1 Introduction: Unprecedented Agricultural Changes and Challenges, and the Importance of Rice Diseases

This brief review deals with rice, the first food crop of humankind, and with rice diseases. It also deals with our present and future need to manage rice diseases in a sustainable way. Therefore, we also touch upon yield-reducing factors other than diseases within the tremendous diversity of contexts in which farmers grow rice. It is this agricultural, social, ecological, and economic diversity that science and research policies must address in an unprecedented global context of rapid changes and challenges.

September 2007 to July 2008 saw an extraordinary increase in global rice prices, with a peak price surpassing US$750 t−1 in February 2008. The main causes for this spike include (S. Pandey, IRRI, personal communication): (1) the inelasticity of rice trade worldwide, compared to other cereals (whose prices also increased very strongly during that period), (2) very low national rice stocks associated with plateaus in yield growth and cultivated rice area expansion rates, and (3) competition among cereals to meet global and national demands for food, feed, and energy (biofuels). There is debate, of course, about the specific contributions of various factors to this price spike, but the fact remains that, ultimately, consumers had to pay more for their food. Although this price increase may have been relatively benign to wealthy consumers, it was not so for the world’s poor: as food accounts for at least half of their daily budget (Zeigler 2001), a twofold increase in price is simply unbearable.

The vast majority of the poor worldwide – nearly 70% of them (Zeigler and Barclay 2008; R. Hijmans, IRRI, personal communication) – live in Asia, and depend on a predominantly rice-based diet (Smil 2000). Another large fraction of the poor worldwide lives in Africa, where rice is also a key staple. Although there is debate on the mechanisms that led to the 2008 spike in cereal prices, especially for rice, there is no debate on the fact that the spike built upon a steady price increase that started in 2001 (Zeigler and Barclay 2008; S. Pandey, IRRI, personal communication). There is no debate either on the fact that this was partly because the rate of global rice production has been slightly lower than 1% during the past decade, whereas it should surpass 1.5% to meet global food needs now and until at least 2020 (Greenland 1997; Daily et al 1998). Herein lies the true challenge we face: rice productivity must increase, not only because of the arithmetic needs of a growing global population (Dyson 1999) but also because more elasticity in rice production–consumption must prevent recurrence of future crises. Any factor that limits attainable yields, or that reduces actual yields, will hamper progress toward achieving both this necessary rate of increase in yield and this higher elasticity. Plant diseases are key yield-reducers. Improving rice crop health in a sustainable manner therefore can, and must, contribute to achieving global food sufficiency and reducing poverty.

2 The Importance of Rice Diseases as Yield-Reducers

The current importance of rice diseases and of rice yield-reducing factors in general is fairly well documented in the lowlands of Asia, which account for the bulk of the world’s rice production. Considering a current average attainable yield of 5.5 t ha−1, a 10-year study conducted by IRRI and its partners (Savary et al. 2000a, b) in several hundred fields across Southeast and South Asia indicates that yield-reducing factors cause 37% losses. Among these, three diseases are responsible for losses of 5% or more each: sheath blight, brown spot, and blast. This is, on average, much more than insect-related losses (0.3%, 0.1%, and 2.3% caused by leaf-feeding insects, stem borer ‘deadhearts’, and stem borer ‘whiteheads’, respectively), and this is, as expected, much less than weed infestation (approximately 20% losses). Simulation modeling (Willocquet et al. 2004) indicates that, overall, yield-reducing factors cause an average yearly yield attrition ranging from 120 to 200 × 106 t of grain over the 87 × 106 ha of lowland rice of tropical Asia. Disaggregating these figures by diseases is hard, for two reasons. One is that yield losses to diseases, and pests in general, have long been known to interact (Padwick 1956) – they are less than additive in most cases; thus, the individual contribution of a particular disease to an overall yield loss mean is often attached to the wrong assumption that removal of the injury would translate into a corresponding gain in yield. A second reason is that injuries vary strongly across production contexts: the means cited above cannot reflect the wide variation in injury intensities. Arithmetic means across large data sets do not do justice to extreme events, such as devastating virus epidemics, which can be captured only incompletely in a survey of such size. Rice production globally, for example, is constantly exposed to virus epidemics, some of which, such as rice tungro in Asia, have the potential to destroy a crop entirely (Savary et al. 2000b). Such catastrophic events overlay their yield-reducing effects on chronic, near-omnipresent diseases such as rice sheath blight. Simulation and experimental work indicate that rice sheath blight alone is responsible for yield losses of 6% across the irrigated and rainfed lowland rice systems of tropical Asia (Savary et al. 2000b; Willocquet et al. 2004). It is nevertheless a fair assumption that rice diseases cause 15% rice grain yield reductions under the current contexts of both crop production and disease management.

