Indian Journal of Agricultural Research

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Research Article

Indian Journal of Agricultural Research, volume 55 issue 3 (june 2021) : 374-378

The Genotype and Crop Age Effect on Nutritive Value of Corn Forage

N.P. Indriani1,*, Y. Yuwariah2, D. Ruswandi3
1Department of Livestock Nutrition and Feed Technology, Faculty of Animal Husbandry, University of Padjadjaran, Jatinangor, Sumedang, Indonesia.
2Laboratory of Crop Production, Faculty of Agriculture, Jatinangor, Sumedang, University of Padjadjaran, Indonesia.
3Laboratory of Plant Breeding and Seed Technology, Faculty of Agriculture, University of Padjadjaran, Jatinangor, Sumedang, Indonesia.
Cite article:- Indriani N.P., Yuwariah Y., Ruswandi D. (2021). The Genotype and Crop Age Effect on Nutritive Value of Corn Forage . Indian Journal of Agricultural Research. 55(3): 374-378. doi: 10.18805/IJARe.A-604.

ABSTRACT

Background: The Corn crop (Zea mays) was one type of feed crop which is a good source of crude fiber for ruminant. Corn crops had several types of genotypes and each genotype had its advantages in terms of productivity and nutritional content. 

Methods: The study was conducted from January to May 2018, at the Agricultural Research and Development Research Studio located at Arjasari Village, Arjasari District, Bandung Regency, West Java, in Indonesia. The purpose of this study was to determine the effect of various genotypes and crop ages on crude protein, crude fiber, crude fat, energy and Nitrogen free extract of Corn forage. This research was designed with an experimental method using a Completely Randomized Design. The treatments in this study were the genotype of Corn crop and the crop age.

Result: The results of the statistical analysis showed that the interaction of genotype and age gave different results on Nitrogen free extract and crude fiber at 5% significant level test. Genotype and age interaction did not give different results on Energy, Crude Fat and Crude Protein at 5% significant level test.

INTRODUCTION

The development of Corn in Indonesia has very good prospect as one of the most important sources of carbohydrate after the rice. Indriani et al., (2019), states that ruminant productivity depends on the availability of high-quality forage. Furthermore Kabir et al., (2019) states that farmers grow Corn crop to be consumed as food and feed. The opinion of Basit et al., (2018) informs that there is very important need to develop Corn varieties genetically to obtain the forage yields and higher nutritional quality.
       
Updating agronomic adaptation, yields and quality are required in order to get new plant genotypes in the area (Mut et al., 2015). Genetic characters are controlled by the action of additive genes and can be used for plant improvement through selection (Singh et al., 2019). Resistance genotypes will help varieties against viral diseases and controlling plant viruses (Sravika et al., 2019). According to Banotra et al., (2017) the plant growth and development is influenced by the selection of cultivars and varieties for different yields, quality and maturity of plants. Islam et al., (2020) said that the best genotypes improving rice varieties.
       
Superior hybrids reduce the negative influence of environment and increase the positive factors of hybrid yields (Yuwariah et al., 2020). One effective tool in influencing the production and the forage quality of maize crop is the selection of suitable maize genotypes (Hakl et al., 2017). Sufficient genetic diversity, heritability and genetic advancement under normal and heat stress environments are suitable for breeding improvement programs (Thapa et al., 2019). Vaswani et al., (2016) showed two varieties of maize harvested at 70-80 DAP (days after planting) and resulted green, fresh, good quality and palatable forages were efficient for ruminant feed. According to Cahya (2018), harvest age determines the quality of Corn crops. The selections of crop characteristics is an effective way to develop the high production crop (Verma et al., 2015).
       
Various genotypes of corn crops animal feed differ substantially in their chemical composition (Vaswani et al., 2016). The research on genotype can select the high quality crop as systematic method of crop development in the future (Chowdhury et al., 2020). The genotype advantage correlated with wide adaptation and growth strength in the rain fed conditions (Giridhar et al., 2016). Rochana et al., (2016) states that crude protein is very important for the life and ruminants growth. Crude protein helps in breaking crude fibers derived from forage and providing amino acids for ruminants. According to Salama (2019) the lowest crude protein is at the highest harvest age with the highest crude fiber. Hartadi et al., (2005) stated that Total Degestible Nutrient (TDN) values was influenced by crude protein, crude fiber, crude fat and Nitrogen free extract (NFE). Higher composition will increase the forage TDN value and vice versa. NFE level is influenced by forage feed water content, ash, crude protein, crude fat and crude fiber.

