Submitted18-01-2020|
Accepted15-03-2020|
First Online 15-05-2020|
doi 10.18805/LR-551
ABSTRACT
INTRODUCTION
MATERIALS AND METHODS
To measure the DMY, cutting was carried out during the early flowering stage. Fresh alfalfa (1.0 kg) was dried in an oven at 65°C until the weight was constant and the DMY per ha was calculated. Fresh alfalfa (0.5 kg) was taken from each plot and the stems and leaves were separated. The stems and leaves were weighed after drying and then the leaf to stem ratio (LSR) was calculated. The WSR was calculated by the as follow (Chen et al., 2014).
The crude protein (CP) content was determined by the AOAC method (AOAC, 1990). The acid detergent fiber (ADF) and neutral detergent fiber (NDF) contents were measured with ANKOM fiber analyzer filter bag method (Anonymous, 1997). The dry matter intake (DMI), digestible dry matter (DDM) and relative feed value (RFV) were calculated as follows (Albayrak et al., 2018; Avci et al., 2017). Dry matter intake (DMI) = 120/NDF; digestible dry matter (DDM) = 88.9 - (0.779 × ADF) and RFV = DMI × DDM/1.29.
The experiment was conducted for four years (2015, 2016, 2017 and 2018) in one location. Analysis of variance (P<0.05, P<0.01) and correlation analysis (Table 5) were performed using SAS software (SAS, 9.1). The data processing was performed with Excel 2010 and the figure was drawn with Sigma Plot software (Sigma Plot, 12.5).
RESULTS AND DISCUSSION
Significant differences (P<0.05) were observed in the WSR among the varieties (Table 1). The WSR of Caoyuan No. 3 was highest from 2015 to 2018. The four-year average WSR of the alfalfa varieties decreased with the increase of the FD rating. The WSRs of Caoyuan No. 3, Zhongmu No. 2, Queen, Gold Empress and Adrenalin (FD 1-4) were significantly higher (P<0.05) than those of Sardi, WL525HQ and WL903 (FD 7-9). There was a significant negative correlation between the FD rating and the WSR, with a correlation coefficient of -0.988 (Table 5). Similar results were obtained in previous studies (Brummer et al., 2002). This indicated that the WSRs of fall-dormant alfalfa were markedly higher than those of nondormant alfalfa. It is likely that the accumulation of raffinose and amino acid contribute to enhancing cold tolerance in fall-dormant alfalfa (Liu et al., 2019). This positive association between winter survival and FD has been reported in previous studies (Brummer et al., 2000; Liu et al., 2019), which recommended that FD be used as an important indicator for selecting varieties of winter hardiness (Barnes et al., 1979).
Table 5: Correlation analysis for fall dormancy (FD), dry matter yield (DMY), crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), digestible dry matter (DDM), relative feed value (RFV), winter survival rate (WSR) and leaf to stem ratio (LSR) of alfalfa varieties from 2015 to 2018.
Crude protein content
Significant differences (P<0.05) were observed among the alfalfa varieties in terms of CP contents (Table 2). The average CP contents of the varieties over four years ranged from 17.27 to 21.17%. Zhongmu No. 2 and Caoyuan No. 3 showed significantly higher (P<0.05) CP contents than the other varieties. Their superiority, in terms of CP content, suggests that higher CP contents were related to their FD. As the FD of alfalfa varieties has a major effect on the CP content of dry matter, the dormant alfalfa varieties almost always had higher CP contents (Avci et al., 2017). The CP contents of alfalfa were determined to be 20.99% (Al-Ghumaiz, 2012), 17.90-19.70% (Avci et al., 2017) and 16.58-21.24% (Albayrak et al., 2018); our results are generally similar to those of the aforementioned studies.
Leaf to stem ratio
The means of the LSR for the alfalfa varieties are shown in Table 2. The four-year average LSRs of the different alfalfa varieties ranged from 0.81 to 0.89. The highest LSR was recorded for Zhongmu No. 2. Alfalfa leaves are the most valuable (i.e., nutritive) parts of alfalfa plants and varieties with higher leaf to stem ratios are characterized by better quality (Strbanovic et al., 2015). Correlation analysis showed that there was a significant positive correlation (0.673, P<0.05) between the LSR and the CP contents (Table 5), suggesting that the ratio of leaves to stems is the most important determinant of quality for alfalfa. Leaves account for 35 to 45 % of low-quality alfalfa plants (LSR=0.53-0.82) and 55 to 65 % (LSR=1.22-1.85) of high-quality alfalfa plants (Putnam et al., 2008). According to this assessment, while the Queen variety (LSR=0.81) is low quality, the quality of Zhongmu No. 2, Caoyuan No. 3, Adrenalin, Gold Empress and WL903 (LSR=0.85-0.89) falls between the low- and high-quality classes. Rotili et al., (1999) also reported that the quality of alfalfa is mainly influenced by LSR and that plants with an LSR from 0.85 to 1.0 are defined as having optimal plant quality.