Simulation modeling enables us to assess the performance of disease management tools and speak of yield gains instead of yield losses. Although currently deployed management tools for diseases are quite inefficient for rice sheath blight (45–60% control efficiency at best), they are very good (95%) to excellent (nearly 100%) for blast and bacterial leaf blight, respectively. Such very high management efficiencies correspond to diseases against which host–plant resistance research, breeding, and deployment have had great success. Simulation modeling also enables us to contemplate the losses diseases might reach if continuous research for new resistance genes and their deployment were to stop. Today, bacterial leaf blight and blast cause yield losses of around 0.1%. Were host–plant resistance not deployed in currently cultivated varieties, losses in excess of 5% for each disease would be expected, with devastating consequences.

3 Research to Prevent Losses to Specific Diseases

New strategies are being developed to identify new resistance genes, with a two-pronged approach. One component is based on the systematic exploitation of existing genetic variation in rice germplasm, which enables us to dissect characters to identify candidate genes that are expressed in backcrosses and near-isogenic lines; another is based on developing a large collection of mutants, which are then screened for gain or loss of resistance. Combined, the two approaches provide convergent evidence for host–plant resistance genes and the development of a candidate gene pool. This, in turn, opens the way toward association genetics, while advanced backcross lines enable us to evaluate consensus candidate genes (Leung et al. 2001). This approach is now used for both blast and bacterial leaf blight. For instance, for bacterial leaf blight, work started in the late 1970s with the identification of resistance gene donors and was continued in inheritance studies by gene identification and the development of near-isogenic lines in the 1990s (Mew and Vera Cruz 2001), in combination with pathogen population analysis (Leach et al. 1992), understanding of pathogen genes underpinning aggressiveness (Bai et al. 2000; Vera Cruz et al. 2000), and the identification of markers of resistance genes (Leach et al. 2001). These studies led to the development and release of new resistant varieties in the 2000s. This example shows how basic research can translate into a better understanding of processes and lead to major, yet insufficiently recognized, impacts for farmers: were it not for the simulation modeling work, no one could tell that this research led to yield gains of 5–15% across Asia. The example also gives a measure of the timeline attached to any basic research required to achieve impact: assuming that the full deployment of a new rice variety takes a minimum of 10 years, 40 years of continuous support were required for the fundamental research on the diversity of the causal agent of bacterial blight, Xanthomonas oryzae pv. oryzae, and host resistance genes to be developed into practical applications. Actually, a delay of about 40 years between the inception of research and its practical application is within the range of estimates given by economists specializing in the global benefit of agricultural research (Pardey et al. 2006; Pardey and Wood 2008).

Fundamental science does not reside only at the molecular level. Basic understanding on the spread of disease epidemics during the late 1960s (Gregory 1968), on the epidemiological implications of genetic uniformity (Browning 1974), and on the dynamics of epidemics (Zadoks 1971) in the 1970s led to new ideas on how to engineer host genetic landscapes that are more resilient to plant pathogens (Wolfe 1985). The idea was then applied to the management of blast, arguably the most important, and the most genetically shifty, rice disease. It was implemented in Yunnan, China, initially as a modest collaboration between Chinese research institutions and IRRI. Several trials were attempted in the early 1990s, unsuccessfully. The need to simultaneously grow rice as food with an acceptable yield and to grow rice as a cash crop too – as a delicacy that is associated with ancient customs – led to a practical solution (Zhu et al. 2000). Four to six rows of blast-resistant indica hybrids separating a single row of japonica glutinous rice not only controlled blast but also ensured acceptable food-yield and generated increased yield-income to farmers, who are among the poorest people in China (Revilla et al. 2001). The experiment started with a few plots, each a m (0.15 ha) or less wide. Today, about 40% of Yunnan’s cultivated rice area is using such a genetic association.