MATERIALS AND METHODS

The study was conducted from January to May 2018, at the Agricultural Research and Development Research Studio (SPLPP) at 800 m AGL and 3500 mm/year rainfall located in Arjasari Village, Arjasari District, Bandung Regency in the West Java. The research used  three maize genotypes which are containing high crude protein. This research was conducted by an experimental method. The design used was a Completely Randomized Design (CRD) with a factorial pattern of 3 x 3 which was repeated 6 times. There were 54 experimental units:
 
a. The first factor was Maize genotype
      G1: 1x4 (DR10 x DR 18)
      G2: 3x4 (MDR 741 x DR18)
      G3: VAR B DR14 x DR18
b. The second factor was the age of Maize crop
      U1: 80 DAP
      U2: 90 DAP
      U3: 100 DAP
c. Response design
       
Observation of forage quality included the crude protein, crude fiber, crude fat, energy and NFE.
       
The next step was data analysis using the Anova method for variance analysis. The analysis used Duncan’s multiple range test to find out the differences in mean value. Statistical calculations completed by the SAS 9.4 version software.

RESULTS AND DISCUSSION

Table 1 to 5 showed the results of the reseach observation as the output of statistical calculations. The tables describe the results of NFE, crude fiber, crude protein, energy and crude fat.
 

Table 1: Genotype and crop age interaction effect on NFE (%) of corn crop forage.


 

Table 2: Genotype and crop age interaction effect on crude fiber (%) of corn crop forage.


 

Table 3: Genotype and crop age treatment effect on average crude protein (%) of corn crop forage.


 

Table 4: Genotype and crop age treatment effect on average energy (kcal/kg) of corn crop forage.


 

Table 5: Genotype and crop age treatment effect on average crude fat (%) of corn crop forage.


       
Table 1 showed genotype and crop age interaction on NFE for all treatments. Based on genotypic variance and crop age, the NFE showed significant differences. The genotypes gave different percentages of NFE at various harvest ages. The genotype and crop age interaction on NFE content (% NFE) reached the highest on genotype G1 (50.9767%) at 100 days and did not differ from genotype G1 at 90 days (49.8233%), G2 at 100 days (49.823%), G3 at 90 days (48.4233%) and G3 at 100 days (49.6817%). In the Same age of 90 days, the genotype G2 (47.5567%) had NFE significantly lower than G1 (49, 8233%) and G3 (49.4233%). High NFE levels in 100 days of harvest was may be due to the accumulation of sugar in the stems and the corn seed cause a sweet taste. These carbohydrates will increase the NFE levels in the forage. In young plants (80 days) the NFE was significantly lower than old plants (100 days). According to Rochana et al., (2016), NFE levels are strongly influenced by forage nutrient content.
       
Plants grow on field can express their genotypic advantages very well. According to Ruswandi and Syafi’i (2016) the genotypic adaptation produce different responses based on  the environment. Research by Ilmawan (2017) shows that corn crop environment affects the age of harvest. The results of Ammodu et al., (2014) study showed that Shimaz Corn NFE content of 91 DAP was 53.6% and significantly lower than WASA Corn 1 NFE (56.6%). Harvest at 105 DAP, the Shimaz NFE content (49.1%) was significantly lower than WASA 1 NFE (52.1%). Likewise the harvest at 119 DAP, Shimaz NFE (48.1%) was significantly lower than WASA 1 NFE (51.7%).
       
Table 2 showed the genotype and harvest age interaction on crude fiber content. The results of variance showed that corn forage crude fiber was strongly influenced (P <0.05) by genotype and age of harvest. The genotypes gave different percentages of crude fiber at various harvest ages. The highest crude fiber was found in G2 at 80, 90 and 100 days witch were 31.3350%, 31.9167% and 32.6433% respectively and did not differ to G3 at a crop age of 100 days (32.1250%). Interaction of genotype and crop age for G3 (VAR B DR14xDR18) showed the crude fiber increased with increasing crop age. According to Haryani et al., (2018) the crude fiber increases as the crop age increase. Opinions from Lemaire and Belanger (2020) suggest that analysis of genetic and environmental variations helps a better understanding of genotype-environment-management-production interactions and forage quality. The results of Hajar et al., (2019) showed that Sorghum crude fiber forage gave different value for different varieties. Variety 12 FS9006, 13FB7001 and 12549001 reached 30.12%, 28.09% and 31.71% respectively.
       
