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Genetic Diversity and Heterotic Orientation of South Africa Maize Inbred Lines Towards Tropical and Temperate Testers
Siphiwokuhle Funani Shandu, John Derera, Kingston Mashingaidze, and 1 more
published 20 Jul, 2021
Read the published version in Euphytica →
An efficient hybrid breeding program defines and utilizes few heterotic groups. The objectives of this study were to determine genetic diversity and alignment of South Africa maize inbred lines collection towards tropical and temperate testers. Forty-two maize inbred lines were genotyped with 56110 single nucleotide polymorphism (SNP) DNA markers, using the Illumina MaizeSNP50 Bead chip. The 42 lines were crossed to two tropical and two temperate inbred line testers. The testcrosses were evaluated across seven environments, in South Africa, during 2014-2016. Genotypes and specific combining ability (SCA) effects of hybrids were significantly different (P<0.05) for grain yield. There was a weak correlation between molecular genetic distances and both grain yield mean and specific combining ability effects of hybrids, indicating that productivity of maize inbred lines could not be reliably determined based on molecular genetic distances. The SCA data was capable of classifying these maize inbred lines into three heterotic groups with respect to both tropical and temperate testers. Only a few lines could not be grouped on the basis of SCA data. The study also indicated high level of diversity among the maize inbred lines, which was shown by both the dendogram and molecular genetic distances. The SNP marker data classified the inbred lines into 11 clusters that could be simplified into three major groups of normal maize endosperm and two groups of quality protein maize (QPM) endosperm types. However, the SNP data indicated that maize lines were more aligned towards tropical than temperate inbred testers. This information would be useful for simplifying heterotic classification of the lines with profound implications for breeding progress.
Plant Molecular Biology and Genetics
Plant Physiology and Morphology
Heterotic groups
maize inbred lines
single nucleotide polymorphism
specific combining ability
temperate and tropical maize testers
Advances in maize breeding have an important role in continually developing and deploying new maize cultivars, exhibiting improved grain yield and desirable agronomic characters. The strength and success of any breeding program depends on a well-established and properly arranged germplasm (Rajendran et al., 2014), which provides potential exploitation of maximum heterosis in crosses (Bidhendi et al., 2012; Librando and Magulama, 2008). Therefore, identification of heterotic groups (HGs) and heterotic patterns is the principal step towards developing a well-established germplasm (Barata and Carena, 2006; Delucchi et al., 2012) for a hybrid oriented breeding programme. Melchinger and Gumber (1998) defined a heterotic group as a group of related or unrelated genotypes from the same or different populations, which show similar combining ability and heterotic response when crossed with genotypes from other genetically different groups, whereas heterotic pattern is observed when a cross between a specific pair of two heterotic groups expresses high level of heterosis.
Classification of germplasm into heterotic groups offers several advantages in most breeding programs. When inbred lines from different known and unknown origins are used, a large number of hybrid combinations are made which are later evaluated in multi-location environments (Bidhendi et al., 2012). However, this is labour-intensive, lengthy and costly (Aguiar et al., 2008). However, when heterotic groups are formed, undesirable combinations are avoided by crossing inbred lines from the existing and divergent groups (Aguiar et al., 2008). This allows the exploitation of maximum heterosis (Melchinger and Gumber, 1998) among selected lines in hybrid combination, reduces the chance of missing superior hybrids and subsequently improves breeding efficiency. According to Fan et al. (2009) breeding efficiency is the percentage of superior hybrids, which are obtained relative to the total number of crosses made between lines from distinct heterotic groups in a breeding program. The employment of simple heterotic groups would simplify germplasm management (Fan et al., 2003). Selecting parental lines from defined heterotic groups is rapid and efficient (Kanyamasoro et al., 2012). The information on simplified heterotic orientation is crucial for setting up an efficient maize breeding program.
Knowledge of combining ability among maize inbred lines in the program is paramount for establishing heterotic orientations. General combining ability (GCA) and specific combining ability (SCA) as defined by Sprague and Tatum (1942) data are used to determine utility of maize inbred lines. They reveal the ability of inbred lines to combine amongst each other during hybridization and transmit the desirable genes to the F1 crosses (Fasahat et al., 2016). A survey of the literature indicates that SCA data is an important statistical tool for classifying maize germplasm into heterotic groups. The SCA data has a high predictive value for F1 grain yield than heterosis data (Betran et al., 2003). However, the SCA data can be used together with other methods that are cheaper and even more precise, because they are not affected by genotype x environment interaction effects. This includes molecular markers such as SNP genotyping.
Genotyping maize inbred lines with molecular markers and pedigree analyses are some of the methods which can be used to establish levels of diversity and classifying germplasm into potential heterotic groups. These methods have been reported in the literature (Parentoni et al., 2001; de Pinto et al., 2003; Fan et al., 2003; Fan et al., 2004; Menkir et al., 2004; Barata and Carena, 2006; Aguiar et al., 2008; Badu-Apraku et al., 2013; Rajendran et al., 2014). Effectiveness of these methods in classifying germplasm is mainly validated by estimating SCA of the hybrids using the line by tester method. The line x tester mating scheme utilizes a few divergent testers of known heterotic groups to determine heterotic orientation of inbred lines. Among other tools, the line x tester mating scheme has been widely used and reported in the literature (Vasal et al., 1992; Menkir et al., 2003; Li et al., 2007; Aguiar et al., 2008; Fan et al., 2010; Rajendran et al., 2014; Fasahat et al., 2016).
The public maize germplasm lines in South Africa have been maintained in at least seven heterotic groups since the beginning of professional maize breeding in the country. These heterotic groups have been utilised extensively in different combinations to develop commercial maize hybrids, since the Saunders and Gevers eras (Fourie and Gevers, 1987; Gevers and Whythe, 1987; Gevers and Lake, 1998). The use of a large number of heterotic groups from different populations complicates the breeding process and decision making during selection of parental lines. Employment of many heterotic groups is associated with several major drawbacks, including high costs of making and evaluating hybrids, and extended timeline to obtain results (de Pinto et al., 2003; Aguiar et al., 2008; Bidhendi et al., 2012) and subsequent reduction in breeding efficiency (Fan et al., 2014). This prompts the need to simplify the heterotic classification of the lines in South Africa for use in breeding.
Due to climate change, there is need to continuously introgress and incorporate germplasm from other countries, such as tropical Africa, tropical South America and USA temperate maize inbred lines. This would enhance genetic diversity and adaptation of the lines to climate change effects, such as increasing frequency and severity of drought, and global warming among other challenges.
Given the foregoing, the objectives of the current study were to determine diversity of South Africa maize inbred lines, and investigate their orientation towards the widely utilized tropical and temperate testers. The use of tropical and temperate testers was prudent because South Africa maize production falls within subtropical to warm temperate conditions. In this regard, both tropical and temperate maize germplasm could be exploited to develop productive hybrids, using a simplified heterotic classification system.