Neutral detergent fiber
The variance analysis of the NDF contents of the different alfalfa varieties is shown in Table 3. The NDF contents of alfalfa ranged from 48.4 to 51.0%, on average, over four years. The lowest NDF content was found in Zhongmu No. 2. In previous studies (Albayrak et al., 2018; Avci et al., 2017; Spandel and Hesterman, 1997), the NDF contents of alfalfa were reported to be 41.7-44.8, 44.8-49.6 and 39.4-47.8%, depending on the variety and year. Low NDF contents are desirable and are associated with increased animal intake. Correlation analysis showed there was a significant negative correlation (-0.849, P<0.05) between CP and NDF contents (Table 5). Avci et al., (2017) also found that CP and NDF are inversely related and that the varieties highest in CP had the lowest in the NDF contents, while the varieties lowest in CP typically had the highest NDF contents. When considered from this perspective, Zhongmu No. 2 is a high-quality variety.
Acid detergent fiber
The variance analysis of the ADF contents of the different alfalfa varieties is shown in Table 3. The four-years average of the alfalfa ADF contents ranged from 30.2 to 34.4%. In previous studies (Albayrak et al., 2018; Avci et al., 2017; Spandel and Hesterman, 1997), the ADF contents for alfalfa were found to be 30.5-34.4; 36.8-40.4; 25.2-39.2%. The ADF contents of Zhongmu No. 2 and Caoyuan No. 3 were significantly lower (P<0.05) than those of the other varieties. ADF content has a negative effect on digestibility and intake (Mader et al., 1991), indicating that the nutritional values of Zhongmu No. 2 and Caoyuan No. 3 were better than those of the other alfalfa. On the one hand, this pattern may be related to ecological factors, such as the relatively low precipitation and the high evaporation in Hohhot; it is possible that the foreign alfalfa varieties were affected by the arid climate conditions in this region (Rimi et al., 2012). On the other hand, fiber content may be closely related to genetic factors in alfalfa varieties (Albayrak et al., 2018; Hill and Barnes, 1977). These findings indicate that the chemical composition of alfalfa mainly depends on the variety and many ecological factors (Albayrak et al., 2018; Karayilanli and Ayhan, 2016).
Digestible dry matter
Significant differences (P<0.05) were found in the DDM content among the alfalfa varieties (Table 4). The DDM value of Zhongmu No. 2 was the highest in 2015 and 2016. In 2018, the DDM values of Zhongmu No. 2 and Caoyuan No. 3 were significantly higher (P<0.05) than those of the other varieties. The four-year average of the DDM contents of the alfalfa varieties ranged from 62.10 to 65.40%. Zhongmu No. 2 and Sardi had the highest and the lowest DDM contents, which was mainly due to these varieties having the highest and lowest LSRs, respectively. As already noted, alfalfa leaves have relatively higher nutritive value and intake than stems. Julier and Huyghe (1997) also reported that the digestibility of alfalfa varieties showed differences depending on their LSRs. The DDM content determined for the alfalfa varieties in our study was similar to that reported in a previous study by Avci et al., (2017).
Relative Feed Value
Significant differences (P<0.05) were observed in the RFVs among the varieties (Table 4). The four-year average RFVs of the alfalfa varieties ranged from 113 to 126. The highest and the lowest RFV values were found for Zhongmu No. 2 and Sardi, respectively. This indicated that the RFVs were significantly different among the varieties, which may be mainly due to the large amount of variation in the DDM and DMI (not shown here). RFV is derived from the DMI and DDM contents of alfalfa (Avci et al., 2017). Forages with RFVs between 150-125, 124-103, 102-87 and 86-75 are categorized as premium, good, fair and poor, respectively (Kiraz, 2011). According to this assessment, Zhongmu No. 2 is classified as premium, while the other varieties are classified as good.
Dry Matter Yield
The means of the DMY for the alfalfa varieties are shown in Fig 1. Based on the four-year average, the four varieties (FD 1-4) with the highest DMYs were Zhongmu No. 2 (11,912 kg ha-1), Adrenalin (10,559 kg ha-1), Gold Empress (10,406 kg ha-1) and Caoyuan No. 3 (9,960 kg ha-1). However, the varieties with FD ratings between 7 and 9 (Sardi, WL525HQ and WL903) performed poorly in Hohhot, indicating that there was not a significant correlation between the FD rating and DMY (Table 5). Previous studies have reported that there was no definite relationship between FD and annual forage yields (Chen et al., 2014; Rimi et al., 2012). Our results provide solid evidence to support these claims. FD should not be used as the main index for selecting alfalfa varieties in Hohhot. Previous studies have also reported that in areas with warmer winters, the establishment of suitable harvesting systems is the main factor affecting alfalfa production and FD is a secondary factor (Berti et al., 2012; Ventroni et al., 2010).
CONCLUSION
REFERENCES
- Al-Ghumaiz, N. (2012). Performance of some cool-season forage legumes growing under desert environment. Legume Research. 35: 243-247.
