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AGROCLIMATOLOGY

Quantification of Grain Yield Response to Soil Depth in Soybean, Maize, Sunflower, and Wheat

^a Universidad de Mar del Plata-INTA Balcarce, CC 276, Balcarce 7620, Argentina
^b CREA Tandil, Bolívar 710, Tandil 7000, Argentina

Corresponding author (pcalvino{at}infovia.com.ar)

Received for publication May 8, 2000.

	ABSTRACT

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Risk analysis to identify the more profitable or less risky crops in areas with shallow soil requires quantification of yield responses to physical constraints to root penetration. Grain yield, shoot biomass, and harvest index (HI) were measured in commercial fields of indeterminate soybean (Glycine max L. Merr.), maize (Zea mays L.), sunflower (Helianthus annuus L.), and wheat (Triticum aestivum L.) grown on Typic Argiudols and Petrocalcic Paleudols. At crop maturity, shoots were sampled along transects (approximately 200 m) with soil depths between 0.35 and >1 m as determined by petrocalcic horizon depth. In all four species, shallow soil reduced shoot biomass and grain yield but did not affect HI in wheat. Harvest index was most affected by shallow soil in maize. Seasonal water deficit [maximum - actual evapotranspiration (ET)] accounted for 43 to 90% of the variation in yield. Average water use efficiency (WUE) was wheat, 14.5; maize, 11.7; soybean, 8.9; and sunflower, 7.5 kg grain ha^-1 mm^-1 ET. In relation to crops on the deepest soil, yield decline per centimeter reduction in soil depth was 0.41% in wheat, 0.45% in soybean, 0.54% in sunflower, and 0.76% in maize. This ranking of grain yield response to shallow soil was mostly accounted for by (i) cropping season (autumn to late spring for wheat vs. spring to autumn for row crops), (ii) timing of the most critical period for grain yield determination (later in soybean than in sunflower and maize), and (iii) plant features related to vegetative and reproductive plasticity, including growth habit.

Abbreviations: ET, actual evapotranspiration • ET_max, maximum evapotranspiration • HI, harvest index • PAW, plant available soil water • WUE, water use efficiency

	INTRODUCTION

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SHORTAGE of water and/or nutrients can restrict crop yield in shallow soils. Physical restriction of root elongation can also reduce plant growth irrespective of water and nutrient supply (McConnaughay and Bazzaz, 1991). Isolation of the individual effect of drought, nutrient deficiency, and mechanical impedance is not straightforward (Masle and Passioura, 1987; Passioura and Gardner, 1990), and crops in shallow soil are often exposed to the combined effects of all of these factors. Furthermore, responses of dryland crops to soil depth are strongly influenced by the interaction between crop phenology and the amount and seasonal pattern of rain (Calviño and Sadras, 1999). Interaction among water, nutrient, and mechanical stresses makes it difficult to predict yield response to soil depth; therefore, it is important to measure this response. In the southeastern Pampas of Argentina, the region of focus in this study, soil depth and rain amount are major constraints to crop yield (Calviño and Sadras, 1999; Mercau et al., 2001).

Comparative studies indicated that mechanical impedance has the same limiting effect on root elongation for a series of plant species including cotton (Gossypium hirsutum L.), maize, wheat, and groundnut (Arachis hypogaea L.) (Bennie, 1996). This conclusion, however, is based on the comparison of relative root elongation, whereas some evidence indicates substantial variation among species in the absolute rate of root elongation. Absolute rates (measured at 25°C) ranked sunflower > maize > soybean (Andrade et al., 2000). Leaf expansion, one of the main determinants of light interception and crop growth, is more sensitive to water and nutrient deficit in dicots than in monocots (Radin, 1983; Sadras and Milroy, 1996). This simple consideration of only two processes, root and leaf elongation, indicates that ranking crop species in terms of their response to shallow soil cannot be easily derived from our knowledge of crop responses to the multiple stresses involved. Nonetheless, in temperate climates with a more or less uniform seasonal distribution of rain, greater susceptibility to soil shallowness could be expected in summer crops than in winter crops owing to differences in evaporative demand. Comparative studies involving a range of biophysical stresses highlight the high susceptibility of maize in relation to sunflower and soybean (Connor and Sadras, 1992; Vega et al., 2000). As a working hypothesis, it is therefore proposed that response to soil depth in the region investigated should be least in wheat, greatest in maize, and intermediate in sunflower and soybean.