Forty-two maize inbred lines were selected from the Agricultural Research Council of South Africa maize germplasm database. Six representative maize inbred lines were randomly selected from each of the seven traditional heterotic groups. The seven heterotic groups were described by fore-bearers of the public maize breeding programs in the region, such as Saunders, Gevers, Olver, Fourie and others (Gevers and Whythe, 1987; Gevers and Lake, 1998; Olver, 1998) and Fourie (2017, personal communication). According to the literature, the inbred lines used were developed from germplasm which was introduced from the USA, Australia and also mainly from the local open-pollinated varieties which mostly originated from the USA corn-belt (Saunders, 1942; Gevers, 1997). There is a possibility of infusion of temperate and tropical genetic backgrounds through both incorporation and introgression of USA's temperate germplasm, in South Africa. Therefore, it was prudent that the 42 lines were crossed with four testers, representing the heterotic Groups A and B of both tropical and temperate origin. The maize inbred line testers were represented by the International Maize and Wheat Improvement Center's (CIMMYT) tropical testers from Group A (CML312) and Group B (CML444). The temperate testers were represented by the Group A (B73) and Group B (MO17) inbred lines of the USA. These testers and their derivatives are widely used worldwide. The B73 and MO17 maize testers are temperate inbred lines representing the US Reid (heterotic Group A) and Lancaster heterotic groups (heterotic group B), respectively. These testers were developed by the University of Missouri and Iowa State University, respectively. The CML312 and CML444 are CIMMYT tropical maize inbred lines that were developed by the CIMMYT breeding program in Mexico and Harare in Zimbabwe, respectively. The CML312 is an intermediate maturing and subtropical line that is drought tolerant. The CML444 is a late maturing and mid-altitude or subtropical adapted inbred line. According to CIMMYT (2001), the heterotic Group A to which CML312 belongs consists of the pro-Tuxpeno (Mexico), Kitale (Kenya), BSSS and N3 (Zimbabwe) germplasm types. Most of the germplasm which is aligned to this group is of more dent grain texture. The CML444 is the counterpart of the CML312 in CIMMYT's heterotic Group B. It corresponds to the ETO, Ecuador 573, Lancaster and the SC (Zimbabwe) germplasm (CIMMYT, 2001). The germplasm lines in this group tend to be of a flint grain texture type in the CIMMYT heterotic system. CML444 is drought and low nitrogen tolerant (CIMMYT, 2001). The N3 and SC heterotic pattern has been reviewed and discussed in detail (Derera and Musimwa, 2015; Musimwa and Derera, 2015).
Experimental Design and Management
Field experiments were conducted at the Agricultural Research Council's Summer Grain Crops Institute station, in Potchefstroom (26.740S; 27.080E; altitude 1349 m) and the Cedara Research Station (29.540S; 30.260E; altitude 1068 m), in South Africa, during the 2014/15 and 2015/16 summer season. Rainfall amount was below average of the long-term weather data of the previous 29 growing seasons (29 years). During the 2015/16 season, the Potchefstroom Station received 67% and Cedara got 78% of the long term average total rainfall of 541 mm and 662 mm, respectively; while both stations received 93–95% of the long term total rainfall in the 2014/15 season. The 2015/16 season was characterised by the El Nino associated drought, which affected the whole Southern Africa region. Maximum daily average temperatures were at least 20C above the long term average of 290C and 250C at Potchefstroom and Cedara stations, respectively. The average night or minimum temperatures were at least 10C below the long-term average of 150C and 140C at Potchefstroom and Cedara, respectively.
All trials were laid out as α-lattice design with two replicates within the sites. A compound fertiliser (NPK, 3:2:1) was applied as a basal fertiliser prior to sowing, at a rate of 25 kg N ha− 1, 17 kg P ha− 1 and 8 kg K ha− 1. Each hybrid entry was planted to a two-row plot of 4 m length, and the intra-and inter-row spacing were 0.25 m and 0.75 m, respectively. Thirty-four seeds (two per hill) were initially sown and later thinned to 17 vigorous plants per row to achieve 53 333 plants ha− 1. Lime ammonium nitrate (LAN, 33% N) was applied as a top dressing at a rate of 150 kg ha− 1, at four weeks after crop emergence. Weeds were controlled using pre-emergence herbicide, Bateleur Gold 650EC (Flumetsulam (sulfonanilide), s – metalachlor), at 1.3 L ha− 1 and post-emergence herbicide, Basagran (480 g/L bendioxide (thiadiazine)) at 2.5 L ha− 1. This was augmented by occasional manual weeding when needed. Insecticides were applied to control stalk-borer, using Karate (50 g/L lambda-cyhalothrin) at 70 ml ha− 1. Due to the below normal total rainfall, which was experienced at both stations, supplementary irrigation water was applied to augment rainfall amount until crops reached the physiological maturity, especially during the 2015/16 season. Grain yield per plot was estimated and converted to tonnes ha− 1 at 12.5 % grain moisture content in line with the standard practice for maize production, in South Africa.
Field Data Analysis and Classification of Lines
Analysis of variance (ANOVA) was performed on plot means for grain yield data across sites for each season. Lines that did not cross successfully with all testers were not included in the analysis, hence 31 lines were used to perform the line x tester analysis. Specific combining ability effects for grain yield were estimated using the line by tester procedure, which is embedded in the Analyses of Genetic Designs computer software with 'R' (AGD-R, version 3.0) (Rodriguez et al., 2015). Lines and testers were treated as fixed effects. The statistical model used for the combined analysis was as follows:
Yijkl = µ + Li + Tj + (L×T)ij + El + (L×E)il + (T×E)jl + Rk(El) + (L×T×E)ijl + eijkl,
where Yijkl is the measured grain yield data of the testcross of the ith line crossed to jth tester in the lth site and kth replicate; µ is the grand mean; Li is the effect of the ith line; Tj is the effect of the jth tester; El is the effect of the lth site; (L×T)ij is the interaction effect of the cross between the ith line and the jth tester; (L×E)il is the interaction effect of the ith line and the lth site; (T×E)jl is the interaction effect of the jth tester and the lth site; Rk (El) is the effect of the kth replicate nested in the lth site; (L×T×E)ijl is the interaction effect of the ith line, jth tester and the lth site and Eijkl is the random error term.
Classification of lines into heterotic groups was based on the specific combining ability (SCA) value of a line and a tester for grain yield as proposed by Vasal et al. (1992). Lines that showed negative SCA effects for grain yield when crossed to a particular tester were deemed to belong to the same heterotic group with the tester; whereas lines that exhibited positive SCA effects with one tester indicate that those lines belong to the opposite heterotic group. The lines displaying positive SCA with both testers (A and B) were allocated to the AB heterotic group and those displaying negative SCA with both testers could not be classified on the basis of SCA data.