Table 3 showed the average crude protein content of Corn forage G1 (DR10xDR18 1x4), G2 (MDR741xDR18 3x4) and G3 (VarBDR14xDR18) were similar and they were 8.8978%, 8.8339% and 8.4706% respectively. Average crude proteins for various ages reached the highest at 80 DAP. The crude protein content of 80 DAP, 90 DAP and 100 DAP were 9.7122%, 8.9656% and 7.5244% respectively. This was in line with Haryani et al., (2018) that crude protein content is inversely proportional to grass age. The crude protein content decreases with increasing cutting age. According to Burton et al., (1967), the quality of forage decreases with increasing crop age. The genotype and crop age interactions are not significantly different. The results of Amasaib et al., (2016) explained that genotype had no effect on crude protein content of Cyamopsis tetragonoloba (Guar), namely the Gm1 and Gm3 genotypes. The forage with a high nutrient can be recommended for ruminants. Therefore, to produce high nutritional need to increase the nutrient intake of plants (Susilawati et al., 2019).
       
According to Turano et al., (2016), the crude protein of Pearl millet grass x Napier grass hybrids 2 (PMN2), PMN3, 5344 and 4604 are the similar of 6.4%, 7.0%, 7.9% and 7.9% respectively. The results of Hajar, et al., (2019) showed that the crude protein of sorghum 12 FS9006, 13FB7001 and 12549001 variety were 6.62%, 6.47% and 9.18% respectively. In the study of Vaswani et al., (2016) the crude protein of Corn forage HTHM 5101, DHM 117 and HM variety were 8.39%, 6.56% and 7.09% respectively. In the study of Tufail et al., (2020) Agaitii Berseem 2002 genotype was superior compared to LBFI (Landrace produced by local farmers) and LBMI (Landrace sold locally in the agricultural market) genotype. Agaitii Berseem 2002 produced the best quality forage if harvested at 65, 110 and 150 DAP.
       
There were significant variations for green forage energy  among the maize genotypes (Table 4). According to Ruswandi and Syafi’I (2016) each genotype has different character in responding to their environment. Furthermore according to Ullmann et al., (2017) forage quality can be determined by genotypic and phenotypic. Miller et al., (2014) explain that for growing plants need to consider genetic variations in phenotypic plasticity to compare input substances and other environmental variables.
       
The average energy of the Corn forage on genotypes G1 (DR10xDR18 1x4), was significantly lower (2921.22 kcal) than G2 (MDR741xDR18 3x4) (3001.33 kcal) and G3 (VarBDR14xDR18) (3018.83 kcal). The average energy for various  corn ages did not differ significantly at 80 DAP, 90 DAP and 100 DAP, which were 2970.11 kcal, 2988.78 kcal and 2082.50 kcal respectively. In the results of Turano et al., (2016) study, the forage energy content for Pearl millet x Napier grass 2 (PMN2) hybrid, PMN3 hybrid and 5344 hybrids are the same at 1700 kcal/kg and 4604 hybrid has 1600 kcal/kg.
       
In Table 5, the average crude fat G1 genotype (DR10xDR18 1x4) was significantly lower than G2 (MDR741xDR18 3x4) and was not significantly differ to G3 (VarBDR14xDR18) with were 5.6872%, 6.3422% and 5.8644% respectively. Average crude fats for various Corn ages were not significantly differ among 80 DAP, 90 DAP and 100 DAP, witch were 5.8789%, 6.0906% and 5.9244% respectively. The  results of Indriani et al., (2018) the fat of corn crops of 8x14 genotype was 3.46% and was significantly different than others 21 genotypes.

CONCLUSION

There are interactions on genotypes and crop age that give different results on NFE and crude fiber at 5% significant level. The genotype and age interactions do not give different results on energy, crude fat and crude protein at 5% significant level.
 

ACKNOWLEDGEMENT

The authors would like to appreciate the Rector of Universitas Padjadjaran for funding this research through Academic Leadership Grant (ALG) program  to Prof. Dr. Ir. Yuyun Yuwariah, M.S.

REFERENCES


  1. Amasaib, E.O., Ibrahim, R.A.B.H and Abdalla, A.W.H. (2016). Nutriens and anti-nutrients analysis of Guar (Cyamopsis tetragonoloba) forage genotypes. International Journal of Science, Environment. 5(5): 2865-2876.

