Download PBIO*3110 Crop Physiology Lecture #1 Introduction: Level of

PBIO*3110 ­ Crop Physiology Lecture #1 Fall Semester 2008 Lecture Notes for Thursday 4 September How is crop yield related to the absorption of sunlight by a chlorophyll molecule? Introduction: Level of organization Learning Objectives 1. To appreciate what is meant with levels of organization and be able to name at least three levels of organization of a crop canopy. 2 To know what are the five components of the yield equation. 3 To understand what leaf area index (LAI) is and know how LAI influences canopy light interception.
Document1/8/19/2008 1 Crop physiology and its level of organization Crop physiology is the study of plants at the whole­plant and plant­community level of organization. Plant molecular biologists study plant processes in test tubes, biochemists measure processes in isolated plant cells and organelles, and plant physiologists study plants by measuring the response plant organs (e.g., leaves). At the other end of the spectrum, communities of one or more crop species at the landscape level are studied in agronomy. In crop physiology, whole plants and communities of plants of the same genotype are studied, placing it in between plant physiology and agronomy (Fig.1). Without judging differences in the real or perceived value of various disciplines of plant science, one can distinguish differences in terms of time and space associated with disciplines that operate at different levels of organization. For instance, a physicist/photochemist who studies the initial light reactions in photosynthesis will not need more than a small laboratory bench and can study a complete “cycle” in a matter of seconds, whereas the “laboratory” of an agronomist may consist of an 1­ha field, which has to be utilized for a number of years before a study is completed. The scale in terms of time and space can be estimated for the various disciplines involved in the process of photosynthesis, ranging from the level of organization for photochemistry, i.e., the absorption of photons by a chlorophyll molecule and the fate of the excited chlorophyll molecule, to the level of organization for economic yield, i.e., a full life cycle of a crop, and for the various levels of organization in between those two extremes (Fig. 1). The rate by which processes occur can be described in terms of ‘half­time’, i.e., the time necessary for the number of molecules/species in a given state to decrease by 50%. For instance, the half­time of the absorption of blue light is less than 1 × 10 ­15 seconds, whereas the “half­time” of a corn crop is about 3 months (considering that time from planting to maturity is about 6 months) or about 1 ×10 +7 seconds. In a similar vein, the volume that is taken up by “these processes” can be estimated. The volume of an exciton may be about one cubic nano meter (1 nm 3 = 10 ­27 m 3 ), whereas the volume of a corn crop in a farmer’s field is about 3 m (high) × 1 ha (10 +4 m 2 ) > 10 +4 m 3 (Fig. 3). When moving from lower to higher levels of organization, the complexity of “the system” increases. In crop Fig. 1. Approximate scale of levels of organization involved in photosynthesis.
Document1/8/19/2008 2 physiology, the simple logic of lower­level processes is applied to the complexity of the higher level of organization that is the crop canopy throughout its life cycle. Agronomy is the study of crops and cropping systems at the landscape scale over periods of years. At this level of organization, the complexity of the system is so large that no attempts are made to examine the mechanisms that underlie the observed responses to management or climate. For instance, an agronomist may carry out a multi­location, multi­year study of 10 corn hybrids grown at three plant population densities and three N fertilizer applications and the three rates of plant density and N were (i) 50% of the recommended rate, (ii) the recommended rate, and (iii) 50% greater than the recommended rate. The objective of the study was to determine which combination of N fertilizer, plant population density, and corn hybrid resulted in the highest yield. Results of the first year of the study show that the highest­yielding combination varied from location to location. For instance, the highest yield in one location was recorded for Hybrid A grown at the high plant­population density and the high N fertilizer rate, whereas the highest yield in another location was recorded for Hybrid B grown at the low plant density and yield of this hybrid did not differ among the three fertilizer rates. When the study was repeated the next year, results showed that Hybrid C grown at the recommended plant­population density and at the recommended N rate was among the top