SNP Genotyping and Diversity Analysis
The 42 maize inbred lines were planted in the glasshouse for DNA sampling. Leaf samples bulked from four plants of each inbred were taken at two weeks after planting. Genomic DNA was extracted at the Agricultural Research Council-Grain Crops laboratory, following a modified CTAB procedure (Doyle, 1987). DNA samples were sent to the Agricultural Research Council-Biotechnology platform in South Africa for genotyping using the single nucleotide polymorphism (SNP) markers. Genotyping was carried out using the Illumina MaizeSNP50 Bead chip, which was derived from the B73 reference genome (www.illumina.com). The protocol provided 56110 SNP markers, which were densely covering all the ten chromosomes of the maize genome. The genetic distance (dissimilarity) estimates among inbred lines were calculated based on the Gower's distance (Gower, 1971). Genotypes were subsequently grouped by the Unweighted Pair Group Method using Arithmetic average (UPGMA) algorithm, using the R studio Software version 3.3 (RStudio Team, 2015).
Diversity Analysis based on SNP markers
The UPGMA dendogram of 40 maize inbred lines and four testers is shown in Fig. 1. The SNP markers divided the South African germplasm into 11 clusters (Table 1). The principal clusters were the USA Corn-belt temperate containing the two testers B73 and MO17, and the other mega cluster consisted of South Africa maize inbred lines. The South Africa maize inbred lines were on the same side with the tropical testers, CML444 and CML312, indicating that they were more inclined towards the tropical CIMMYT testers than the USA temperate testers. The South Africa maize inbred lines had shorter genetic distance from the tropical lines than the temperate testers (Table 1).
Summary of the dendogram clusters and mean genetic distance between the clusters and testers
Inbred lines within a cluster
General description of the cluster
Average genetic distance with testers
MO17
CML444
RO421W (M)
A QPM line derivative of M37W, singleton cluster
K64R.22 (K), R2565Y (K), J80W (M), P28 (R), P612MSV (R), P614MSV (R), U71Y (R
Mainly B73 introgressed into South African lines with BC to South Africa lines
K64 (K)
Kansas inbred line, singleton cluster
P590MSV (L), P594MSV (L), P598MSV (L)
Derivatives of Lancaster Sure crop through introgression of MO17 into South Africa lines via a BC to the South Africa lines
B1138T (F), P588MSV(L)
Purely South Africa germplasm, with no known temperate alignment
I-16 (I), I-34 (I), I-39 (I), I-41 (I), I-42 (I), NC258 (L)
South Africa inbred lines, of mainly the I-heterotic group
U127Y (K), CML312 (A), CML444 (B)
Tropical lines from CIMMYT and one South African line (U127Y)
U2540W (K)
K64R/M162W derivative, singleton cluster
BO394Y (F), E30Y (F), RO544W (F), UO705Y (F), V0430Y (F), FO215W (P), SO713W (P)
QPM lines, which were derived from the F2834T and Natal Potchefstroom Pearl (NPP)
FO215W (P), SO713W (P), SO607W (P)V0495Y (P), VO500Y (P), V0501Y (P)
QPM lines, which are derivatives of the Natal Potchefstroom Pearl (NPP)
MO17HtHtN (L), RO452W (M), SO503W (M), VO617Y (M), S0181Y (M), S198Y R), SO1224Y R)
Reid derivatives and QPM inbred lines from predominantly the South African M-group (M37W)
The average genetic distances between lines and different testers are shown in Table 2. The widest (0.95) average genetic distance was between the South Africa lines and the USA Corn-belt testers. The distance ranged from 0.68 and 1.19, with the minimum distance between P598MSV and B73 and the maximum between J80W and MO17. The mean genetic distance with the tropical testers was 0.80 and ranging from 0.52 to 0.80. The lowest genetic distance was estimated between U127Y and both CIMMYT testers, CML312 and CML444, while the largest genetic distance was found between J80W with both tropical testers, and between RO452W and CML444.
Genetic distances between the South Africa maize inbred lines and tropical (CML312 and CML444) and temperate USA testers (B73 and MO17)
Inbred line
Current RSA HG
Abbreviated Pedigree
Genetic distance with testers
B1138T
TEKO YELLOW
BO394Y
F2834T.4O2
E30Y
B390YxM136Y
RO544W
BO160W.3J400W
UO705Y
YOFE1(S4)
V0430Y
(HO466Y.1BO310Y)
Pride of Saline
K64R.22
K64R-22
R2565Y
K64R2(I137TN1.K64R)
U127Y
M162W.1KO326Y
U2540W
M162W1.DO940Y-J34
MO17HtHtN
P588MSV
MRSxVHMO17
MLSxVHMO17
21A-6xVHMO17
J80W
D800W2.HtN
DO940Y-11.O2(W)
DO940Y-13.NHK
SO503W
KO315Y2.NPPES1
VO617Y
(1)"M37W.TE/TEO"
S0181Y
FO215W
NPPES14.O2S14
POWS1(S4)
POWS12.Y
B73xVHKG/C1
S198Y
M28Y1.DO620Y
SO1224Y
M28Y1.KO288Y
U71Y
M28Y2.NP
There were generally large average genetic distances between lines within clusters, ranging from 0.31 to 0.58 (Table 3). The minimum distance was between the temperate inbred lines in cluster 1, whereas the maximum was in clusters 3 and 6. The distance between lines within cluster 11 showed the widest range (0.17 to 0.70). The average genetic distance between clusters ranged from 0.70 to 0.86. The minimum genetic distance was recorded between clusters 6 and 8 and clusters 8 and 9; while the maximum genetic distance was between clusters 1 and 12 (Table 3).
Average genetic distances (GD) between maize germplasm clusters and within clusters
Average GD between lines within clusters
GD Range
within a cluster
The average distances among the current South African heterotic groups and among tester lines are shown in Table 4. The average genetic distance between the South Africa heterotic groups ranged from 0.74 (L and K) to 0.86 (I and M as well as M and R). The average genetic distance between the South Africa heterotic groups and the tester maize inbred lines was the highest (0.97) between group R and temperate testers, while the minimum genetic distance (0.59) was between heterotic group F and the tropical testers. The distance between testers was generally large, ranging from 0.31 for B73 and MO17 to 0.91 for MO17 and CML444 (Table 4).