  2. Amodu J.T., Akpensuen, T.T., Dung, D.D., Tanko, R.J., Musa, A., Abubakar, S.A., Hasan, M.R., Jegede, J.D. and Sani, I. (2014). Evaluation of maize accession for nutriens composition, forage and silage yield. Journal of Agricultural Science. 6(4): 178-187.

  3. Banotra, M., Sharma, B.C., Nandan, B., Verma, A., Shah, I.A., Kumar, R., Gupta, V. and Nangial, T. (2017). Growth, phenology, yield and nutrient uptake of sweet corn as influenced by cultivar and planting times under irrigated subtropics of shiwalk foot hills. Int. J. Curr. Microbiol. App. Sci. 6(10): 2971-2985.

  4. Basit, A., Khaliq, A., Pervez, A., Hayet, S. and Akhtar, M.S. (2018). Assessment of maize genotypes for forage yield and quality. J. Plant Breed Genet. 6(1): 9-14.

  5. Burton G.W., Hart, R.H. and Lowrey, R.S. (1967). Improving forage quality in bermudagrass by breeding. Crop Science Society of America. 7(4): 324-332.

  6. Cahya, Jamil Eko dan Ninuk Herlina. (2018). The Potency Test Six Varieties of Sweet Corn (Zea mays saccharata Sturt) on Lowland Pamekasan Regency. Journal of Plant Production. 6(1) : 92-100. (in Indonesian).

  7. Chowdhury, M.M., Haque, M.A., Malek, M.A., Rasel, M., Molla, M.R. and Ahamed, K. (2020). Morphological and SSR marker based diversity analysis of lentil (Lens esculenta) genotypes using yield and yield contributing characters. Indian Journal of Agricultural Research. 54(4): 429-436. DOI: 10.18805/IJARe.A-464.

  8. Giridhar, K., Kumari, S.S., Rajani, A., Sarada, C. and Naidu, N. (2016). Identification of potential genotypes of fenugreek in rainfed vertisols for yield and diosgenin content. Indian Journal of Agricultural Research. 50(4): 311-317. Doi: 10.18805/ijare.v0iOF.8603

  9. Hajar, L. Abdullah dan D. Diapari. (2019). Production and nutrient content of sorgum hybrid varieties with different planting distances as feed source. Journal of Nutrition Science and Feed Technology. 17(1): 1-5. (in Indonesian).

  10. Hakl, L., Laucka, R., Jirmanova, J. and Jambar, V. (2017). Influence of genotype. Site and year on maizenutritive value-yield relationship. Scientia Agriculturae Bohemica. 48(2): 47-53.

  11. Hartadi H., Resohadiprodjo, S., Tillman, A.D. (2005). Feed Compostion Table for Indonesian. Gadjah Mada Press. Fifth Issue. Yogyakarta. (in Indonesian).

  12. Haryani, H., Norlindawati, A.P., Norfadzrin, F., Aswanimiyuni, A. and Azman, A. (2018). Yield and nutritive values of six Napier (Pennisetum purpureum) cultivars at different cutting age. Malaysian Journal of Veterinary Research. 9(2): 6-12.

  13. Ilmawan, E. (2017). Dry stress tolerance level of Corn crop genotypes (Zea mays L.). Jurnal Agrominansia. 2(2): 119-128. (in Indonesian).

  14. Indiani, N.P., Yuwariah, Y., Nuraini, A. and Ruswandi, D. (2018). Nutrient content of various Padjadjaran hybrid maize as feed forage at arjasari village Bandung. Asian Journal of Crop Science. 10(3): 121-125. Doi: 10.3923/ajcs.2018.121.126.

  15. Indriani, N.P., Mustafa, H.K. Ayuningsih, B. and Rochana, M.A. (2019). Production and nitrogen, phosphorus and calcium absorption of sword bean leaf (Canavalia gladiata) in application of rock phosphate and VAM inoculation. Legume Research. 42(2): 238-242. Doi: 10.18805/LR-422.

  16. Islam, S.S., Anothai, J., Nualsri, C. and Soonsuwon, W. (2020). Genetic variability and cluster analysys for phenological traits of Thai indigenous upland rice (Oriza sativa L.). Indian Journal of Agricultural Research. 54(2): 211-216. DOI:10.18805/IJARe.A-461.

  17. Kabir S.H., Das, A.K., Rahman, Md, S., Singh, S.K., Morshed, M. and Marma, A.S.H. (2019). Effect of genotype on proximate composition and biological yield of maize (Zea mays L.). Archieves of Agriculture and Environmental Science. 42(2): 185-189.

