the photosynthetic rates among the five genotypes suggesting that the UENF`s hybrids are endowed with similar photosynthetic capacity and morphological characteristics to the top commercial genotypes. The relevance of this characterization to drive future successful genetic improvement programs will be discussed.
genotype of Plinia sp. (jabuticaba tree) is more adapted to orchard conditions, based on the measures of stem growth and primary shoots. During a three-year period, the initial growthof jabuticaba tree genotypes from the native fruit collection of the Experimental Station of the Universidade Tecnológica Federal do Paraná - Câmpus Dois Vizinhos was evaluated. These genotypes included seedlings from forest fragments of the southwestern region of Paraná State and some from Minas Gerais State, Brazil. Analysisof variance (ANOVA) was performed, in a 29 x 3 factorial design, with three replicates in each treatment. Phenotypic adaptability and genotypic stability were evaluated based on the data obtained by the following methods: Eberhart and Russell, Lin and Binns and the AMMI. The analyses were carried out through the computer programs GENES and Stability. The methods that were tested to determine the adaptability and stability of the growth behaviour of the jabuticaba tree did not present consistent patterns in the results. However, the genotype generally referred to as 'Vitorino' was the most suitable for open-air cultivation.
The contribution of legume green manures to nitrogen credit and improvement ofpotato yield in different production systems has been quantified. However, the effi- ciency of legume green manures incorporation timing and nitrogen doses as a unique N source on potatogrowth and yield has not been studied. The current study aimed to in- vestigate the influence of incorporation timing and N doses of sunhemp (Crotalaria juncea L) on potatogrowth and productivity. The experiment was conducted in Viçosa MG, Brazil in 2011. Eight treatments (2×4) from sunhemp residue as full dose incorpo- ration (FI) at 15 days before planting and split incorporation (SD) as 50% before plant- ing and 50% at 15 days after planting combined with 4 N doses (75, 150, 225 and 300 kg ha -1 ). In addition, 2 extra controls were included whereas, MN (250 kg ha -1 recom- mendation) and N0. Treatments were arranged in a split-plot in a complete randomized block design with 4 replicates. Potato N nutrition status was determined in the fourth expanded leaf from plant apex employing SPAD, CHLT and N-total content at 38 DAP. Dry matter production, N accumulation and partitioning between foliage and tu- bers, N recovery (NR) and N recovery efficiency (NRE) as well as apparent N recovery (ANP) was measured before senescence at 85 DAP. At harvest, 103 DAP, fresh yield and its components, dry matter content (%) and production (kg ha -1 ) as well as nitrogen use efficiency (NUE) was evaluated. In addition, sunhemp residue N mineralization and dry matter breakdown within each application time were accompanied using litter bags. Data were subjected to ANOVA and regression analysis (p<0.05). Comparison between sunhemp treatments and MN control was carried out by Dunnett test (p<0.05). In addition, Pearson correlation between N nutritional indices and marketable and total yield for sunhemp treatments was tested (p<0.05).
There are available molecular markers for the Ry adg and Ry sto genes that can select genotypes that are resistant to PVY. Sorri, Watanabe and Valkonen (1999) identified a CAPS marker, which is designated ADG2/ BbvI, linked to the Ry adg resistance gene and Kasai et al. (2000) developed the SCAR markers, RYSC3 and RYSC4, for the same gene (RYSCR), which has been widely used by plant breeders for its high selection efficiency and with different objectives as follows: determining the genetic constitution of PVY-resistant clones derived from two-parent crosses through the analysisof progeny (Ribeiro et al., 2006; Andrade et al., 2009 ), screening of PVY resistance genes in GenBank (Dalla Rizza et al., 2006; Whitworth et al., 2009) and detecting markers that are closely linked to genes imparting resistance to multiple pathogens, including the Ry adg , Gro1 (confers resistance to nematodes of the Globodera genus) and Rx1 genes for extreme resistance to PVX (Gebhardt et al., 2006). Ottoman et al. (2009) also used this marker for the validation and implementation of marker-assisted selection in the selection of tetraploid potatogenotypes in breeding programs.
Later, the number of galls, reproduction factors and number of protuberances were assessed by ANOVA and the averages of each treatment grouped together by the Scott-Knott test at 5% error probability, through the software SASM- Agri (CANTERI et al., 2001). In addition, the values of variables, number of protrusions and reproduction factor were correlated by Pearson correlation analysis, using the statistical software SAS® (SAS 9.3, SAS Institute, Cary, North Carolina, USA). The resistances ofpotatogenotypes were classified according to the FR values, considering as tough those whose nematode presented FR <1.00 and susceptible, those with FR> 1.00.
