Coffee yield losses due to injury profiles under different management strategies and production situations

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Primary and secondary crop losses

Primary crop loss is the reduction of yield and/or quality of the crop product caused by pests and diseases in the current crop cycle; this loss may result in a loss of income and/or in increased production costs (Zadoks and Schein, 1979; Nutter et al., 1993).
Secondary crop loss is the “loss in yielding capacity of future crops” (Zadoks and Schein, 1979). In annual crops, secondary losses are caused by inoculums of pathogens that remained in soil, seeds or tubers which are going to reduce the yields of the new crop sowed in the same terrain; whereas in perennial crops, secondary losses are caused by defoliations and other negative physiological effects caused by pests and diseases, which lead to loss of vigor of plants and therefore reduce the production in the next years (Zadoks and Schein, 1979). For instance, in a perennial crop such as coffee, dead branches resulting from the attack of pests and diseases in a given year, are not going to bear fruits anymore, representing that way secondary losses (Avelino et al., 2015). In economic terms, secondary losses should include the loss of income and/or the costs to manage soil and seeds, costs of production and renewal of plantations if necessary (Nutter et al., 1993).
In this research, therefore, for a perennial crop such as coffee, it is considered that each year there are primary and secondary crop losses, with these definitions: primary crop loss is the loss caused by pest and disease injuries in the current harvesting year of coffee; and secondary crop loss is the loss resulting from negative impacts of pests and diseases injuries caused in the previous year.

Production situations

The production situation is a broad concept because it involves several conditions under which the crop is grown, which leads to some differences in its definition. Some authors consider that the production situation includes the social, physical, biological, economic and technical context where an agricultural production takes place; this definition includes the management (cropping system), in the sense that farmer´s skills are part of the production situation (Savary et al., 2006b). That means that a specific biophysical context may comprise several production situations and, as a consequence, that there is no necessarily a geographic continuity among plots belonging to the same production situation. Other authors consider that a production situation is defined by the biological, chemical, physical, socioeconomic and environmental conditions under which a crop is grown, excluding the management from the definition [(Aubertot and Robin, 2013) adapted from (Breman and de Wit, 1983)] but recognizing that in a given context of production, farmers do not apply the same management. Textual definitions of production situations are given in Table 1.2. Although including or excluding management from the definition of production situation may appear as being mostly part of a semantic debate, there are some key implications, particularly when defining the attainable yield. The attainable yield actually is the yield obtained in a given production situation with no pests and diseases. Depending on authors, crop management will be included or not when calculating attainable yield. In addition, pest and disease attack levels which are the result of the interaction between the physical and the biological environment (including the host plant and the pest or pathogen) and actions conducted by the farmer (Zadoks and Schein, 1979), a reflection of socio-economic conditions, are then dependent on a production situation, or on a combination of a production situation and a particular management, depending on authors.
We retained the second meaning of production situation, i.e. with no crop management included, as used recently is studies related to the topic (Aubertot and Robin, 2013; Robin et al., 2013; Aouadi et al., 2015). The definition of production situation given by Aubertot and Robin (2013) adapted from Breman and de Wit (1983), enabled us to put the same emphasis in both production situations and management strategies. Besides, we considered that injury profiles, physiological conditions of coffee plants, yield and yield losses, are affected by a given combination of a production situation and a management strategy in each plantation. However, we maintained the idea that the attainable yield is dependent on crop management, which seems particularly true in perennial crops as coffee, where some characteristics of the plantation (plantation distances, shade type, aged the coffee tree) cannot or are difficult to be changed.
Thereby, in this research, the production situation is defined as the set of biological, chemical and physical components of the agroecosystem, and the socioeconomic and environmental (climate and topography) conditions under which the agroecosystem takes place. Soil fertility was considered as a chemical component. And, given that this research dealt with agroforestry systems, the type of shade (shade canopy) was included as an important biological component. A type of shade includes the botanical composition (species richness of herbaceous plants, bushes, palms and trees) and the structure (abundances, basal areas and shade cover) of the coffee shade canopy in this case. Given that this research was focused on the study of the crop (yields) and of injury profiles, both were excluded from the biological component of production situations. This latter decision is convenient when such components are the objects of study in order to put more emphasis on them, and to well differentiate them from other components in the study (Savary et al., 2006b).