Average genetic distances between current South African heterotic groups and between testers
The analysis of variance results of yield in 2014/15 and 2015/16 are presented in Table 5. During the 2014/15 season, the mean squares associated with the sites main effects was highly significant (P < 0.001) for grain yield. The results also showed significant differences due to lines main effects (P < 0.05) and testers main effects (P < 0.001). Although the genotype x site interaction effects were not significant (P > 0.05), the site main effects and tester interaction effects were highly significant (P < 0.001) for grain yield data. The mean squares associated with the line x tester interaction effects was not significant (P > 0.05) for grain yield, and site x line and site x line x tester interaction effects were not significant (P > 0.05). There were no significant differences between sites main effects, testers main effects and tester x sites interaction effects, during the 2015/16 season (Table 5). However, the mean squares associated with genotypes, lines main effects and the interaction between sites x lines were highly significant (P < 0.001) for grain yield, during the 2015/16 season. The interactions between lines x testers, sites x genotypes were also significant (P < 0.01) during the 2015/16 season. The mean squares associated with site x line x tester interaction effects was also significant (P < 0.05). The results indicated the presence of sufficient variability among the lines to be classified into heterotic groups.
Analysis of variance of maize hybrids for grain yield at two sites in each of the 2014/15 and 2015/16 summer season, in South Africa
35.81***
Rep(site)
Genotypes
4.90**
5.71***
Line × tester
Site × genotypes
Site × line
Site × tester
Site × line × tester
***, **, * Data significant at P < 0.001, 0.01 and 0.05, respectively; DF - degree of freedom;! Testers excluding MO17.
Heterotic grouping of lines based on SCA effects
Classification of 26 South African maize inbred lines in accordance with their specific combining ability effects with tropical testers is shown in Table 6. Heterotic classification of South Africa maize inbred lines based on their SCA with the tropical CIMMYT maize inbred testers indicated that 10 maize inbred lines were oriented towards CML312 and were fitted in heterotic Group A, 12 inbred lines with negative SCA with CML444 were placed in Group B; while two inbred lines which exhibited positive SCA with both tropical testers were classified as heterotic Group AB. Only two lines, which displayed negative SCA effects with both tropical testers, were not classified on the basis of SCA data. The results indicated a weak correlation (r < 0.30) between genetic distance with both grain yield mean and specific combining ability data of the testcrosses of South Africa lines with tropical inbred testers (Table 6).
Heterotic orientation of 26 South Africa maize inbred lines towards tropical maize inbred testers based on SCA data
(t ha− 1)
Genetic distance
Testcross mean yield
CML312 (A)
CML444 (B)
-1.47*
M162W
SO181Y
Correlation with GD
*Significant at P < 0.05; SCA, Specific combining ability; GD, Genetic distance; SCASE (P < 0.05) = 0.98
Heterotic orientation of 18 South Africa maize inbred lines on the basis of their SCA effects with temperate USA corn-belt testers is shown in Table 7. Five inbred lines which showed negative SCA with B73 were fitted into heterotic group A, while six inbred lines, which showed negative SCA with MO17, were put in Group B. Three inbred lines, which exhibited positive SCA with both temperate testers, were allocated to the Group AB. Four maize inbred lines, which showed negative SCA with both temperate testers, could not be fitted into any of the heterotic groups on the basis of SCA data.
Heterotic orientation, SCA effects, genetic distance and mean yield of 18 South Africa maize inbred lines with temperate inbred testers across environments
South African Heterotic Group
SCA effects
towards testers
distances with
B73(A)
MO17(B)
Grand mean (t ha− 1)
Standard error (SCA)
*Significant at P < 0.05; SCA, specific combining ability; GD, genetic distance
Classification of maize inbred lines by SNP markers
The SNP markers genotyping was highly effective in confirming classification of the germplasm collection in South Africa. As expected, the SNP markers divided the germplasm lines into two principal clusters of USA Corn Belt temperate testers and the South African maize lines clustering with the tropical testers from CIMMYT. This indicated that South Africa public lines were more inclined towards the tropical CIMMYT than the USA temperate testers. However, there were 11 sub-clusters within the South African germplasm collections indicating tremendous diversity. Only the lines from the current "I" heterotic group were placed in the closest cluster with both CIMMYT's tropical testers, CML444 and CML312, indicating that these lines have never been introgressed with temperate germplasm, and were more pro-tropical than the rest of the 40 lines in the sample. The findings from the study were consistent with pedigree data. Based on the pedigree data, lines with a history of temperate germplasm introgression, such as P614MSV and P612MSV with B73 introgression and P590MSV and P594MSV with MO17 introgression were placed in clusters 3 and 5, which is near the temperate cluster (Cluster 1) on the dendogram, indicating their orientation towards the temperate material. Clusters 10 and 11, which are furthest away from the temperate cluster on the dendogram are formed by a group of quality protein maize lines, which is a pro-tropical germplasm collection. These lines resulted from the opaque-2 breeding program, which led to the release of yellow and white opaque-2 modified inbred lines (Gevers, 1972). These lines were bred from tropical germplasm. However, within the QPM group, the inbred line MO17HtHtN from the current L heterotic group was non-QPM by origin. Clustering of this line within the QPM collection is an implication of more QPM alleles than normal maize in its genetic background, which could have been introduced along with Northern corn leaf blight (Ht) resistance.
Although genotypic classification by SNP markers was closely linked with the origin of inbred lines and pedigree records, there were deviations that were observed. The lines NC258 and U127Y which are currently classified as L and K heterotic groups, respectively, in South Africa, were actually placed in the same sub-cluster with the I and CIMMYT's tropical testers, respectively. This indicates that the classification of South African lines in the whole collection might require confirmation with SNP genotyping. In the same vein, lines RO421W (M), K64 (K) and U2540W (K) which were expected to cluster with the current M and K heterotic groups of South Africa, formed singleton clusters, and were not associated with any of the South African lines. They have also displayed a lack of association with the USA temperate and tropical CIMMYT lines, qualifying them as representing distinct germplasm groups within the South African inbred lines collection.
Classification based on Specific combining ability
Based on specific combining ability effects for yield data, inbred lines were grouped into three heterotic groups by both temperate and tropical testers, which was consistent with the system that was described by previous researchers. The SCA value reveals the genetic relationship between two parents or between a line and a tester (Vasal et al., 1992). High SCA value (positive) between two parents indicates a distant relationship and low (negative SCA) value is an indication of close relationship (Fan et al., 2003). The tropical testers were capable of discriminating the lines, such that six lines were allocated into tropical group A, indicating that they were oriented towards CML312, whereas nine lines placed into tropical group B indicating their orientation towards CML444. Only three lines which showed negative SCA with both tropical testers could not be classified on the basis of SCA data. The classification of the South Africa lines using their interaction (SCA effects) with the temperate testers allocated five lines into temperate group A, indicating that they were B73-orientated; while six lines were placed in temperate group B indicating that they were orientated towards MO17. Three lines, which exhibited positive SCA with both B73 and MO17, were classified as temperate AB group on the basis of SCA data; while four lines, which displayed negative SCA effects with both temperate testers, could not be classified.