By the joint analysisof proteins and isozymes in tubers and isozymes in leaves, the smallest similarity (0.45) was shown by Eliza and C-1485-2-87 genotypes and the highest (1.00) by Catucha and 2AC-917-7-80; C-1226-35-80 and C-1684-7-93; Baronesa, Baronesa p.s. and Baronesa w.; C-1485-2-87 and C-1485-6-87. The genotypes were also organized in two groups (Figure 1). Eliza formed one group and the other ten subgroups, varying from one to 13 accesses per subgroup, formed another group. Data of electrophoretic analysisof tubers and leaves permitted to separate the 27 genotypes analyzed. Similarly, Augustin & Costa (1992), when characterizing 12 potato cultivars with isozymes, used leaves and tubers and did not differentiate three genotypes (Baronesa, Cerrito Alegre and Santa Silvana). Rocha et al. (2002), using isozymes and protein analysis in tubers, separated nine genotypesof Solanum tuberosum L., in eight groups, and only one of them was formed by two cultivars (Baronesa and Macaca). Douches & Ludlam (1991) were able to separate 112 potato cultivars in 95 groups, however, they used 13 isozyme systems, including some used in this work. Moore & Durham (1992) reported that the main difficulty in using isozymes for identifying the genotypes consists of the possibility of the lack of enough enzyme polymorphism for cultivar identification. This may be attributed to the inherent lack of polymorphism, the nature of species, the lack of genetic variability in the studied cultivars or the small number of analyzed loci.
Seeds of two rice (Oryza sativa L.) genotypes (IR4630 and IR15324) were obtained from the International Rice Research Institute, Manila, Philippines. Seeds were soaked for 24 h in distilled water and transferred to a growth cabinet where they were allowed to germinate on the surface of nylon mesh placed over the nutrient solution of Yoshida et al. (1976), but modified by halving the phosphate concentration (earlier experiments with full-strength concentration of phosphate exhibited phosphate toxicity in the presence of external NaCl). In addition, NaH 2 PO 4 .2H 2 O as the phosphate supplement in the original protocol was replaced for KH 2 PO 4 and K 2 HPO 4 (to reduce Na + concentration in the non-salinised
shoot and root yields were determined at 180 DAA. The software R was used for data analysis. The data were subjected to analysisof variance and significant means were compared by the Scott-Knott test. Phytotoxicity and branch growth data were subjected to regression analysis, with graphical representation in multivariate grouping, fitting the data of each subplot to a quadratic model, using the function lm of the program R. The coefficients of the fitted model of each subplot were subjected to multivariate analysis. The Tocher’s optimization method was used to group the curves (CRUZ; CARNEIRO, 2006). Subsequently, the average of the treatments that composed each of the groups was considered for new data fitting grupos (FIORINI et
Potato is responsive to intensive agricultural input use; however, it can be produced in less intensive production systems (such as the organic system) by using appropriate production techniques and genotypes adapted to this system. This study aimed to evaluate the performance of advanced potatogenotypes for tuber yield under conventional and organic production systems, in order to select potential genotypes to become new cultivars adapted to these systems. Fifteen advanced potato clones and two controls were evaluated under organic and conventional production systems, in 2016 and 2017, in Brasília-DF, Brazil. The experimental design was randomized blocks with three replicates and plots composed of two rows with 10 plants each, spaced 0.35 m between plants and 0.80 m between rows. Total (mass) and marketable (mass and number of tubers) productivities were evaluated. Variance analysis showed significant differences among genotypes for all traits. Despite the lower average tuber yield in the organic system, selecting genotypes with high potential productivity was possible in this system, such as F158-08-01 and F158-08-02, showing high marketable tuber yield, with values equivalent to the conventional system. Clones F102-08-04, F13-09- 07, F-18-09-03, F-183-08-01, F-21-09-07, F31-08-05, F63-10-07 and F97-07-03 also outperformed the control cultivars in organic system. For conventional system, F158-08-01, F158-08-02 and F183-08-01 were superior, and F18-09-03, F21-09-07, F63-10-07, F97-07-03, PCDINV10 and PCDSE090 showed performance similar or superior to the most productive control (cultivar Asterix). Genotypes F158-08- 01 and F158-08-02 were superior in both conventional and organic systems, with potential to become new cultivars recommended for both production systems.
Analyses were performed with the Selegen REML/BLUP software (Resende 2016) using model 20 (randomized blocks, unrelated clone test, one observation per plot), given by y = Xr + Zg + e, where y is the vector of the known data observed; r is the vector of repeating effects (fixed effects); g is the vector of genotype effects (random effects); e is the vector of errors or residuals (random); and X and Z are the incidence matrices for these effects. The unrelated clone test (model 20) was chosen because preliminary analysis identified that the variation between families was lower than the variation within a family. This greater variation within a family than between families is because the sweet potato is a self-incompatible hexaploid species with multiple allelism for several loci, which provides considerable genetic variability. Genetic parameters and variance components were estimated. The genetic parameters and variance components included genetic variance σ 2