The aim of this study was to quantify grain yield responses to physical constraints to root penetration in a series of rainfed crops including indeterminate soybean, maize, sunflower, and wheat. The plots were established in commercial fields, and the analysis emphasized the interaction between soil depth, as determined by petrocalcic horizon depth, and rain.

	MATERIALS AND METHODS

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Site
Rainfed crops were grown on five farms around Tandil in the southeastern Pampas (37°S). These farms belong to AACREA (Asociación Argentina de Consorcios Regionales de Experimentación Agrícola), an organization in which professional consultants advise groups of growers whose farms are grouped according to agroecological and management similarities (Tables 1 and 2). No tillage is widespread in the region (Table 1), and it was a feature common to all crops in this study. Main soils were Typic Argiudols and Petrocalcic Paleudols (both illitic, fine, thermic) with an average 6.2% organic matter and 1.5 mm available water holding capacity cm^-1 soil (Travasso and Suero, 1994). Farms alternate 8 to 15 yr cropping and 3 yr pasture; the most common crop rotations involving one crop per year are maize–wheat–soybean or sunflower–wheat. Acreage allocated to double cropping (wheat and soybean) has steadily increased in the last 5 yr. Average annual rain is 940 mm with a slight spring–summer bias, i.e., 64% of rain falls between October and March.

Data Analyses
Analysis of variance was used to test the effect of site (farm), soil depth, and the interaction between depth and site on grain yield, shoot biomass, and HI. Soybean data from Farms C and D were partially analyzed in a previous publication (Calviño and Sadras, 1999). To compare crops, relative grain yield was calculated as the ratio between actual yield and the highest yield of each crop at each site. Linear and nonlinear models were fitted to describe the relationship between relative grain yield and soil depth; soil depth = 1.2 m was assumed for the deepest soil (Calviño, unpublished data, 1999).

Owing to the similarity in soil and crop management among the farms under study, we assumed that rain, and hence water availability, were the main factors underlying grain yield response to both site and site x soil depth interaction (Table 3). To test this assumption, we investigated the relationship between grain yield and crop water deficit, calculated as the difference between ET and maximum evapotranspiration (ET_max) (Hillel, 1990). Maximum evapotranspiration was calculated as the product between reference ET (Penman, 1948) and phenology-dependent crop coefficients (Doorenbos and Pruit, 1977) that were locally tested (Della Maggiora et al., 2000). Published upper and lower limits were used for the calculation of relative plant available soil water (PAW) (Travasso and Suero, 1994). Actual evapotranspiration was assumed to be equal to ET_max when PAW > 0.5 and to decline linearly when PAW was between 0 and 0.5 (Sadras and Milroy, 1996). Changes in soil water content (up to the maximum soil depth determined by petrocalcic horizon depth) were calculated as a function of initial soil water, rain, and ET. Long fallow (6 mo) and large amount of residues (90% ground cover) ensured a relatively high and uniform initial PAW, which was assumed to be 0.8 (Calviño, unpublished data, 1999). Measurements in wheat confirmed this value. Runoff was calculated as the amount of water above the upper limit of soil water content and was particularly important in shallow soils. Meteorological data for ET_max calculations were from a single weather station close to the field sites, except for rain that was measured at each farm. The water budget outlined above was fully described by Della Maggiora et al. (2000), who also tested the method with local cultivars in the environment under study. Their tests and the consistent association between grain yield and water deficit in the current study both indicate that this water budget provides estimates of ET with sufficient accuracy for the farm level requirement of our work.