Relationship between SNP and SCA-based classification
Heterotic orientation of inbred lines under non-stress environments corresponded with the SNP marker classification. It was noted that lines that did not belong to any heterotic group when tropical testers were used could be classified clearly using temperate testers and vice versa. For example, in SNP cluster analysis, the I-group representatives were more aligned to both tropical testers. However, heterotic orientation by temperate testers did not classify them into any heterotic group, as revealed by negative SCA effects with both B73 and MO17. The grouping of the I-group lines with only tropical testers was an indication of a distant relationship between the I heterotic group and the temperate lines. This was further supported by the maximum average genetic distance between the I-group and both temperate testers, B73 (0.97) and MO17 (1.07). Therefore, delineation of inbred lines by either temperate or tropical lines is influenced by the predominance of either temperate or tropical genome in their genetic background, which was clearly confirmed by the SNPs marker data. Findings from this study are consistent with previous reports. Adetimirin et al. (2008) also observed that markers clearly discriminated temperate from tropical germplasm. They further observed that some lines that were known to be temperate x tropical were aligned with the tropical lines, indicating that they were more closely related to the tropical than temperate material. In this study, some lines were consistent in their heterotic orientation by both USA temperate and CIMMYT tropical lines. However, the strongest relationship towards either temperate or tropical lines was observed from the magnitude of SCA effects and their placement in the dendogram.
There are inbred lines including RO421W, K64 and U254OW that formed distinct singleton clusters. Use of the SCA heterotic orientation approach did not clearly classify these lines. For example, RO421W did not belong to any heterotic group under tropical classification, while classification based on temperate testers allocated this line into heterotic the temperate group AB. The inbred line K64 was assigned into temperate AB group by temperate testers and into heterotic tropical group A by tropical testers.
Grouping lines by SCA effects therefore revealed that when inbred lines are classified into heterotic groups using two sets of testers, failure of one set of testers to classify lines could be an indication of distant relationship between a line and a particular set of testers. Alternatively, classification of some lines might not be clear with both sets, such lines could represent distinct germplasm groups within the germplasm collection. Therefore, when the molecular data is not available for validation, there should be no preference for any set of testers over another. However, inclusion of two sets of testers could be a more accurate approach, especially in distinguishing germplasm like the South African collection with a history of both tropical and temperate introgression.
The inbred lines used in the study were pooled from seven known South African heterotic groups to minimise the number of heterotic groups for improved breeding efficiency. The 11 clusters obtained could be simplified into a broader group of normal endosperm maize and quality protein maize lines. Normal maize endosperm lines may be grouped into three groups, with one group forming temperate germplasm (clusters 1 and 3) with pro-MO17 and B73. The second group is a group of South African lines in clusters five and six, with no temperate or tropical alignment, while the I-group lines and those lines with tropical alignment formed the third group. The QPM lines on the far right of the dendogram could be split into two groups (clusters 10 and 11). Intra-group combinations among the normal maize groups and between the QPM groups are expected to give high heterosis in crosses. Cross combinations between normal maize and some lines in the QPM group, particularly the white versions are also recommended to maximise heterosis. The heterotic potential of these groups was shown by a cross between FO215W from the QPM cluster and the tropical tester, CML444 (data not presented). Lines that represented distinct germplasm should also be considered for utilisation in crosses; for example in the current study, high heterosis was revealed by crosses RO421W x B73 and RO421W x MO17. Previous investigations revealed high heterosis in crosses including F and I, M and K, K and P, M and P and crosses between M and F and R and L group combinations (Gevers and Whythe, 1987). Based on the new clusters formed, these combinations also included temperate x tropical lines. The identified groups will likely result in superior tropical × temperate combinations with new favourable alleles, wider genetic base, and consequently improvement in agronomic performance and adaptation of local varieties.
From the current seven heterotic groups of South Africa studied, some groups clearly clustered into the identified clusters. The study therefore indicated that the established patterns would be beneficial in inferring the classification of lines that were not included in the study, but represented in the seven heterotic groups. The F, P and M group lines and the rest of the Opaque-2 modified lines from other South African heterotic groups belong to the QPM group. Lines from the L- group form a distinct group of normal maize endosperm lines; the I-group lines form a distinct group closest to the CIMMYT lines, while the temperate group include the R lines and K-group lines with a normal maize endosperm type. However, classification of some South African heterotic groups, particularly the K-group lines may not be straightforward as lines from this group were distributed in different clusters. Such deviations may be an indication of the presence of diversity within the K-group; this also suggests that inbred lines extracted from the same population do not always cluster together. This was also observed in many previous investigations (Vasal et al., 1992; Yu et al., 2001; Fan et al., 2003; Barata and Carena, 2006) that reported that maize inbred lines which were derived from the same population classified differently.
Genetic distances
Genetic distances summarise the extent of genetic differences between populations or species (Dogan and Dogan, 2016). Genetic distances were estimated to determine the relatedness among inbred lines studied. The average genetic distances computed between clusters, South African heterotic groups, inbred lines within clusters and among tester inbred lines indicated the presence of sufficient variability between the identified clusters and therefore the possibility of obtaining superior hybrid combinations from inter-cluster crosses. The average genetic distances between lines within clusters clearly indicated that lines that formed the same cluster were genetically related by distance, as the average genetic distance ranged from 0.31 to 0.58 between clusters. However, for some clusters, the genetic distance range of inbred lines showed a considerable diversity within a cluster. For example, the genetic distance in cluster 11 ranged from 0.17 to 0.70. This therefore showed that the collection of QPM lines that formed cluster 11 were derived from distinct genetic backgrounds. The maximum average genetic distance between clusters 1 and 11, further demonstrated the reliability of SNP markers in distinguishing between inbred lines. Genetic distances between testers clearly revealed that both temperate USA Corn-belt testers, MO17 and B73, are closely related which reflected their temperate adaptation domain. The closest relationship was further confirmed by the grouping together of these inbred testers on the dendogram. Similarly, the close genetic relationship between tropical CIMMYT testers, CML312 and CML444, was confirmed by the minimum genetic distance between them, and their placement within the same cluster, indicating their tropical adaptation domain.
The genetic differences among the current South African heterotic groups were generally large, indicating the presence of diversity within the South African germplasm collection. The largest genetic distance was between group R and M, and I and M, indicating genetic dissimilarity between these South African heterotic groups. The R group lines were grouped in cluster 3, with temperate alignment, whereas the M group lines were mainly grouped along with the QPM lines in cluster 11; the M group also showed the highest genetic dissimilarity with the I group. Inbred lines from heterotic Group I formed a distinct group in cluster 7, that was closest to the tropical testers, and were thus not closely associated with the M-group lines. The highest average genetic distance between these heterotic crops thus indicated that they are the most distinct heterotic groups within the seven South African heterotic groups. The minimum distance between the South African heterotic groups K and L was an indication of genetic similarity. Although these groups did not cluster together, their placement by the SNP markers in closest clusters, for example allocation of the K lines in clusters 3 and 4 and the L-group lines in cluster 5, could be an explanation of the minimum genetic distance estimates between them. Overall, the average genetic distance was generally large between South Africa inbred lines and temperate testers than with the tropical testers, indicating that although some lines may be aligned towards temperate than tropical testers, the lines are of South Africa origin and were closer to the tropical testers. This is expected because South Africa falls within the subtropical to a warm temperate environment, which places its germplasm between tropical and temperate although with a bias placement towards tropical orientation.