yielding entries at all locations, whereas neither Hybrid A nor Hybrid B were among the top yielding treatment combinations in any of the locations. How does one interpret those results? The most common response would be to repeat the study, but it is unlikely that more results will resolve the issue. Another approach, which would currently receive considerable support, would be to measure global gene expression of seedlings of the 10 hybrids grown at various N rates under greenhouse conditions. However, nothing would be learned from that study either. A third response would be to measure in the field and at the whole­plant level the physiological mechanisms that are involved in the different responses of the hybrids to the plant density and N treatments. Once we know the reasons for the particular response of a hybrid to soil N levels under various climatic and soil conditions, we can tailor the N application for hybrid and field conditions. This would be the approach a crop physiologist would take. The scientific approach to agriculture has been to isolate (i.e., experiments in which everything else is equal except the studied phenomenon) and to reduce (i.e., the process by which, ultimately, a phenomenon is quantified in terms of one or more essential molecular processes), because the system (e.g., a field of wheat, a greenhouse with tomatoes) is too complex. Whereas the unraveling of biological systems to simple chemical and physical phenomena has improved our general understanding of the biology, it is necessary to understand how the chemical and physically processes interact within a whole plant grown from seed to maturity under natural conditions for this information to be useful in agronomy. Nothing has contributed more to the increase in agricultural efficiency during the past 100 years than the genetic improvement of crop cultivars, i.e., plant breeding. Whereas “scientific” plant breeding has been practiced since the re­discovery of Mendel’s laws in the early 1900s, biotechnology has been applied to cultivar development only during the last 10 to 20 years. Discoveries at lower levels of organization have lead "lower­level" scientists to raise unrealistic expectations concerning the potential impact of changes at the molecular level on processes at
Document1/8/19/2008 3 Fig. 2. Mean US maize yield in bu/A from 1860 to present.
higher levels of organization (e.g., agricultural productivity). Recent advances in molecular biology are a point in case. The complexity of traits is paralleled to some extent by the number of genes that control the traits. Pest resistance, for instance, is controlled by a number of single­ gene traits that can be identified, isolated, and transferred relatively easy at the molecular level. Traits that have been introduced during the past 15 years in commercial crop cultivars by using biotechnology are almost exclusively traits related to pest tolerance (i.e., disease, insect, and weeds). The second wave of agricultural biotechnology may bring improved nutritional quality and special­use crops (such as the production of high­valued chemical compounds), again involving modification of relatively few genes. The third wave of agricultural biotechnology is supposed to produce crops that will be more tolerant to abiotic stresses such as water and N stress. It is not clear, however, when this will materialize. Increasing yield is an entirely different story. The genome of corn contains something in the order of 30,000 genes and a very large proportion of these genes directly affect grain yield and attempts to find major “yield genes” have not been successful. In contrast to biotechnology, traditional crop breeding has been very successful when it has focused on yield per se. For instance, mean corn yield in the Ontario and the US has increased sevenfold yield between the late 1930s and present (Fig. 2), and more than 50% of this yield improvement can be attributed to genetic improvement (Lee and Tollenaar, 2007). Yield improvement has resulted from empirical selection at the canopy level at maturity, i.e., grain yield of a community of plants of one genotype has been evaluated by growing it across large numbers of environments. Unfortunately, traditional crop breeding for yield per se is not going to successfully utilize molecular methods of gene transfer (involving many genes) until it is known how lower­level processes are translated in higher­level responses. This requires an understanding of the basic factors underlying yield formation of a crop canopy. Document1/8/19/2008 4 Factors underlying economic yield: The yield equation Economic yield of a crop (Y e ) is the result of the spatial and temporal integration of biological processes across a community of plants during the life cycle of the crop. The temporal integration of the factors underlying economic yield at the crop­canopy level is expressed in the yield equation: t = harvest date Ye = I(Q × I A ' × , × ρ) dt [1] t = planting date where economic yield (Y e) is a function