  18. Lemaire, G. and Belanger, G. (2020). Allometries in plant as driver of forage nutritive value: A review. Agriculture.10(5): 6-18.

  19. Miller, R.E., Gleadow, R.M. and Cavagnaro, T.R. (2014). Age versus stage 2 does ontogeny modify the effect of phosphorus and arbuscular mycorrhizas on above -and below-ground defence in forages sorghum. Plant Cell an Environment. 37: 929-942.

  20. Mut, Z., Akay, H. and Erbas, O.D. (2015). Hay yield and quality of oat (Avena sativa L.) genotypes of world wide origin. International Journal of Plant Production. 9(4): 507-522.

  21. Rochana, A., Indriani, N.P., Ayuningsih, B., Hernaman, I., Dhalika, T., Rahmat, D. and Suryanah, S. (2016). Feed forage and nutrition value at altitudes during the dry season in West Java. Animal Production.18(2): 85-93.

  22. Ruswandi, D., dan M. Syafi’i. (2016). Preliminary selection of Unpad Corn for shading tolerant in Agroforestry system using albizzia. Jurnal Agrotek Indonesia. 1(1): 47-56. (in Indonesian).

  23. Salama, H.S.A. (2019). Yield and nutritive value of maize (Zea mays L.) forage as affected by plant density, sowing date and age at harvest. Italian Journal of Agronomy. 14(1383): 114-122.

  24. Singh, S., Verma, V., Singh, B., Sharma, V.R. and Mukesh (2019). Genetic variability, heritability and genetic advance studies in pea (Pisum sativum L.) for quantitative characters. Indian Journal of Agricultural Research. 53(5): 542-547. DOI:10.18805/IJARe.A-5245. 

  25. Sravika, A., Kennedy, J.S., Rajabaskar, D. and Rajeswari, E. (2019). Field screening of greengram (Vigna radiata L.) genotypes for resistance against Urdbean Leaf Crinkle Virus. Indian Journal of Agricultural Research. 53(4): 458-462. DOI: 10.18805/IJARe.A-5184.

  26. Susilawati, I., Indriani, N.P., Khairani, L. and Tanuwiria, U.H. (2019). Increase nutritional content and in vitro digestibility of forage legumes by adding molybdenum with foliar spray methods. Legume Research. 42(4): 35-41. DOI: 10.18805/LR-406.

  27. Thapa, R.S., Sharma, P.K., Kumar, A., Singh, T. and Pratap, D. (2019). Assessment of genetic variability, heritability and genetics advance in wheat (Triticum aestivum L.) genotypes under normal and heat stress condition. Indian Journal of Agricultural Research. 53(1): 51-56. DOI: 10.18805/IJARe.A-5095.

  28. Tufail, M.S., Krebs, G.L., Southwell, A., Piltz, J.W., Norton, M.R. and Wynn, P.C. (2020). Enhancing performance of berseem clover genotypes with better harvesting management through farmers participatory research at smallholder farms in Punjab. Scientific Reports.10(3545): 1-12.

  29. Turano, B., Tiwari, U.P. and Jha, R. (2016). Growth and nutritional evaluation of Napier for ruminants. Tropical Grasslands- Forrajes Tropicales. 4(3): 168-178.

  30. Ullmann, I., Herrmann, A., Hasler, M. and Taube, F. (2017). Influence of the critical phase of stem elongation on yield and forage quality of perennial ryegrass genotypes in the first reproductive growth. Field Crop Research. 205: 23-33.

  31. Vaswani, S., Kumar, R., Kumar, V., Ray, D. and Kumar, M. (2016). Nutritional and mineral composition of diferens varieties of normal and high quality protein maize fodder at post-Cobstage 1. International Journal of Science, Environment and Technology. 5(5): 2719-2727.

  32. Verma, A.K., Jyothi, K.U. and Doraje Rao, A.V.D. (2015). Variability and character association studies in dolichos bean (Lablab purpureus L.) genotypes. Indian Journal of Agricultural Research. 49(1): 46-52. DOI: 10.5958/0976-058X.2015.00006.2.

  33. Yuwariah, Y., Indriani, N.P., Ariyanti, M., Azizah, E. and Ruswandi, D. (2020). Genotype x Environment interaction of maize hybrids under intercropping with sweet potato in Indonesia. J. Agron. 19(1): 31-39.
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