Correlation of genetic distance with grain yield and specific combining ability
There were low correlations detected between genetic distance with grain yield mean and specific combining ability data, indicating that hybrid performance could not be efficiently predicted using molecular marker-based genetic distances. The low predictive value of genetic distance was also confirmed by the degree of heterosis observed in crosses (data not shown). For example, a pair of lines that showed the widest range of genetic distances did not necessarily show maximum heterosis in their testcrosses. These observations are in agreement with previous studies where poor (Makumbi, 2005; Parentoni et al., 2001; Xu et al., 2004) to no (Rajendran et al., 2014) correlation was demonstrated between genetic distance with grain yield and SCA. The low correlation observed in several studies has been associated with the markers used to compute genetic distances. The markers used are generally many, evenly distributed on the genome, and may not be closely linked to grain yield and associated quantitative characters (Melchinger, 1999). This therefore reduces the association between genetic distances and heterosis. Furthermore, the genetic differences between parents are due to many traits and loci which may not all be correlated with yield. Zhang et al. (2010) thus suggested the use of only yield-related markers to analyse genetic differences, and subsequently to reliably predict hybrid performance.
In sharp contrast to findings in the current study, Schrag et al. (2010) and Gichuru et al. (2017) reported high predictive value of molecular maker genetic distances in heterosis; the observed degree of correlation was associated with the genetic differences and complementary traits of lines used. The ability of genetic distance to predict heterosis in crosses therefore varies with germplasm used (Betran et al., 2003) and probably the set of molecular markers used. In the current study, the observed levels of correlations therefore underlines the need for conducting field trials to evaluate hybrid performance, irrespective of known genetic distances between inbred lines. However, despite the inability of genetic distances to reliably predict hybrid performance, their usefulness as a guide during selection of inbred lines for hybrid make-ups is underscored.
The study confirmed existence of high level of genetic diversity among the South Africa line collection. These lines have shown alignment towards both tropical and temperate testers. However, they were more inclined towards the tropical than temperate testers. The SNP markers genotyping was highly effective in confirming classification of the germplasm collection in South Africa. On the basis of SNP genotyping data the germplasm could be simplified into two broader groups, which are consistent with biochemical composition of the grain endosperm type. The first group comprised quality protein maize (QPM) lines and the second group is normal endosperm type of maize inbred lines. However, there are further sub-divisions within these broad germplasm groups indicating that the program in South Africa has maintained the diversity in both quality protein and normal endosperm maize germplasm. The SNP data was complemented by SCA data which grouped the germplasm into three heterotic groups (A, B and AB), indicating that South Africa germplasm lines have orientation towards both tropical and temperate testers, and that some lines showed heterosis with both testers within the two broad adaptation groups. These findings have profound implications for optimising breeding programmes that target the warm temperate production environments in South Africa.
The authors have no conflict of interest.
The maize germplasm used in the study were provided by the Agricultural Research Council (ARC) of South Africa and the International Maize Improvement Center (CIMMYT). We are indeed grateful for support which was provided by the Agricultural Research Council through postgraduate funding of the senior author and use of its SNP genotyping platform, in Pretoria.
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Chloé to ...
Chloé to sponsor 27th Andam Fashion Awards
Don-Alvin Adegeest
Chloé Chairman Geoffroy de la Bourdonnaye is preparing to take on the role of sponsor for the 27th ANDAM Fashion Awards.
The fashion house will provide two years' worth of design and business support for the winner of the Grand Prix 2016, set to be named in July.
The current CEO of Chloé, Geoffroy de la Bourdonnaye, will follow in the footsteps of Chanel's Chairman of Fashion Bruno Pavlovsky, as the sponsor of this year's ANDAM Fashion Awards. The winner of the Grand Prix will be awarded with two years of sponsorship from the fashion house, along with 250,000 euros in the hope of developing a label of their own. Following the news of the post, the Chloé chairman announced with pride that "the house has always been an incubator for young designers".
Launched in 1989 by Nathalie Dufour as an initiative by the Ministry of Culture, ANDAM (the French National Association for the Development of the Fashion Arts) aims to make young designers known to established fashion houses and to help them make a name for themselves, thanks to winners' bursaries totalling 390,000 euros.
Moncler is also one of the labels that is offering sponsorship for the first time this year at the 27th edition of the awards ceremony. Submissions will be open from April 15 onwards, and the jury will decided the winners in July this year, at the end of Autumn/Winter 2016-2017 Haute Couture Fashion Week.

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text: Q: Uniformizer of an elliptic curve at infinity I have read in a solution to a problem that I was studying that $t = \frac{x}{y}$ is a uniformizer at the point $(0,1,0)$ of the curve given by $y^2z=x^3+axz^2+bz^3$, and that one can expand $x=t^{-2}+...$ and $y=t^{-3}+...$. I am not sure how one gets this and was hoping someone could clarify?

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text:
Suzanne Adams
Nov 30, 2020 Updated Jan 9, 2021
The Pinal County Sheriff's Office reported the following people booked into the Pinal County Adult Detention Center:
Joseph Figueroa
Levi Bonney
Elia Antone
Sabra Castle
Steven Petershagen
Shane Sexton
Paula Cudd
Tasha Herman
Sarah Arbizu
Jorge Juarez
Victoria Valencia
Jacob Ericson
David McIntosh
Ashley Jeffrey
Edgar Acosta Cazares
Stephanie Danforth
Letricia Sopha
Mario Sanchez
Jennifer Felix
Chance Kinkade
Marc Castelamare
PCSO Booking Mugs 12/01/20
Marc Castelamare, 25, was arrested on suspicion of theft of means of transportation, unlawful control of means of transportation and theft.
Chance Kinkade, 23, was arrested on a probation violation.
Jennifer Felix, 44, was arrested on a probation violation.
Mario Sanchez, 36, was arrested on suspicion of exceeding 85 mph.
Letricia Sopha, 35, was arrested on suspicion of interfering with judicial proceedings.
Stephanie Danforth, 30, was arrested on a warrant.
Jonathan Johnson, 39, was arrested on suspicion of child/vulnerable adult abuse-intent, assault-intent and domestic violence disruptive behavior-fighting.
Edgar Acosta Cazares, 23, was arrested on a warrant.
Ashley Jeffrey, 39, was arrested on a warrant and on suspicion of possession of narcotic drugs, two counts of possession of drug paraphernalia and failure to stop for law enforcement.
Allen Moore, 48, was arrested on a warrant and on suspicion of possession of a weapon by a prohibited person and a probation violation.