This second example again illustrates the necessary time lag, about 40 years, between basic fundamental research and impact. The practical impact of scientific advances cannot be guaranteed, but the two examples show that planning for impact can be, and actually is, inherently part of scientific advances. Plant pathology exists because of the perspective of such applications, and that is probably a major asset of the discipline.

4 Dealing with Crop Health Syndromes

Diseases do not occur in isolation, as we indicated in the early part of this brief review. In essence, rice in tropical Asia is exposed to three broad syndromes, that is, three main types of disease associations:

  • –Syndrome 1: Sheath blight and stem rot (along with plant hoppers, stem borer injury, and weed infestation)

  • Syndrome 2: Bacterial leaf blight and some stem rot, sheath rot, sheath blight, brown spot, and leaf blast (along with defoliating insects, some stem borer injury, and very high weed infestation)

  • Syndrome 3: Leaf blast, neck blast, brown spot, sheath rot, and some sheath blight (along with stem borer injury and some weed infestation)

These are only broad generic patterns, emerging from multi-year, multi-site characterization work (Savary et al. 2000b, 2006). Although these patterns may not exactly fit each of the several hundred farmers’ fields surveyed, they give us a current overview. Two main findings of this characterization work are that (1) these syndromes are not site-specific: they can occur in locations several hundred micrometer apart, and (2) such crop health syndromes are very strongly dependent on patterns of cropping practices and, more generally, on production situations.

Although some farmers may be particular about a few specific diseases, such as blast or bacterial leaf blight, all farmers are concerned about crop health as a whole. A first challenge is therefore to design production contexts in which crop health syndromes would not compromise agricultural sustainability. Certainly, host–plant resistance is one component of success, but designing disease-risk-acceptable, sustainable rice production systems will also take a better understanding of the network of interactions among syndromes and production situations.

Because of shrinking agricultural water, declining rural labour, and increasing costs of fuel and fertilizer, agricultural change is taking place at an unprecedented pace in the world’s rice-producing countries. This change in production situations also translates into changes in the relative importance rice diseases (and rice yield-reducing factors in general) may have (Savary et al. 2006). A second challenge is therefore to design new production situations so that their vulnerability to new crop health syndromes would be minimized while the consequences of climate change and globalization unfold. Here again, host–plant resistance will be an important ingredient, all the more so because the new crop health syndromes are very likely to include ‘newcomers’, or diseases that were until now considered secondary in importance. Sudden outbreaks of diseases, such as the rice yellowing syndrome in 2007–2008 in Southeast Asia (I.R. Choi, IRRI, personal communication), are also to be expected.

5 Concluding Comments

When crises such as the current one unfold, agricultural scientists in general and plant pathologists in particular, inevitably refer to the need for science to generate the required response. Experience shows, however, that impact cannot be guaranteed if not grounded in long-term efforts and the accumulation of knowledge that can be mobilized. Immediate needs should not compromise long-term investment. For example, the dramatic price spike of rice in February 2008 masked the upward pressure on prices that went unnoticed for half a decade. Balancing the need for rapid impact and the necessary scientific investment can be difficult, unless strategic programs are developed. Plant pathologists are actually accustomed to dealing with these sudden seemingly erratic outbreaks – while yield losses of some 37% continue unabated season after season. Although sudden outbreaks can immediately put at risk millions of livelihoods, systematic yield attrition causes low yield, and yield instability, which both contribute to poverty, especially in South Asia and Africa. Scientific investment is not only material or technical but also human. As this manuscript is being submitted, IRRI with its African partners and with WARDA (the Africa Rice Center) will organize a new training program for breeders and plant pathologists working in eastern and south-eastern Africa. We see the building of human capital and the sharing of knowledge as powerful devices for designing scientifically sound research programs with strong practical impact.