Abstract
The objective of this paper is to illustrate uses of the CROPGRO-peanut model for hypothesizing and simulating action of genetic traits likely to improve peanut yield under water-limited conditions. Literature suggests there is potential to improve peanut yield under water limitation, based on increased water extraction (rooting depth or altered root distribution), increased water-use-efficiency (WUE), and improved harvest index (HI). Previous, and new, crop model simulations presented here, support these hypotheses, but also highlight feedbacks, such as the problem that increased WUE may be associated with increased specific leaf weight (SLW) which creates a self-limiting effect via decreased light interception.

Media Summary:

Key Words:

Crop simulation, Arachis hypogaea L, rooting traits, water uptake, water-use-efficiency, harvest index

Introduction and Literature Review:

Production and yield potential of peanut (Arachis hypogaea L.) in many parts of the world are limited by water deficit, caused either by short rainy season as in West Africa and India, or by sporadic and limiting rainfall in the USA, Australia, and South America. Genetic improvement in yield of peanut under water-limiting conditions has been a target of plant breeders. In West Africa’s Sahelian region, certain cultivars such as C55-437 and C59-127 were shown to perform better than other cultivars under low rainfall conditions, yet produced equivalent yields under higher rainfall seasons (Bockelee-Morvan et al. 1974). In Australia, the cultivars Tifton-8 and Streeton have been reported to produce better than other cultivars under the low and sporadic rainfall environments of that peanut-producing region. Past genetic improvement in peanut yield under water-limitation has often followed a trial-and-error approach. Can we take a more pro-active approach, with the assistance of crop growth simulation modeling?

The premise of this paper is that crop growth simulation models may facilitate taking a systematic approach to hypothesize the consequences of improvement in genetic traits for yield under water-limiting environments. Boote and Jones (1986) attempted to begin such an effort with variation in rooting, life cycle, and vegetative traits for a short-season cultivar, using an early version of the PNUTGRO model, and 21 years of Florida weather data. Some of these efforts will be extended in the present paper, using a more recent CROPGRO-peanut model version (V3.5, Boote et al. 1998). Williams and Boote (1995) used a 1994 version of the CROPGRO-peanut model to hypothesize how variation in the ratio of intercellular CO₂ (Ci) to ambient CO₂ (Ca) linked to genetic variation in specific leaf weight, could improve WUE and yield of peanut under water-limited conditions. Using the CROPGRO-soybean model, Boote et al. (2003) evaluated hypothesized root, shoot, and life cycle traits that were shown to benefit soybean yield potential under water limitation.

Simulation models are particularly helpful toward taking a systematic approach to yield potential under water-limitation. Passioura (1994) defined a simple starting framework in which he described three ways to increase yield as a function of: 1) the amount of water taken up (as with deeper rooting or more prolific rooting patterns), 2) the water-use-efficiency, and 3) harvest index (HI). We will look at these three aspects, relative to available literature and then with model simulations.

In the first mechanism for drought tolerance (increased water uptake), we need to consider effects of more rapid rate of rooting depth increase as well as altered rooting distribution to improve plant water extraction and minimize water stress during drying cycles. Increased partitioning to roots can be either constitutive (all the time) or adaptive (in response to onset of water deficit).

A second mechanism is via increased water-use-efficiency which allows more biomass (not necessarily more pod yield) to be produced with a given amount of water. If the water-use-efficiency is associated with partial stomatal closure, there may be subsequent conservation of water to later more critical phases. Farquhar et al. (1982) suggested, based on theory, that WUE and ¹³C isotope discrimination ratio should be correlated, given their common linkage to the ratio of Ci/Ca ratio. This theory was confirmed for peanut by the discovery of negative correlations between WUE and ¹³C isotope discrimination (Δ¹³C) among peanut genotypes (Hubick et al. 1986; Wright et al. 1988). These authors reported negative associations between specific leaf weight (SLW) and Δ¹³C, and also between HI and Δ¹³C (Nagaswara Rao et al. 1993; Wright et al. 1994). Basically, greater WUE by a cultivar such as Tifton-8 was achieved by increased specific leaf weight, which had small effects on the WUE via the decrease in Ci/Ca ratio to give steeper CO₂ gradient into the leaf despite the same water vapor gradient from the leaf. Boote et al. (1997) conducted simulations with the CROPGRO-peanut model to illustrate that this mechanism in Tifton 8 also was associated with, and indeed, required a concurrent increased allocation of new assimilate to leaf (and less to stem), in order to prevent reduction in light interception with the decreased leaf area. Williams and Boote (1995), used the CROPGRO-peanut model version with hourly energy balance, to test the assumption of Ci/Ca linked to SLW, to show the full range of possible advantage of increased WUE with increased SLW. In their exercise, the Ci/Ca was assumed to vary from 0.9 at “zero” SLW, decreasing to 0.5 at SLW of 90 g m^-2, while light-saturated rate of leaf photosynthesis increased linearly with increasing SLW. Their simulations illustrated that the benefit of high SLW was rather small, with an optimum SLW that varied between 25 to 60 g m^-2, in part because higher SLW to improve WUE also concurrently reduced the crop’s leaf area index (LAI), causing reduced light capture. Genetic and management ways around this problem would include the genetic accompaniment of increased partitioning to leaf as Tifton-8 does, or by increasing the sowing density and reducing row spacing.