	RESULTS

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Soybean
Soil depth, site, and depth x site interaction all affected soybean grain yield (Fig. 1). The response to soil depth was greatest at Site C where grain yield doubled when soil depth increased from shallowest to deepest. Yield response to increasing soil depth was less pronounced at Sites D and E. Harvest index was affected by both site and site x depth interaction (Fig. 1). Shoot biomass at maturity was greatest at Site C and increased with soil depth at all three sites; interaction between soil depth and site was significant, however (Fig. 1). Across sites and soil depths, shoot biomass accounted for 83% of the variation in yield.

View larger version (31K): [in this window] [in a new window]   Fig. 1. Soybean grain yield, harvest index (HI), and shoot biomass as a function of soil depth in commercial fields at three sites. Error bars are two standard errors of sample mean and are not plotted when smaller than symbol

View larger version (32K): [in this window] [in a new window]   Fig. 2. Maize grain yield, harvest index (HI), and shoot biomass as a function of soil depth in commercial fields at three sites. Error bars are two standard errors of sample mean and are not plotted when smaller than symbol

View larger version (32K): [in this window] [in a new window]   Fig. 3. Sunflower grain yield, harvest index (HI), and shoot biomass as a function of soil depth in commercial fields at three sites. Error bars are two standard errors of sample mean and are not plotted when smaller than symbol

View larger version (31K): [in this window] [in a new window]   Fig. 4. Wheat grain yield, harvest index (HI), and shoot biomass as a function of soil depth in commercial fields. Yield was measured at three sites whereas HI and biomass were only measured at two sites. Error bars are two standard errors of sample mean and are not plotted when smaller than symbol

View larger version (13K): [in this window] [in a new window]   Fig. 5. Relative grain yield of wheat, soybean, sunflower, and maize as a function of soil depth. P < 0.0005 for all four models fitted to the data

View larger version (21K): [in this window] [in a new window]   Fig. 6. Relationship between seasonal water deficit and grain yield of soybean, maize, sunflower, and wheat grown in commercial fields. Lines are fitted regressions. Correlation coefficients are shown for the linear regressions between yield and water deficit before (Pre), during (CP), and after (Post) the most critical period for yield determination and for the seasonal water deficit (Season). The most critical periods were defined as follows: Pod and grain set for soybean, i.e., between stages R3 and R5 (Calviño and Sadras, 1999); 40 d bracketing silking in maize (Tollenaar and Dwyer, 1999); 60 d bracketing anthesis in sunflower (Cantagallo et al., 1997); and 30 d before anthesis in wheat (Fischer, 1985). Significance levels are *, 0.05; **, 0.01; and ***, 0.001

where r² = 0.33 and P < 0.05. For soybean,

where r² = 0.49 and P < 0.05.

	DISCUSSION

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On-Farm Research
Worldwide, growers need to fine-tune the management of their crops owing to increasing pressure from declining commodity prices and environmental problems. Economic risk analysis to identify the more profitable or less risky crops in areas with shallow soil requires quantification of grain yield response to soil depth, which was the aim of this study. In comparison with experimental plots, on-farm research provides more realistic estimates of crop yield responses. Working in growers' fields also accelerates the delivery of research outcomes to industry. Economic risk analysis derived from related on-farm research in our region indicated that substantial improvement in soybean profitability can be achieved by considering two broad soil categories within fields, i.e., deep (>0.7 m) and shallow (<0.7 m) soils (Calviño and Sadras, 1999; Sadras et al., 1999). In response to these findings, growers are reshaping their paddocks and devising rotations to account for soil depth. This response involved, 1 yr after the communication of our results, approximately 25000 ha in the southeastern Pampas.