David McIntosh, 38, was arrested on suspicion of disorderly conduct-fighting, preventing the use of a telephone in an emergency, assault-intent and a probation violation.
Jacob Ericson, 36, was arrested on suspicion of aggravated assault-adult on minor, criminal damage, disorderly conduct with a weapon and two counts of disorderly conduct-fighting.
Victoria Valencia, 24, was arrested on suspicion of making a false report to a law enforcement officer, forgery-pass forged instrument and failure to appear.
Jorge Juarez, 34, was arrested on a warrant.
Sarah Arbizu, 34, was arrested on suspicion of unlawful imprisonment, aggravated assault-adult on minor and domestic violence disruptive behavior-fighting.
Tasha Herman, 50, was arrested on suspicion of a dangerous drug violation and shoplifting.
Jesse Garcia, 40, was arrested on suspicion of possession of drug paraphernalia, shoplifting, criminal trespass and a warrant.
Paula Cudd, 59, was arrested on suspicion of failure to appear.
Shelby Hill, 29, was arrested on suspicion of criminal damage, aggravated assault and assault-intent.
Shane Sexton, 48, was arrested on suspicion of criminal damage and disorderly conduct-fighting.
Dennis Sexton, 27, was arrested on suspicion of resisting arrest and disorderly conduct-fighting.
Mark Johnson, 64, was arrested on a warrant.
Steven Petershagen, 29, was arrested on suspicion of failure to comply with a court order.
Sabra Castle, 28, was arrested on suspicion of failure to comply with a court order.
Elia Antone, 31, was arrested on a warrant and suspicion of criminal damage.
Levi Bonney, 23, was arrested on suspicion of possession of narcotic drugs, possession of marijuana and possession of drug paraphernalia.
Joseph Figueroa, 20, was arrested on suspicion of failure to appear.
Robert Payne, 39, was arrested on suspicion of disorderly conduct-fighting, threatening, criminal damage, liquor laws-passenger in possession, theft and a probation violation.
Burglaries/thefts/vandalism
The theft of a vehicle was reported near East El Camino Viejo and U.S. 60 in Gold Canyon.
Fraud was reported in the 1700 block of West Hunt Highway in San Tan Valley.
A theft was reported in the 800 block of West Banyan Avenue in San Tan Valley.
A theft was reported in the 12100 block of West Aries Drive near Tat Momoli.
A theft from a motor vehicle was reported in the 10300 block of West Sunbird Drive in Arizona City.
A theft was reported in the 15700 block of South Coral Road in Arizona City.
A theft from a motor vehicle was reported in the 8900 block of West Raven Drive in Arizona City.
A theft was reported in the 10400 block of East Aster Lane in San Tan Valley.
A theft was reported in the 4300 block of East Rose Quartz Lane in San Tan Valley.
A theft was reported in the 32300 block of North Gantzel Road in San Tan Valley.
Shoplifting was reported in the 100 block of West Combs Road in San Tan Valley.
A theft was reported in the 15000 block of South Capistrano Road in Arizona City.
Fraud was reported in the 600 block of South Tornado Trail in Queen Valley.
A theft was reported in the 2200 block of West Josiah Trail in San Tan Valley.
Shoplifting was reported in the 1700 block of West Hunt Highway in San Tan Valley.
A theft was reported in the 700 block of West Vineyard Plains Drive in San Tan Valley.
The theft of a motor vehicle was reported in the 49100 block of West Wildwood Road near Stanfield.
Incidents/accidents
An assault was reported in the 4000 block of East Copper Road in San Tan Valley.
A sex offense was reported near Red Rock.
An assault was reported in the 4200 block of East Rock Drive in San Tan Valley.
An assault was reported in the 1000 block of South Belmont Avenue in Superior.
Suzanne Adams-Ockrassa is a reporter covering the city of Casa Grande and the surrounding area, as well as Central Arizona College. She can be reached at sadams@pinalcentral.com.
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As a local just for kids dentist, we can treat any emergency oral health issues that your child may have. We practice preventative care and do our best to keep your kids' teeth healthy so that there won't be an emergency. You can help by brushing their teeth at home twice a day and using a fluoride toothpaste. Feeding them a healthy diet will also help to strengthen and protect their teeth.
If, however, a dental emergency strikes it is important to know where to go for help. We don't want any of our young patients to suffer with pain so if they start to complain about a toothache, give us a call right away so that we can identify what is making their tooth hurt and how to treat it. We offer sedation so we can help your child to stay comfortable during the exam and any treatments that follow.
Food that's stuck. When your child eats something sticky or a food like corn, there is a chance that it will become stuck in between their teeth. Most of the time you can get it out by brushing and flossing but with young children this can be difficult at times. If they eat something then start to complain and you can't get it out – call us. We have the tools necessary for dislodging anything that is stuck between their teeth.
Chipped teeth. Kids are known for chipping their teeth. Whether tripping and falling, playing baseball or running around on the playground, accidents happen. Kids that play hard are even more likely to have an accident and chip or crack their teeth. When this happens, don't worry. Just call us for an appointment, and we will restore the tooth so that they can be pain-free and eat like normal. Our restorations will also look natural so no one will know that the accident ever happened.
Toothache. If your child develops a cavity, it may cause pain while they eat or bite down. If dinnertime becomes a fight because it hurts to eat, we need to see them right away. We can treat cavities quickly and easily, use a natural colored filling, and provide sedation so that they are comfortable during the procedure.
Bleeding. If your child's mouth starts to bleed and won't stop, give us a call. We can examine them and find out why the bleeding started then treat the area. Don't give them aspirin because this will make their blood thin and prevent it from clotting.
Regardless of what oral health issues your child has, we can help. Whether their tooth is damaged, or they are in pain, give us a call so that we can find out what the issue is and make an immediate treatment recommendation. It is important to get them help as quickly as possible and as a just for kids dentist; we will try to schedule an appointment for right away.
This entry was posted in Just for Kids Dentist and tagged Just for Kids Dentist on October 9, 2014 by admin.


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Straits of Mackinac during a Coast Guard Air Station Traverse City MH-60 Jayhawk helicopter overflight on April 4, 2018. (U.S. Coast Guard photo).
MACKINAW CITY, Mich. — The Unified Command has isolated the impacted utility lines and is monitoring the removal progress of the remaining mineral oil from those lines, Thursday.
The Oil Spill Response Organization, contracted by the American Transmission Company, removed approximately 10 percent of the mineral oil from one of the utility lines yesterday. The Unified Command will continue to consult with oil recovery experts and engineers today to ensure the oil extraction process is effective.
Approximately 400 gallons of oil remains in each utility line and is not known to be leaking from the source. The estimate that 600 gallons of mineral oil leaked from the utility lines before securing the source remains unchanged.
