Soybean Yield Potential—A Genetic and Physiological Perspective

Abstract

Given a limit to crop yield improvement, Waggoner (1994) observed that a logistic model was more suitable Soybean [Glycine max (L.) Merr.] yields in the USA have risen for crop yield vs. time data 22.6 kg ha Ϫ1 yr Ϫ1 from 1924 to 1997, but in the last quarter century (1972-1997) have risen 40% faster, 31.4 kg ha Ϫ1 yr Ϫ1 . This upwardtrend in on-farm yield is fueled by rapid producer adoption of technologies emerging from agricultural research. Published estimates of the The logistic response curve is sigmoid because the expoannual gain in yield attributable to genetic improvement averaged nential change in yield (Y) over time (T) is modulated about 15 kg ha Ϫ1 yr Ϫ1 prior to the 1980s, but is now averaging about by the degree to which present yield differs from its 30 kg ha Ϫ1 yr Ϫ1 in both the public and proprietary sectors. Periodic limit (K). The inflection point (Tm) separates the posiadvances in agronomic technology, and a relentless rise in atmospheric tive and negative exponential phases of the sigmoid.CO 2 (currently 1.5 LL Ϫ1 yr Ϫ1 ), also contribute to the upward trend Wagoner (1994) used average U.S. corn (Zea mays L.) in on-farm yield. In Nebraska, irrigated yield averages 800 kg ha Ϫ1 yields from 1940 to 1992, and set K to 21 Mg ha Ϫ1 (the more than rainfed yield, and is improving at a 40% faster annual rate highest grain yield recorded in U.S. corn production), (35.1 vs. 24.9 kg ha Ϫ1 ). About 36% of the annual variation in the to show that U.S. corn yield was rising at a logistic rate irrigated-rainfed yield difference is attributable to annual variation in absolute rainfed yield. Inadequate water obviously limits absolute of 3.6% yr Ϫ1 . crop yield, but also seems to be an obstacle in terms of the rate of Attaining the theoretical yield maximum on each U.S. yield improvement. Several physiological traits changed during six farm each year for each crop would unquestionably redecades of cultivar releases in Ontario that led to a genetic gain in yield quire optimization of every yield-affecting biotic or abiof about 0.5% yr Ϫ1 . Changes in some traits were obvious (improved otic factor in every production environment. The degree lodging), but more subtle in others (greater N 2 -fixation, greater stressto which such multiple-factor optimization is possible, tolerance). In terms of photosynthate supplied to sinks across a wide or economically feasible, will determine what fraction range of environments, recent cultivars seem to be superior to obsolete of the crop's yield potential that can actually be realized ones. To sustain and enhance soybean yield improvement in the future, on the average U.S. farm on a year-to-year basis. In any technological innovation must be continually injected into the agriculevent, mitigation of the yield-limiting factors will require tural enterprise.

Drivers of spatial and temporal variation in soybean yield and irrigation requirements in the western US Corn Belt

“…Variation in mean attainable yield across region-years was positively associated with radiation and Q during July and August (Supplementary Table 3) and negatively associated with sowing date (r = 0.50, P < 0.001). The region-year values of attainable yield derived in the present study (range: 4.2 to 5.4 Mg ha −1 ) were below the attainable yield of 6.4 Mg ha −1 value estimated by Specht et al (1999) to be a 'functional' yield benchmark for a large population of U.S. soybean producers. Onfarm yields ca.…”

“…When grown under optimal conditions, crop growth rate is determined only by solar radiation, temperature, atmospheric CO 2 and genetic traits that govern length of growing period, light interception by the crop canopy, and its conversion to biomass. Average on-farm soybean yield in NE is well below maximum yields >6 Mg ha −1 measured in experimental plots or contest-winning fields across the US Corn Belt, which might suggest a large gap between actual and potential yields (Specht et al, 1999). However, no explicit quantification of yield gap has been performed for soybean in the US Corn Belt or other regions of the world.…”

A high seed yield and associated attributes of dry matter production achieved by recent Japanese soybean cultivars

“…These results suggested that soybean's yield potential in Japan, which represents the yield in the absence of limitations caused by water and nutrient availability, diseases, and weeds, (Evans & Fischer, 1999), is potentially high if these and other constraints can be removed. The potential yield of soybean was estimated to reach 800 g m −2 (Specht et al, 1999). Very high soybean yields, with values close to the estimated potential yield [795 g m RUE were 1.40 g MJ −1 (Shiraiwa et al, 1994), 1.26 g MJ −1 (Nakaseko & Goto, 1983), and 1.15 g MJ −1 (Sinclair & Shiraiwa, 1993).…”

“…In Sachiyutaka, RUE was 25% higher in D18 than in D12. Specht et al (1999) estimated that soybean's yield potential could reach 800 g m −2 if the estimated seed yield limit for corn was 2250 g m −2 and the ratio of corn yield to soybean yield was 2.8. In fact, very high soybean yields that approach or exceed this estimated potential yield have been reported: 795 g m −2 (Van Roekel & Purcell, 2014) and 920 g m −2 (Isoda et al, 2006).…”

Correlation between Yielding Ability and Dry Matter Productivity during Initial Seed Filling Stage in Various Soybean Genotypes

“…These studies suggested the importance of dry matter productivity before the beginning of seed fi lling. On the other hand, it has been reported that the cultivar difference in seed yield was apparently associated with differences in dry matter production during seed fi lling when the number of pods is primarily determined (Shiraiwa and Hashikawa, 1995;Specht et al, 1999;Kumudini et al, 2001). Thus the critical stage for yield determination in soybean has not been specifi ed, nor has the existence of such a common stage been confi rmed.…”