Yield Response to Soil Depth
Determinate soybean or short-season maize hybrids may show different responses to the ones found in this study. Notwithstanding intraspecific variation, comparison of crop species is a powerful research tool, provided major biological and agronomic features are considered to ensure conclusions hold for a wide range of cultivars (Vega et al., 2000; Sadras et al., 2000).

Some crop responses were consistent with our working hypothesis, including the identification of maize as the most responsive crop to soil depth and wheat as the least (Fig. 5). Two main factors account for the contrasting susceptibility of these species to shallow soil: plant plasticity, which is greater in wheat than in maize, and cropping season, i.e., autumn to late spring for wheat vs. spring to autumn for maize. The extreme susceptibility of maize to environmental stresses around flowering is well known (Tollenaar and Dwyer, 1999). In our study, this was reflected in (i) the dramatic response of HI to both soil depth and the interaction between soil depth and site (Fig. 2) and in (ii) the close association between water deficit around silking and crop yield (r² = 0.71, P < 0.001; Fig. 6). In contrast, wheat was the only crop in which HI was unaffected by soil depth. It was also the only crop in which grain yield was unaffected by the interaction between soil depth and site (Fig. 4). Tillering contributes to the ability of wheat to adjust to varying environmental conditions, in contrast to the reduced vegetative and reproductive plasticity of maize (Vega et al., 2000). Wheat underwent less severe water deficits because of lower evaporative demand and despite less rain than summer crops (Table 3). Lower evaporative demand also accounts for the large WUE of wheat compared with summer crops (Sinclair et al., 1984).

Other crop responses were contrary to our expectation. In deep soil, where drought is associated with shortage of rain and/or high evaporative demand, grain yield reduction in sunflower is usually less than in soybean (Cox and Jolliff, 1986). This is, in part, related to the ability of sunflower to absorb water from deeper soil layers than soybean (Connor and Sadras, 1992; Cox and Jolliff, 1986; Hattendorf et al., 1988). Conversely, our study showed that indeterminate soybean was more tolerant than sunflower to the stresses associated with shallow soil. Plant plasticity and timing of the most critical period for yield determination, in relation to evaporative demand and rain, accounted for the difference in susceptibility to shallow soil among summer crops. The prolonged flowering of indeterminate crops permits greater compensation for flower loss and seed abortion than in determinate species, which are more vulnerable to isolated periods of stress around flowering (Loomis and Connor, 1996). In shallow soil, where potential root depth is largely irrelevant, more important features of the root system likely include the precision in foraging for soil resources (Grime, 1998) and speed in generating rain roots in response to rain (Nobel, 1988; Palta and Nobel, 1989). Compared with dicots, monocots have low precision in foraging for soil resources (Grime, 1998); this could further contribute to the greater susceptibility of maize to shallow soil compared with soybean and sunflower. The ranking of grain yield loss in response to soil depth among summer crops, i.e., soybean < sunflower < maize, agrees with the ranking of decreasing plant plasticity determined by Vega et al. (2000). Importantly, the most critical period for grain yield determination in soybean occurred later in the season (Feb.) than in maize and sunflower (Dec.–Jan.). In this period, soybean had less than half the rain of maize and sunflower but 50 to 60% lower water deficit (Table 3).

Grain yield response to drought depends on the timing, intensity, and duration of the water deficit. In annual species of determinate growth habit, including maize, sunflower, and wheat, the greatest susceptibility to stress often corresponds to a time window of a few weeks around anthesis (Cantagallo et al., 1997; Fischer, 1985; Tollenaar and Dwyer, 1999). In indeterminate soybean, the greatest susceptibility to stress commonly coincides with later reproductive stages (Calviño and Sadras, 1999). Consistently, we found significant associations between grain yield and water deficit during the most critical period for grain yield in all four crops. Our study also showed, however, that under very stressful conditions derived from shallow soil, critical periods were not so neatly defined because water deficit during early vegetative growth and grain fill also contributed to substantial grain yield loss. Board and Harville (1998) highlighted the importance of stresses during the vegetative period of soybean if crop dry matter and light interception by R1 are insufficient for optimal crop growth during reproductive stages.