A third mechanism of drought tolerance, following the framework above, would be to increase harvest index. As we can see with simulation examples, this is not so easy because increased HI may be difficult to achieve, particularly if the season-length is limited. In this situation, decrease in HI is itself caused by the water deficit or heat stress. Indeed, for the Sahelian regions, yield potential under water deficit has been attributed to better heat tolerance that improves reproductive success (improved pollination) during periods of heat stress that typically occur during water-limiting periods (Greenberg et al. 1992; Prasad et al. 2001; Craufurd et al. 2003). This mechanism would likely be associated with improved HI compared to other cultivars, at least during water-limited trials. By contrast, the mechanisms of increased water extraction or increased WUE would produce (mimic) increased total dry matter accumulation and probably also increased seed yield, with minimal effect on HI.

The objective of this paper was to conduct a simulation evaluation of genetic improvement hypothesized to increase peanut yield under water limitation in USA, where full-season runner type cultivars with high levels of technology are grown under a long rainy season.

Materials and Methods:

The CROPGRO-peanut model (DSSAT V3.5, 1998 release) was used in this study. Weather data from Gainesville, FL. USA (25 years) was used to evaluate yield response over multiple weather years. Soil characterizations were available from previous experiments and soil water measurements for these sites. Genetic traits were modified, using a combination of the cultivar, ecotype, and species input files used with the CROPGRO-peanut model. Changes were made one-at-a-time, unless specifically indicated to be in combination. The seed yield response was evaluated as a percentage change, compared to a standard genotype run.

Results and Discussion:

Simulations illustrate that increasing the rate of root depth progression increased seed yield by 2.6% for a 10% faster rate of depth progression (Table 1). Increasing the partitioning to root in a constitutive mode (meaning all the time) had very little benefit, even for this relatively long-season cultivar, because it cost in terms of reduced LAI and light capture. On the other hand, an inducible shift in partitioning (done with the current ATOP function, value of 0.8 versus 0.0) was quite valuable, increasing yield 6.1%. The model already has this feature, meaning that it increasingly shifts dry matter to root when the plant begins to experience water deficit. The literature is clear that this feature is already present in most plants.

Table 1.Simulated peanut yield in response to varying genetic traits, for a long-season Florunner cultivar, averaged over 25 years of weather at Gainesville, Florida.

*EB - Comparison with hourly energy balance (EB) option for evapotranspiration and foliage temperature. All other simulations used daily Priestley-Taylor evapotranspiration option.

Increasing SLW 10% (with linkage to LAI and photosynthesis, but not to stomatal conductance), increased yield only 0.20% with a 0.32% decrease in evapotranspiration (ET) caused by the slightly lower LAI. If partitioning to leaf was concurrently increased, then yield was increased 1.11%. A version of the model, with hourly energy balance (EB) for ET and foliage temperature was used to test effects of increased SLW and linkage to both photosynthesis and stomatal conductance (via lower Ci/Ca) as done by Williams and Boote (1995). This option gave similar yield and slightly lower ET compared to the daily Priestley-Taylor ET option. Increasing SLW 10% decreased yield 0.78% and ET 0.85% because of lower LAI and slightly lower photosynthesis. However, increasing the partitioning to leaf by 4% (to recover LAI), led to 1.17% increase in yield, but 0.52% decrease in ET.

Modifying genetic traits such as the maximum fraction assimilate allocation to pods (XFRUIT) will influence yield in rainfed and irrigated environments. In this rainfed environment for a long-season cultivar, yield was increased about 2% for increasing XFRUIT from 0.94 (default) to 0.98, or decreased about 2% for decreasing it from 0.94 to 0.90.

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