The Coast Guard deployed an MH-60 Jayhawk helicopter crew from Coast Guard Air Station Traverse City on Monday and Wednesday afternoon to search for pollution over the Straits of Mackinac. The flight crews used infra-red technology to detect temperature differences between the oil and water and did not locate any oil sheen or signs of pollution. Coast Guard overflights will continue to monitor the spill.
In consultation with engineers from the Pipeline and Hazardous Materials Safety Administration and the Michigan Department of Environmental Quality, a 10-person work crew and vacuum truck are on site for the OSRO working to draw the oil out of the two decommissioned utility lines; no pressure is being applied to the lines. A suction, or negative pressure, is present on the entire span of the lines across the Straits.
The calculated trajectory of the spilled mineral oil is to the south and southwest of the source. Given the dilution of the product and the mobility of fish, there continues to be a low risk to fisheries and wildlife. A concern remains that waterfowl or shore birds may come in contact with the product floating on the surface. The Unified Command is exploring methods to deter birds from the area.
Due to the inaccessibility of the shorelines from ice, the threat to the public is low since they are unable to come in contact with the oil. The dilution of the oil and distance from the bridge and water intakes provide additional protection from the product.


text:
Sound Pedagogical Approach
Components & Resources
FAQ: Classes
- Sound Pedagogical Approach
- Components & Resources
- FAQ: Classes
The North American Model of Conservation has transformed wildlife and habitat management around the world. It is the most successful model of management in history, at a time when society poses many risks to wildlife and habitat globally. The Sportsmen's Alliance Foundation has launched an exciting education initiative, called Conservation Adventures, aimed at addressing critical gaps in education as it pertains to wildlife and habitat conservation. Through this effort, we will educate students on the North American Model of Conservation, its impact and importance for the future of ecosystems while fulfilling educational requirements in several core and elective classes.
Thank you for your interest in Conservation Adventures, and for exploring new ways for your students to learn to love the natural world around them. If you have any questions or would like to sign up, please see the frequently asked questions section or feel free to contact us directly.
Course Description: Students will develop skills, build an understanding of science and learn scientific techniques taught through the lens of conservation with an emphasis on hands-on, real-world activities. The curriculum focuses on wildlife conservation and the outdoor recreational activities that financially support the North American Model of Wildlife Conservation, such as hunting, fishing, trapping, conservation work, shooting sports and boating. Conservation Science gives students a foundational basis for how these activities directly benefit habitat acquisition, enhancement and protection, as well as wildlife management, including game, non-game and endangered species. Students are not required to participate in these activities, but rather the lessons relate to these recreational activities. Some examples include:
Conservation Work: Investigating the effects of trash on wildlife and habitat while conducting a cleanup project.
Fishing: Applying scientific methods and writing a formal lab report while testing the breaking strength of fishing knots.
Hunting: Learn anatomy standards during the processing of a game animal, such as a pheasant, rabbit or deer.
Shooting Sports: Applying physics standards related to force, acceleration, aerodynamics, projectile motion, etc. to the flight path of an arrow.
Boating: Learning about hydrology while applying physics standards, such as buoyant force, average density, volume, etc., to kayaking.
Designed to Engage Students: Project-based learning, flipped classrooms, inquiry, depth of knowledge, critical-thinking skills and differentiated instruction are buzzword in education today. Conservation Adventures courses incorporate all of these concepts organically while using concrete, real-life examples to teach students the importance of conservation.
Versatile: Most states require students to take three (or more) credits of science to graduate. With approval from your school district, the Conservation Science class could fulfill the third credit required. If a student takes more than the required science credits, this course could fulfill a required elective credit. Additionally, many schools use the curriculum for their agricultural science programs.
Course Resources Provided:
Student Workbook: A paperback, consumable workbook containing the different units of study. The workbook is designed for the students to read the daily topic and complete the introductory assignment prior to coming to class. Class time can then be spent applying the content, answering students' questions and exploring the topic in more detail. (Each student will also receive a digital version of the workbook)
Teacher Edition Workbook: This includes answer keys, grading rubrics, suggested course sequence and unit duration, national and state science standards covered in each unit or activity, assessments for each unit, etc.
Online Materials & Resources: The teacher will have an online login that allows access to:
Digital versions of the student and teacher handbooks
Links to online resources for each unit
Additional teacher materials, including: suggested labs/experiments, activities, projects, assessments, etc.
Ongoing Support: Conservation Adventures staff will be available to help organize, plan and implement course activities. This includes, but is not limited to, helping to schedule guest speakers, provide or help source the necessary equipment and supplies for various course activities, etc.
Teacher Trainings: We will also offer training sessions for instructors.
Relevance to State Curriculum: Our course offerings will provide students with a curriculum that aligns with state requirements for graduation. For example, the Conservation Science class could fulfill the third science credit required for graduation in Ohio or Pennsylvania. If a student takes more than the required science credits, this course could also fulfill one of the five required elective credits.


Restaurant "Palkin" is one of the oldest dining establishments in St. Petersburg, keeps the original name and location. Authentic russian food with modern presentation in a stunning place. I had one of the most amazing experiences in Russia there, eating a fresh salad with parmigiano, salmon dumplings and a delicious fish as a main dish.
Wonderful food, wine and service. Staff is incredibly friendly. I want to highlight the decoration. Is like a doll house with good style. Have a different and great experience at Saint Petersburg at Teplo. Be sure to book in advance.
The Venice of the North, Saint Petersburg. You can find few excellent restaurants in big cities, and this is one of them. I've been there twice, one for business lunch and other for couple dinner. Service is just perfect, and food is greatly presented. Pay attention at every detail, as you're in front of gastronomic artists.
Local food, cheap and fast service. If you don't have a lot of time or money, this is a great option while you visit Saint Petersburg. In my opinion this is a great restaurant, as one expensive and stylish restaurant could also be great. It depends. Sandwiches, bakery, sweets, delicious bites at affordable prices.


The latest outing from Charalambides is a really peaceful side of bliss radiating from a new split 7″ with Pocahunted (via Not Not Fun's still available Bored Fortress series, now in year 3!!). With a discography stretching back 15 years, Tom & Christina Carter seem able to effortlessly mainline each others intentions into otherworldly tone poems that often fall into black hole damage and delicate tone float in equal measure. 'Memory' is completely the latter, a shivering haze of colliding vocal & guitar sustain that sorta floats in, hovers around then quietly disappears. So Lovely. If only everything from Texas was this sweet.


There's been an attack at S.H.I.E.L.D. Science and Technology Pavilion and Iron Man has called upon Ant-Man and The Wasp to help defeat Zola and his Swarmbots, but the heroes need your help. Ant-Man and The Wasp: Nano Battle! lands at Hong Kong Disneyland on March 31, and our friends over at Disney Parks Blog are giving us a super-powered sneak peek at the new attraction. Check it out below!