- Albayrak, S., Oten, M., Turk, M. and Alagoz, M. (2018). An investigation on improved source population for the alfalfa (Medicago sativa L.) breeding. Legume Research. 41: 828-832.
- Anonymous, (1997). Acid detergent fiber and neutral detergent fiber using ANKOM’s fiber analyzer F220/220. Ankom Tech. Corporation Fairport. NY.
- AOAC, (1990). Official methods of analysis. Association of official Agricultural chemists. 15th Ed. Arlington, Virginia. USA.
- Avci, M., Hatipoglu, R.T., Çinar, S. and Kiliçalp, N. (2017). Assessment of yield and quality characteristics of alfalfa (Medicago sativa L.) cultivars with different fall dormancy rating. Legume Research. 41: 369-373.
- Barnes, D.K., Smith, D.M., Stucker, R.E. and Elling, L.J., (1979). Fall dormancy in alfalfa: A valuable predictive tool. Agricultural Reviews and Manuals Arm Nc.
- Berti, M., Nudell, R. and Meyer, D.W. (2012). Fall harvesting of alfalfa in north Dakota impacts plant density, yield and nutritive value. Forage and Grazinglands. 10.
- Brummer, E.C., Moore, K.J. and Bjork, N.C. (2002). Agronomic consequences of dormant-nondormant alfalfa mixtures. Agronomy Journal. 94: 782-785.
- Brummer, E.C., Shah, M.M. and Luth, D. (2000). Reexamining the relationship between fall dormancy and winter hardiness in alfalfa. Crop Sci. 40: 971-977.
- Chen, J., Zhu, R., Zhang, Y., Cao, G. and Di, G. (2014). Yieds of alfalfa varieties with different fall dormancy levels in northeast China. Pakistan Journal of Botany. 46: 167-172.
- Fairey, D.T., Lefkovitch, L.P. and Fairey, N.A. (1996). The relationship between fall dormancy and germplasm source in north American alfalfa cultivars. Canadian Journal of Plant Science. 76: 429-433.
- Fang, S.S., Sun, Q.Z., Yan, Y.F., Liu, Z.Y., Tao, Y. and Feng, L.I. (2015). Preliminary assessment of fall dormancy in 45 alfalfa cultivars. Acta Prataculturae Sinica. 24: 247-255.
- Hill, R.R.J. and Barnes, R.F. (1977). Genetic variability for chemical composition of alfalfa. II. Yield and traits associated with digestibility. Crop Sci. 17: 948-952.
- Julier, B. and Huyghe, C. (1997). Effect of growth and cultivar on alfalfa digestibility in a multi-site trial. Agronomie.17: 481-489.
- Karayilanli, E. and Ayhan, V. (2016). Investigation of feed value of alfalfa (Medicago sativa L.) harvested at different maturity stages. Legume Research. 39: 237-247.
- Kiraz, A.B. (2011). Determination of relative feed value of some legume hays harvested at flowering stage. Asian Journal of Animal Veterinary Advances. 6: 525-530.
- Liu, Z.Y., Baoyin, T., Li, X.L. and Wang, Z.L. (2019). How fall dormancy benefits alfalfa winter-survival? Physiologic and transcriptomic analyses of dormancy process. BMC Plant Biol. 19: 205.
- Mader, T.L., Dahlquist, J.M., Shapiro, C.A. and Anderson, B.E. (1991). Long-term storage losses of alfalfa stored in loaf stacks1. The Professional Animal Scientist. 7: 13-15.
- Putnam, D.H., Robinson, P. and De-Peters, E. (2008). Forage Quality Testing. Irrigated Alfalfa Management for Mediterranean and Desert Zones. University of California Division of Agriculture and Natural Resources Pub. 8302. Chapter 16. 1-25.
- Rimi, F., Macolino, S., Leinauer, B., Lauriault, L.M. and Ziliotto, U. (2012). Fall dormancy and harvest stage effects on alfalfa nutritive value in a subtropical climate. Agronomy Journal. 104: 415.
- Rotili, P., Gnocchi, G., Scotti, C. and Zannone, L. (1999). Some aspects of breeding methodology in alfalfa. In: Proc. of The Alfalfa Genome Conf., Wisconsin.
- Spandel, E. and Hesterman, O.B. (1997). Forage quality and alfalfa characteristics in binary mixtures of alfalfa and bromegrass or timothy. Crop Sci. 37: 1581-1585.
- Strbanovic, R., Simic, A., Zivanovic, D.P.T., Vuckovic, S., Pfaf- Dolovac, E. and Stanisavljevic, R. (2015). Yield and morpnological traits in alfalfa varieties of different origin. Legume Research. 38: 434-441.
- Suzuki, M. (1991). Effects of stand age on agronomic, morphological and chemical characteristics of alfalfa. Canadian Journal of Plant Science. 445-452.
- Ventroni, L.M., Volenec, J.J. and Cangiano, C.A. (2010). Fall dormancy and cutting frequency impact on alfalfa yield and yield components. Field Crops Research. 119: 252-259.
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