Genetic, environmental and management contributions to ratoon decline in sugarcane
Introduction
Commercial sugarcane (Saccharum spp.) production entails the harvesting of mature stalks at ground level. Underground buds that are released from apical dominance then emerge to produce another (ratoon) crop that grows to maturity, and the process is repeated for as many ratoons as possible. The general decline in crop yields with successive ratoons, a phenomenon termed ratoon decline (RD), limits the economic viability of sugarcane production by increasing the frequency of costly replanting operations. Lower yields of older ratoons are generally associated with increases in pests and diseases, increased competition between tillers and subsequent tiller mortality (Chapman et al., 1992), effects of stool damage (Swinford and Boevey, 1984), weed competition (Srivastava and Chauhan, 2006), and other crop management factors. In Louisiana, poor ratoon yields have been associated with freeze damage to overwintering cane stubble (Ricaud and Arcenaux, 1986). Where sugarcane is harvested mechanically, rates of RD are much higher due to the physical damage to the stool and the effects of soil compaction. The wide range of potential factors influencing RD is indicative of the complexity of the phenomenon, and the variation that is encountered across different industries. For example, the typical number of profitable sugarcane crops harvested from a single planting range from about three (Ricaud and Arcenaux, 1986) to ten (Hoekstra, 1976). In Louisiana, the second ratoon crop is normally the last profitable crop to be harvested (Milligan et al., 1996). In contrast, some commercial plantings in South Africa are harvested profitably for as many as 20 crops.
The term ratooning ability (RA) has been commonly (and loosely) used in sugarcane literature to describe the yield performance of different cultivars at older ratoon crops. Past studies have defined RA as a ratio of older crop yields (conventionally second or third ratoon) to plant crop yields (Jackson, 1992, Milligan et al., 1996, Mirzawan and Sugiyarta, 1999). These studies, and others, focused on indirectly selecting cultivars with good RA based on performance in younger crops. Cultivar differences in RA have been investigated in many other studies (Chapman et al., 1992, Ferraris et al., 1993, Jackson, 1994, Singh et al., 2003). As a result, the focus of RD in sugarcane has been largely in association with cultivar RA only. The relative effects of cultivar, environment, and management on RD, is rarely considered. Furthermore, one of the limitations of the above definition of RA is that the yields of ratoon crops are confounded with seasonal effects (Kang et al., 1987). For example, a particular season in the second ratoon crop may favour the performance of one cultivar more than another, hence overestimating its RA relative to other cultivars. Additionally, the number of profitable crops harvested is often determined by industry norms (economics), environmental conditions, and possibly even the germplasm profiles within an industry (the genetic make-up of cultivars in an industry as determined by the proportion of Saccharum spontaneum vs. Saccharum officinarum). Hence, the use of the absolute yield of a specific crop in the definition of RA may not be applicable across environments and industries.
Ratoon decline needs to be revisited in order to develop a definition or a meaningful parameter with widespread application. The term RA may have somewhat similar meanings across different sugarcane studies; however, the definitions of RA are very often different. Due to these limitations, we use the term RD to describe the general decline in productivity with successive ratoons, while the term RA is considered as a genetic trait describing cultivar differences in RD. Ramburan et al. (2012) recently expressed cane yield as a linear or quadratic function of ratoon number, and interpreted RD patterns of different treatments from the linear and quadratic coefficients. That study showed that quadratic models fit the RD patterns better than linear models; however, the quadratic coefficients were difficult to interpret as simple, practical parameters to describe RD. A compromise between model fit and practical application was therefore suggested in favour of a linear model, which produces a simple, easily interpretable measure of a rate of decline (i.e. the linear coefficient). The use of a linear “rate” of yield decline with successive ratoons to describe RD patterns has not been attempted in the past. Such an approach may mitigate some of the limitations of past definitions of RA, and may be more widely applicable. Furthermore, RD is generally a neglected aspect of sugarcane research due to seasonal variability and the long-term nature of the subject matter.
The factors causing RD in South Africa are currently unclear. Although it is generally accepted that factors such as pests and diseases (Cadet and Spaull, 2001, Cadet and Spaull, 2003) and stool damage (Swinford and Boevey, 1984) are important, there is a general grower perception that cultivar differences in RD (i.e. RA) are of greater importance. Amidst these perceptions, we realized that the relative effects of different crop production factors on RD had never been evaluated. Information on the relative influences of cultivar, environment, and management practices on RD is essential, and is needed to support future research. The objectives of this study were to (i) explore the relative effects of cultivar, environment, and management practices on RD patterns, (ii) evaluate the appropriateness of linear coefficients to describe differential RD trends, and (iii) determine if there are statistically significant differences in RD (as defined by a linear coefficient) between various agronomic treatments.
Section snippets
Materials and methods
Four separate trial datasets were analyzed for this study. Each dataset consisted of a series of trials with different characteristics and agronomic objectives (Table 1). The approach used was to evaluate the RD patterns of different treatments within and across trials in each dataset. Different methods of analysis (described below) were employed for each dataset in order to investigate specific aspects of RD.
Dataset 1
Variance components analysis showed that the trial effect contributed 83%, 59%, and 76% of total variation in a for TCANE, ERC, and TERC, respectively (Table 2). For ERC, cultivar accounted for a higher proportion of total variation in a (8.94%) compared to TCANE (1.34%) and TERC (0.34%). This suggests that selection gains for (or selection against) RD in ERC may be achieved faster compared to gains that may be achieved for TCANE and TERC. The effect of cultivar (i.e. RA) accounted for less
Conclusions
This study was the first to investigate the long-term RD trends of sugarcane using a parameter that describes a rate of decline. The parameter a (linear coefficient) allowed for the detection of statistically significant differences in RD between treatments in various agronomic trials. This shows that it may be a suitable parameter to describe general RD in sugarcane. However, further testing of this approach under a wider range of conditions in different industries is encouraged. Retrospective
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