In summary, we demonstrated a marked difference in grain yield response to soil depth among crop species and a strong interaction between soil depth and rain. The ranking of tolerance to shallow soil, wheat soybean > sunflower > maize, was mostly accounted for by (i) cropping season (autumn–late spring for wheat vs. spring–autumn for row crops), (ii) timing of the most critical period for yield determination (later in soybean than in sunflower and maize), and (iii) plant features related to vegetative and reproductive plasticity.

	ACKNOWLEDGMENTS

 
We thank Miguel Redolatti and Juan P. Monzon for excellent technical assistance and members of CREA Tandil for access to their farms: Aleluya, El Parque, Instituto Arana, Lauraleufú, and San Lorenzo. V.O. Sadras is a member of CONICET, the Research Council of Argentina.

	REFERENCES

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION REFERENCES

 

• Andrade, F.H., L.A.N. Aguirrezábal, and R.H. Rizzalli. 2000. Crecimiento y rendimiento comparados. p. 61–96. In F.H. Andrade and V.O. Sadras (ed.) Bases para el manejo del maíz, el girasol y la soja. INTA-Universidad de Mar del Plata, Balcarce, Argentina.
• Bennie, A.T.P. 1996. Growth and mechanical impedance. p. 453–470. In Y. Waisel, A. Eshel, and U. Kafkafi (ed.) Plant roots: The hidden half. Marcel Dekker, New York.
• Board, J.E., and B.G. Harville. 1998. Late-planted soybean yield response to reproductive source/sink stress. Crop Sci. 38:763–771.[Abstract/Free Full Text]
• Calviño, P.A., and V.O. Sadras. 1999. Interannual variation in soybean yield: Interaction among rainfall, soil depth, and crop management. Field Crops Res. 63:237–246.
• Cantagallo, J.E., C.A. Chimenti, and A.J. Hall. 1997. Number of seeds per unit area in sunflower correlates well with a photothermal quotient. Crop Sci. 37:1780–1786.[Abstract/Free Full Text]
• Connor, D.J., and V.O. Sadras. 1992. Physiology of yield expression in sunflower. Field Crops Res. 30:333–389.
• Cox, W.J., and G.D. Jolliff. 1986. Growth and yield of sunflower and soybean under soil water deficits. Agron. J. 78:226–230.[Abstract/Free Full Text]
• Della Maggiora, A.I., J.M. Gardiol, and A.I. Irigoyen. 2000. Requerimientos hídricos. p. 155–171. In F.H. Andrade and V.O. Sadras (ed.) Bases para el manejo del maíz, el girasol y la soja. INTA-Universidad de Mar del Plata, Balcarce, Argentina.
• Doorenbos, J., and W.O. Pruit. 1977. Crop water requirements. FAO Irrigation and Drainage Paper 24. FAO, Rome.
• Fehr, W.R., C.E. Caviness, D.T. Burmood, and J.S. Pennington. 1971. Stage development descriptions for soybeans, Glycine max (L.) Merrill. Crop Sci. 11:929–931.[Abstract/Free Full Text]
• Fischer, R.A. 1985. Number of kernels in wheat crops and the influence of solar radiation and temperature. J. Agric. Sci. 105:447–461.
• Grime, J.P. 1998. Annual Report, 1996–1998. Unit of Comparative Plant Ecology. The Univ. of Sheffield, England.
• Hattendorf, M.J., M.S. Redelfs, B. Amos, L.R. Stone, and R.E.J. Gwin. 1988. Comparative water use characteristics of six row crops. Agron. J. 80:80–85.[Abstract/Free Full Text]
• Hillel, D. 1990. Role of irrigation in agricultural systems. p. 5–31. In B.A. Stewart and D.R. Nielsen (ed.) Irrigation of agricultural crops. Agron. Monogr. 30. ASA, CSSA, and SSSA, Madison, WI.