The importance of injury profiles for crop loss assessments

It is assumed that each cropping system, which depends on the farmer´s decisions under a given production situation, leads to a particular injury profile (Aubertot and Robin, 2013); and each injury profile can have a specific impact on crop losses (Avelino et al., 2011). Both important statements mention the injury profile and not individual injuries, suggesting that analyzing the incidences or severity of only one pathogen and its impact on yields separately from other pathogens would not be enough for comparing different agroecosystems and determining which the best is for avoiding crop losses. For instance, an agroecosystem A could have less attack of a given disease than an agroecosystem B, but its crop loss could be higher due to other set of pathogens. Therefore, it is necessary to identify and analyze all the pests and diseases involved (injury profile), the management strategy and the production situation; and then, translate the impact of that injury profile in a crop loss data.
The study of injury profiles involves multiple pathosystems, and requires the intervention of several disciplines to be successful on giving the scientific bases for designing and implementing IPM (Savary et al., 2006a). For understanding and explaining injury profiles, it is necessary to study a range of cropping systems and production situations. Pest and disease outbreaks strongly depend on rainfall patterns and altitude which determines temperatures. In coffee agroecosystems, outbreaks also depend on important practices such as fertilization, pruning and regulation of shade, which are capable to modify the microclimate and the physiology of the crop (Avelino et al., 2004). Biophysical factors such as topography (inclination and orientation of the slope, altitude), distance between coffee rows, coffee tree height, type of shade (structure and composition) and shade percentage must be also measured, because they have effects on the development of pathogens (Avelino et al., 2007). The soil fertility can affect the nutritional status and vigor of coffee plants, and consequently has relationships with injury levels (Avelino et al., 2006). The relationship between biodiversity and pest and disease regulation is particularly important since there can be positive effects but also negative; for this matter, it is important to determine both the functional diversity and the botanical composition of the system (Cheatham et al., 2009).

How to assess crop losses

Currently, there are several approaches and methods suggested to quantify, estimate, model, and to generate different types of knowledge on crop losses; they can be combined and applied for coffee losses research. Several types of knowledge are empirical environment-disease relationships, empirical disease-crop loss relationships, mechanistic simulation models–single disease, mechanistic simulation models–multiple diseases, risk zoning–disease prevalence, and production situation-based models; these types of knowledge are useful for making decisions of different categories: tactical–during season decisions, strategic–between season decisions, strategic–domains for management, and strategic–research priorities (Thornley and Johnson, 1990; Cooke, 2006; Savary et al., 2006b). Important tools for modeling such as the Injury Profile Simulator (IPSIM) using qualitative data (Aubertot and Robin, 2013), or the XPEST platform for modeling yield losses caused by injury profiles with quantitative data (Aubertot et al., 2014) are currently available for generating knowledge and predictions useful for designing innovative cropping systems as part of strategies for a better control of pests and diseases.
The assessment of crop losses becomes more complex in perennial crops such as coffee due to indirect effects of several diseases and their outbreaks impacts on the yields of following years. Crop losses caused by leaf diseases such as coffee leaf rust, American leaf spot or brown eye spot for instance, are harder to quantify because they do not affect directly the fruits like other pathogens do (e.g. coffee berry borer, anthracnose), but they do affect indirectly the production of fruits through alterations of the plant physiology (Avelino et al., 2006).
Besides, when quantifying crop losses in perennial crops, there can be involved together primary and secondary losses due to the effect of a pest or disease outbreak in previous years (Zadoks and Schein, 1979). Therefore, several methods should be utilized in order to assess the overall direct and indirect effects of injury profiles and to determine correctly what primary or secondary losses are.
Surveys, experiments and modeling are the most important methods to quantify crop losses. Results combining these methods could be stronger and more reliable than individual results of each one. Results of surveys and experiments can be incorporated in the modeling. The modeling of yield losses involving multiple pests and diseases rises as one of the main methods for a full understanding of the system and to hierarchize pathogens according to the damage they cause; such understanding is a key aspect for developing long-term strategies in order to determine where an IPM is needed, and for prioritizing the pests and/or diseases which needs further research (Savary et al., 2006b; Savary and Willocquet, 2014). That kind of models for assessing losses of tropical crops, including coffee, does not exist at the moment.

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Location and establishment

A coffee experimental parcel at full sun exposure (960 m2 in total) was established in a flat terrain in the farm of the Tropical Agricultural Research and Higher Education Center (CATIE), Turrialba, Costa Rica (Lechevallier, 2013). The parcel was planted in 2010, and the experiment began in year 2013 and lasted until 2015. The parcel was located in the coordinates 9°53’11.24’’N and 83°40’07.94’’O, at 648 meters above sea level (m.a.s.l.). Turrialba is a rainy area all year long, with slightly dry periods in March and April, and highly rainy periods in June and July. In the last ten years, the mean total annual rainfall was 2781 mm and the mean annual temperature was 22.2°C. In the years on the experiment, there were more noticeable differences in the amounts of rainfall (especially in 2015), while temperatures and relative humidity were similar (Table 2.1).