of (i) incident (solar) radiation (Q) , (ii) fraction of incident (solar) radiation absorbed by the crop canopy (I A ' ), (iii) overall efficiency of conversion of absorbed radiant energy into chemical energy contained in the carbon to carbon bonds of crop dry matter (,), (iv) partitioning of the accumulated crop dry matter to the economically important component of the crop (ρ), and (v) phenology and the integration of the biological processes across the life cycle of the crop, i.e., from t = planting date to t = harvest date. Two important aspects of Equation [1] should be noted. First, Equation [1] is a formalized concept, it cannot be used to mathematically estimate economic yield. Economic yield can be estimated, however, by deconstructing Equation [1] into quantifiable components (see below). Second, economic yield will be expressed in this course as plant dry matter (i.e., plant material at 0% moisture) because the quantity of plant dry matter is the best and most accurate estimate of the amount of radiant energy captured in crop production. Agricultural products in the commercial trade are always at a moisture content greater than 0%, for instance, fruits, vegetables, and flowers are traded in fresh weight (which may be up to 95% water), and grains/seeds are traded at an agreed­upon moisture percentage (for instance, corn is traded at 15.5% moisture content). When using commercial yield estimates to calculate biological efficiencies, one should always account for moisture content of the product. Biolological yield The biological yield is the total dry matter accumulated during the life cycle of a crop. In most cases biological yield includes only the above­ground components of the plant because it is very difficult to estimate the below­ground components. Exceptions are crops for which the economically important parts are the below­ground components (e.g., potato, sugar beet, and tulip). Unless explicitly stated otherwise, biological yield will include only the above­ground component parts. Biological yield or dry matter accumulation during Day t is the product of (i) incident solar radiation [Q(t)] , (ii) the fraction of incident solar radiation that is absorbed by the crop canopy [I A ‘ (t)] , and (iii) the efficiency of conversion of absorbed radiant energy into chemical energy contained in the carbon to carbon bonds of crop dry matter [,(t)] during Day t: Yb(t) = Q(t) × I A ' (t) × ,(t) Document1/8/19/2008 [2]
5 where Y b (t) is the biological yield at Day t in g m ­ 2 day ­1 , incident solar radiation [Q(t)] is in MJ m ­2 day ­1 , the fraction of radiation that is absorbed by the canopy [I A ‘ (t)] is dimensionless (%), and the efficiency of conversion [,(t)] is in g MJ ­1 . The fraction of incident solar radiation that is absorbed by the crop canopy (IA ' ) is a function of the leaf area index (Fig. 3). Leaf area index (LAI) is the ratio of the one­sided area of all leaves in the leaf canopy and the corresponding ground area. The leaf area index (LAI) of a hypothetical wheat leaf canopy and that of a hypothetical maize leaf canopy grown at Guelph is also depicted in Fig. 4. Fig. 3: Absorptance of incident As a rule of thumb (we will get more specific in radiation vs. leaf area index (LAI).
later lectures), canopy absorptance (I A ' ) is greater than 90% when LAI = 4. Mean daily incident solar radiation from 1 May and to 30 September at Guelph (ON) is depicted in Fig. 4. The average incident solar radiation (Q) at Guelph during this period is 20 MJ m ­2 day ­1 . Like Q and IA ' , the efficiency of the conversion of absorbed radiation into plant dry matter (,) also varies during the life cycle of the crop; , for an individual leaf in the canopy usually declines from a maximum at the time that the leaf attains its maximum size until maturity or earlier. The total dry matter accumulation (Y b ) at the end of the growing season can be estimated by summing the biological yield of each day during the growing season: harvest date Yb = ∑ [Q(t) × I A ' (t) × ,(t)] [3] planting date Fig. 4. Average daily incident solar radiation at Guelph, Ontario, and leaf area development of hypothetical wheat and maize canopies during the growing season. Document1/8/19/2008 6 Partitioning of the accumulated crop dry matter to the economically important crop components (ρ) The fraction of biological yield at maturity that is allocated to economically important parts of the crop (ρ) varies among crop species. If the whole plant is utilized (e.g., forages, turf grass, lettuce), ρ is 1. In cereal and grain­legume crops ρ at maturity is called harvest index. The harvest index of an average corn crop = 0.5, i.e., 50% of the above­ground dry matter at maturity is grain and 50% is composed of stems, leaves, cobs. The value of ρ is, to the best of my knowledge, not known for horticultural crops; when estimating ρ one should take care to express the economic product at 0% moisture. Partitioning of assimilates to economically important plant components usually occurs during specific phases of the life cycle. For instance, dry matter partitioning to the seed of grain or legume crops is 0 before flowering, increases rapidly after fertilization of the flowers, is fairly stable during most of the grain­filling period, and then levels off some time prior to the end of the crop's life cycle (i.e., physiological maturity). Partitioning during any day [ρ(t)] may be greater than the rate of crop dry matter accumulation during that day [Y b(t)], as remobilization of temporarily stored assimilates will make up for the difference between the demand of assimilates by the economically important plant components and the supply of assimilates by current photosynthesis by the crop canopy. Economic yield of a crop can be estimated by multiplying total dry matter at maturity (or total biological yield [Y b ] as quantified in Equation [3]) by the fraction of dry matter allocated to the economic component at maturity or harvest. Spatial vs. temporal integration Equations [1] and [3] illustrate the temporal integration of the five most important factors that determine crop yield: incident radiation, absorptance of incident radiation by the canopy, canopy photosynthetic efficiency, rate of partitioning of dry matter to economically important parts of the canopy, and phenology. In addition to the temporal integration of the canopy process across the life cycle, the rates of the processes in Eq. [2] at any time are themselves integrations of all biological processes across levels of organization, i.e., spatial integration of photosynthesis from the molecular level to the canopy level (see Fig. 1). Spatial integration spans from processes that occur at the molecular level in the chloroplast to processes to processes that occur at the plant community level (Fig. 1). A simple example of linking photosynthesis of single leaf with that of the photosynthesis of all leaves within a crop canopy may serve as an illustration of the complexity involved. Canopy photosynthesis (Pc) could be estimated from the photosynthesis of a single leaf (P L ): Pc = P L (mol CO 2 m ­2 leaf s ­1 ) x LAI (m 2 leaf m ­2 ground) = mol CO 2 m ­2 ground s ­1 However, Equation [5] is a very poor estimate of canopy photosynthesis. First, most of the
Document1/8/19/2008 7 [5] incident radiation is absorbed in the top layers of the canopy and little is absorbed in lower layers of the canopy. Second, leaves within a canopy differ substantially in their photosynthetic efficiency (e.g., old leaves vs. young leaves, sunlit leaves vs. shade­adapted leaves). Third, the photosynthesis­ light response curve is not linear (Fig. 5) and, consequently, the photosynthetic efficiency (i.e., photosynthesis per unit light energy) differs for leaves that receive different incident radiation. Fig. 5. Rate of leaf photosynthesis vs. incident radiation. The estimation of canopy photosynthesis will be discussed in Note that α at the leaf level is equivalent to ε at the detail in later lectures. canopy level.
Summary Crop physiology deals with plant production processes across a range of levels of organization. A level of organization includes both a time and a space component. Hence, crop physiology in the study of the temporal and spatial integration of plant processes.
· Appreciate that plant scientists study plants at different levels of organization. In crop physiology, information generated at lower level of organization (i.e., more basic sciences) is bridged with information generated at higher levels of organization (i.e., more applied sciences).
· The five most important factors that determine crop yield are incident solar radiation, absorptance of radiation by the canopy, the efficiency of conversion of solar energy into plant dry matter (photosynthesis), rate of dry matter partitioning to economically important crop components, and the phenology of the crop.
· Leaf area index (LAI) is plant leaf area (on one side of the leaf) per unit ground area. Actual and potential leaf photosynthesis varies greatly for leaves at different positions in the crop canopy. References Lee, E.A. and Tollenaar, M. 2007. Physiological basis of successful breeding strategies for maize grain yield. Crop Sci. 47:S202­S215. Document1/8/19/2008 8