• Loomis, R.S., and D.J. Connor. 1996. Crop Ecology: Productivity and Management in Agricultural Systems. Cambridge Univ. Press, New York.
• Masle, J., and J.B. Passioura. 1987. The effect of soil strength on the growth of young wheat plants. Aust. J. Plant Physiol. 14:643–656.[Web of Science]
• McConnaughay, K.D.M., and F.A. Bazzaz. 1991. Is physical space a soil resource? Ecology 72:94–103.[Web of Science]
• Mercau, J.L., V.O. Sadras, E.H. Satorre, C. Messina, C. Balbi, M. Uribelarrea, and A.J. Hall. 2001. On-farm assessment of regional and seasonal variation in sunflower yield in Argentina. Agric. Syst. 67:83–103.[Web of Science]
• Nobel, P.S. 1988. Environmental biology of Agaves and Cacti. Cambridge Univ. Press, New York.
• Palta, J.A., and P.S. Nobel. 1989. Influences of water status, temperature, and root age on daily patterns of root respiration for two cactus species. Ann. Bot. 63:651–662.[Abstract/Free Full Text]
• Passioura, J.B., and P.A. Gardner. 1990. Control of leaf expansion in wheat seedlings growing in drying soil. Aust. J. Plant Physiol. 17:149–157.
• Penman, H.L. 1948. Natural evaporation from open water, bare soil, and grass. Proc. R. Soc. London., Ser. A. 193:120–145.[Abstract/Free Full Text]
• Radin, J.W. 1983. Control of plant growth by nitrogen: Differences between cereals and broadleaf species. Plant Cell Environ. 6:65–68.
• Sadras, V.O., P.A. Calviño, and A. Bustamante. 1999. Variación interanual en el rendimiento de soja: III. Análisis de riesgo económico 1o Congreso de Soja del Mercosur. Asociación Argentina de la Soja, Rosario, Argentina.
• Sadras, V.O., L. Echarte, and F.H. Andrade. 2000. Profiles of leaf senescence during reproductive growth of sunflower and maize. Ann. Bot. 85:187–195.[Abstract/Free Full Text]
• Sadras, V.O., and S.P. Milroy. 1996. Soil-water thresholds for the responses of leaf expansion and gas exchange. Field Crops Res. 47:253–266.
• Sinclair, T., C. Tanner, and J. Bennett. 1984. Water-use efficiency in crop production. Bioscience 34:36–40.
• Tollenaar, M., and L.M. Dwyer. 1999. Physiology of maize. p. 169–204. In D.L. Smith and C. Hammel (ed.) Crop yield: Physiology and processes. Springer-Verlag, Berlin, Germany.
• Travasso, M.I., and E.E. Suero. 1994. Estimación de la capacidad de almacenaje de agua en suelos del sudeste bonaerense. Boletín Técnico 125. Estación Experimental Agropecuaria Balcarce, Argentina.
• Uhart, S.A., and H.E. Echeverría. 2000. Diagnóstico de la fertilización. p. 235–268. In F.H. Andrade and V.O. Sadras (ed.) Bases para el manejo del maíz, el girasol y la soja. INTA-Universidad de Mar del Plata, Balcarce, Argentina.
• Vega, C.R.C., V.O. Sadras, F.H. Andrade, and S.A. Uhart. 2000. Reproductive allometry in soybean, maize, and sunflower. Ann. Bot. 85:461–468.[Abstract/Free Full Text]

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This Article Abstract Figures Only Full Text (PDF) Free Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Similar articles in Web of Science Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Web of Science (24) Citing Articles via Google Scholar Google Scholar Articles by Sadras, V. O. Articles by Calviño, P. A. Search for Related Content PubMed Articles by Sadras, V. O. Articles by Calviño, P. A. Agricola Articles by Sadras, V. O. Articles by Calviño, P. A. Related Collections Agroclimatology Soybean Maize Wheat Sunflower