NEW DELHI, INDIA
Indian Agricultural Research Institute

Analysis of productivity and kernel composition in Indian maize local cultivars and land races

— Meena, CR; Gadag, RN; Singh, BB; Singh, RD

Though maize is one of the prime cereals world over, in India its area and production lags far behind the other two major cereals, viz., rice and wheat. In view of its high productive potentiality and many other advantages, the maize crop has the possibility of expansion to larger acreage, especially if its use is diversified. Development of maize cultivars with high productivity coupled with enhanced sugar and starch content in the kernels may cater to their enhanced use in human consumption and industrial usage. To facilitate this, specific endosperm mutations affecting carbohydrate metabolism that alter total sugar and starch content in maize kernels might be used. Most of the mutations influencing kernel sugar content have been well characterized and used in the development of specialty corns. However, such work is mainly carried out in maize adapted to temperate conditions and hence might not be suitable for direct introduction under tropical/sub-tropical conditions.

Many strategies to diversify genetic base of corn for specific uses are suggested, including new sources and utilization of field corns (Liu, et al., MNL, 70: 12–13, 1996; Cartea, et al., Crop Sci., 36: 1506–1512, 1996). It might also be desirable to explore the utility of local populations and land races. It has been a common observation that many local types are preferred for this specific mode of direct consumption on account of their higher sweetness and favored taste. This strategy should be advantageous mainly from the point of view of better adaptability for specific geographic conditions. In order to assess the utility of local populations, it is essential to make a comparative analysis in respect to specific traits of interest, in addition to their productive potentiality.

The present investigation involving fifteen maize populations and land races cultivated in small pockets of different parts of the country is an earnest effort in this direction. These cultivars were planted in randomized complete block design, in four-row plots of 5 m length with a spacing of 75 × 25 cm, at the research farm of Genetics Division, IARI. A representative sample was taken from each genotype to determine grain yield, sugar components and starch content in dry kernels.

There was significant variation among the genotypes used in the present study for all the traits, viz., grain yield per plant and per plot, different components of sugar (reducing sugar, non-reducing sugar, total sugar), and starch content (Table 1). This necessitated further analysis on the basis of their actual performance in order to identify specific genotypes for different traits. A perusal of mean values indicated that genotypes differed mainly in respect of productivity, non-reducing sugar component and total starch content. Potential genotypes were identified on the basis of different parameters recorded and analyzed.

Comparison of the mean values for yield/plant indicated that SAW/GML/227 with 55 g/plant was the best, followed by four other cultivars, viz., Arabhavi local, SAW/GML/257, Murali maize and Sikkim sel-1, with a range of 44 to 40 g/plant (Table 2). The same five genotypes were also found to have high starch content in the kernels, and the values ranged from 76.10% in SAW/GML/257 to 73.67% in SAW/GML/227. The corresponding value in the sweet corn composite Madhuri was 69.23%.

For percentage of total sugar content, Jaunpur local (8.31), Jaubua local (7.78) and Bhowali local (7.44) were the best, compared to Madhuri, the sweet corn composite. Non-reducing sugar was the main contributing component of the total sugar, though in Bhowali local reducing sugar was also found to be relatively higher. This corroborates the general observation of higher sweetness of some of these locals (compared to the usual field corns) and their popularity and preference for direct human consumption at green ear stage. The corresponding percentage of total sugar content in the sweet corn composite Madhuri, which was used as a reference check, was found to be 10.14, which can be attributed to the presence of with su endosperm mutant gene.

Thus, this preliminary evaluation of the fifteen Indian maize populations/land races was effective in selecting a total of eight genotypes relatively superior for specific traits. While five genotypes were identified for higher productivity and starch content, three were found to be desirable for high sugar content, and these can be targeted for their specific subsequent uses. To the best of our knowledge, this is the first initiative for assessing the biochemical composition of kernels in these genotypes. While the wide range of starch content among the cultivars is interesting, further information regarding specific starch components should be more helpful in formulating an effective strategy for their further utilization. Similarly, the three local maize cultivars with high sugar content might serve as useful complementary sources, in addition to those carrying specific endosperm mutations. Further studies are essential to ascertain the genetic and biochemical basis of their enhanced sweetness. In general, high adaptability of such lines is an additional attractive feature for their utilization in the usual maize-breeding program.

 

Table 1. ANOVA for yield and kernel biochemical traits in maize population/land races

Source of variation d.f. Mean Sum of Square
  Y/P Y/PL NRS RS

TS TSt
Replication 2 4.20 6.46 0.01 0.02 0.10 1.71
Treatment 15 205.79** 25078.59** 9.26** 0.50** 12.81** 86.87**
Error 30 4.47 11.52 0.05 0.01 0.03 1.72

Y/P = yield per plant (g); Y/PL = Grain yield per plot (kg); NRS = Non-reducing sugar (%); RS = Reducing sugar; TS = Total sugars (%); TSt = Total starch

** Significant at (P =0.01)

 

Table 2. Mean performance for yield and kernel biochemical traits in maize population/land races

S. No. Populations/
Land races
Y/P Y/PL NRS RS TS TSt
1 Jhaubua local 28.92 1.24 6.43 1.35 7.78 63.79
2 Dausa local 33.34 1.30 5.14 1.19 6.33 70.30
3 Murali maize 40.54 0.80 2.17 1.37 3.54 76.00
4 Sikkim sel-1 39.39 1.60 2.49 1.28 3.77 74.67
5 Jaunpur local 26.69 1.71 6.77 1.54 8.31 61.67
6 Arabhavi local 43.48 1.27 2.42 1.31 3.73 75.47
7 VKG 16/86 36.53 1.35 4.82 1.35 6.17 68.88
8 VKG 16/12 34.81 1.25 4.55 1.45 6.00 67.87
9 SAW/GML/257 42.04 1.32 2.33 1.12 3.45 76.10
10 SAW/GML/227 54.68 1.28 2.86 1.16 4.02 73.67
11 SAW/GML/315 34.22 1.54 2.83 1.31 4.14 73.07
12 SH-11 29.01 1.21 3.94 1.42 4.36 69.67
13 IC-204048 34.71 1.27 3.32 1.42 4.74 70.03
14 IC-253817 22.48 0.72 3.57 1.29 4.86 68.17
15 Bhowali local 24.53 0.83 6.25 2.19 7.44 62.70
  Madhuri 27.27 1.20 7.44 2.70 10.14 69.23
 
  SEm 1.73 0.05 0.19 0.18 0.09 1.07
  CD (P = 0.05) 3.39 0.09 0.37 0.35 0.17 2.09
  CD (P = 0.01) 4.44 0.12 0.48 0.46 0.23 2.24

Note: The description of traits is the same as in Table 1.



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