Measurement of the studied variables

Each plot had 30 plants (five rows and six plants per row), the external rows and plants were defined as borders. Therefore, useful plots have 12 plants in the three central rows, where six plants were marked for measurements (Fig. 2.2). On each marked plant, three branches were marked for measurements of pests and diseases: one in the low stage, one in the middle stage and one in the upper stage (Fig. 2.3); these branches were changed every year. Besides, Tinytag PLUS2 devices (to measure microclimate: temperature and humidity) and sensors from Campbell Scientific stations (to measure leaf temperatures and leaf wetness) were installed in 12 coffee plots, two plots per treatment (Fig. 2.2).
Measurements were done during three years (2013-2015): healthy and infected/infested leaves with pests and diseases, differentiating young and old leaves, and severity were measured in marked branches monthly; dead branches were counted at the end of the harvest period each year; yield components (productive branches, fruiting nodes, fruits per node) were counted once, and coffee cherries were harvested in the entire marked plants each 15 days; samples of leaves in the middle stage of several plants in each plot were taken for analysis of nutrient contents; soil sub-samples were taken at 50cm from the trunk of marked plants, and a composite sample per plot for chemical fertility analysis; temperature and relative humidity of microclimate, and leaf temperatures and leaf wetness were measured in four key periods each year. In Chapter 4 a Table is also provided with more details of the list of the variables, the methods of measurements, calculation of additional variables when needed, and frequencies of measurements.

Location and establishment

A coffee research plot network (69 plots) for two years of research (2014-2015) was established in coffee growing communities of the canton Turrialba, Costa Rica. All of the selected coffee plots were in farms of smallholder coffee farmers. The 69 coffee plots were distributed in 27 communities of eight districts of Turrialba, covering 300 km2 (=30.000 ha) approximately (Fig. 2.4). Plots were chosen from a database build by the project CASCADE, where 150 coffee farms were described regarding crop management, shade type and topography. The general weather conditions in Turrialba were already described in section 2.1.1 and Table 2.1. However, rain gauges were also installed in several communities to have a better estimation and representation of the rainfall in different areas of the network; these data were used especially in Chapter 5, where climate was an important production situation to take into account.

Table of contents :

PART I. INTRODUCTION
Chapter 1. Problematic/Definitions/Research questions
1.1 Crop losses worldwide
1.2 Coffee crisis in America
1.3 Research needs
1.4 Definitions to state the scope of this research
1.4.1 Injury profile
1.4.2 Crop loss
1.4.3 Yield loss
1.4.4 Attainable yield
1.4.5 Actual yield
1.4.6 Economic loss
1.4.7 Primary and secondary crop losses
1.4.8 Production situations
1.4.9 Management strategies
1.5 The importance of injury profiles for crop loss assessments
1.6 How to assess crop losses
1.7 Regulation of pests and diseases and other ecosystem services
1.8 Justification of the research
1.9 Research questions and hypotheses
PART II. MATERIALS AND METHODS
Chapter 2. Materials and methods
2.1 General strategy to respond the research questions
2.2 Coffee Losses Experiment (CoLosses)
2.2.1 Location and establishment
2.2.2 Experimental design
2.2.3 Measurement of the studied variables
2.3 Coffee Research Plot Network (CASCADE)
2.3.1 Location and establishment
2.3.2 Objective and strategy for the selection of coffee plots
2.3.3 Experimental design
2.3.4 Measurements of the studied variables
2.4 Statistical methods
PART III. RESULTS
Manuscript 1: Effects of shade, altitude and management on multiple ecosystem services in coffee agroecosystems
Manuscript 2: Primary and secondary yield losses caused by pests and diseases: assessment and modeling in coffee
Chapter 5. Coffee yield losses due to injury profiles under different management strategies and production situations
Manuscript 3: Primary and secondary yield losses caused by injury profiles under different management strategies and production situations in coffee agroecosystems
Chapter 6. Reduction of coffee losses and provision of multiple ecosystem services
Manuscript 4: Coffee agroforestry systems for reducing crop losses while providing multiple ecosystem services
PART IV. GENERAL DISCUSSION
Chapter 7. General discussion
7.1 Scientific contributions of this Ph.D. Thesis in the fields of crop losses research and assessment of ecosystem services
7.1.1 Both production situations and management strategies determine coffee yield and pest and disease injuries
7.1.2 In perennial crops such as coffee, injury profiles affect yield losses not only during the same year but also during the following year(s)
7.1.3 Diversified agroforestry systems have better chances to regulate pests and diseases and provide multiple ecosystem services simultaneously
7.2 Conceptual models and definitions regarding crop losses adapted to perennial crops
7.3 Implications for the design and management of tropical agroecosystems oriented towards the reduction of crop losses and provision of multiple ecosystem services
7.4 Main prospects

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