High-yielding Environments Research Articles

Row Spacing and Seeding Rates for Soybean in Low and High Yielding Environments

Response of soybean [Glycine max (L.) Merr.] to changes in row spacing and seeding rate have been variable. Some researchers have reported grain yields to be higher with the use of narrow row spacings. Other investigators have found that wide row spacings provided grain yields equal to or greater than those obtained with narrow row spacings. This study was designed to determine the influence of environment on the optimum row spacing and seeding rate for soybean. Eleven field experiments were established in Kansas from 1991 to 1993. Four seeding rates in 1991 and five seeding rates in 1992 and 1993, ranging from 52 272 to 261 360 seeds/acre, were used in 8- and 30-in. rows. At high yielding sites, maximum grain yields were higher with 8-in. rows than with 30-in. rows. If moisture stress reduced grain yields, maximum yields were greater with 30-in. rows than with 8-in. rows. Response to changes in seeding rate varied between row spacings depending upon environmental conditions. Under high-yielding conditions, grain yields were maximized with 30-in. rows at approximately 115 000 seeds/acre, whereas seeding rates of 203 000 to 232 000 seeds/acre were required to maximize grain yields with 8-in. rows. Under conditions of limited soil moisture, grain yields were not affected by changing seeding rates. At sites with adequate soil moisture, mature plant heights increased as seeding rates increased. At moisture-deficient sites, plant height was not significantly affected by increased seeding rates. Research Question Recommendations for soybean row spacing and seeding rate are generally constant within a geographical area regardless of yield goal or yield potential. This research was designed to determine the influence of environment on the optimum row spacing and seeding rate for soybean. Literature Summary Many researchers have reported that soybeans planted in narrow row spacings produced higher yields than did soybeans planted in wider row spacings. Other investigators found little or no yield increase with the use of narrow row spacings. Some researchers have reported that soybeans planted in narrow rows had greater water-use efficiency than did soybeans planted in wider rows. Other investigators, however, found that, under conditions of severe water stress, water-use efficiency was greater with wide rows than with narrow rows. Yield response to changes in plant population usually have been small and often inconsistent. Generally, increasing plant populations has increased plant height at maturity. It has been reported that higher plant mortality occurred with wide rows than with narrow rows. Study Description This research was conducted from 1991 to 1993 at 11 dryland locations in Kansas. In 1991, four seeding rates ranging from 52 272 to 209 088 seeds/acre were used in 8- and 3041-1. rows. In 1992 and 1993, an additional seeding rate of 261 360 seeds/acre was added. Plant populations were determined 5 wk after planting. Plant lodging, mature plant heights, and grain yields were measured at maturity. Corsica was the cultivar used at eight environments, Resnik at two envirpnments, and Kunitz at one environment. Applied Question How did row spacing and seeding rate affect grain yields? The growing conditions at a site affected the yield response to changes in row spacing and seeding rate. Under high-yielding conditions, maximum grain yields were higher with 8-in. rows than with 30-in. rows (Fig. 1). If moisture stress limited grain yields, however, maximum yields were greater with 30-in. rows than with 8-in. rows. The response to increased seeding rates was dependent upon environmental conditions and row spacing. Under high-yielding conditions, yield response to increases in seeding rates changed depending upon row spacing. Grain yields were maximized with 30-in. rows at approximately 115 000 seeds/acre, whereas 203 000 to 232 000 seeds/acre were needed to maximize grain yields with 8-in. rows. If soil moisture was limiting, grain yields were not affected by increased seeding rates. Figure 1Open in figure viewerPowerPoint Soybean grain yields as affected by row spacing and seeding rate combined over site-years with high yield levels. How should yield potential affect recommendations for soybean row spacing and seeding rate? Seeding rate and row spacing recommendations should be adjusted depending upon expected environmental conditions. Under high-yielding conditions where moisture is adequate, soybeans planted in narrow rows generally yield higher than soybeans planted in 30-in. rows. If soybean growth is expected to be limited by moisture stress, however, grain yields may be higher with 30-in. rows. Seeding rates should be substantially higher with narrow rows than with wide rows, especially if high-yielding conditions are expected during the growing season.

Selecting stable and high-yielding sorghum cultivars for the semi-arid tropics

A sorghum breeding program was reactivated in 1981 and selected cultivars, along with local checks, were evaluated in two experiments in the sorghum growing region of northern Cameroon. Experiment 1 was conducted in the Extreme North Province where annual rainfall ranges from 450 to 850 mm. Experiment 2 was conducted in the North Province where annual rainfall exceeds 850 mm. The objective of the study was to select a high yield and high stability sorghum cultivar for each region. The cultivar's responses were investigated using two analyses: the adaptability analysis and the stability analysis. The former used the method of superiority measure, defined by distance mean square between the test cultivar and the maximum (the highest yield in the location), and the latter used type 4 stability parameter, defined by the years within location mean square averaged over all locations. The conceptual separation of adaptability and stability facilitated the cultivars assessment. The results showed that in exp. 1, three cultivars S–35, CS–54 and CS–61 had similar adaptability and stability, while in the exp. 2, S–34 was best in terms of yield but was unstable due to susceptibility to grain mold. In contrast, the second best cultivar CS–63 was poorer in the high-yielding environments but was more stable than S–34. Key words: Sorghum, genotype-environment interaction, adaptability, stability parameters

Genotype × environment interactions in progeny from a barley cross II. Variation in grain yield, yield components and dry matter production among lines with similar times to anthesis

Barley lines from the cross cv. Triumph × cv. Grimmett with similar time to anthesis were evaluated for grain yield and several attributes relating to growth and accumulation of grain yield in a range of environments. Significant variation existed for mean grain yield across environment, and for genotype×environment (GE) interaction. Principal component analysis was used in an attempt to identify systematic differences in response for grain yield across environments. The first component was positively correlated with grain yield in most environments, and most effectively accounted for this variation in the high-yielding environments. The second component was closely correlated with mean grain yield across the lower-yielding rainfed environments, although it was negatively correlated with grain yield at one irrigated environment. Line scores on the firsts component were closely related to grain number across the high-yielding irrigated environments, and weakly correlated with total dry matter and tiller number at anthesis in these environments. There was no correlation between line scores and TDM production following anthesis. This suggested that the ability of lines to partition assimilate to grains, perhaps limited by grain number, is of importance in determining relative yield potential under favourable growing conditions. Deliberate evaluation of lines under such conditions may be appropriate in the early stages of selection of progeny. Line scores on the second component were positively corelated with mean grain number, TDM at anthesis, TDM production after anthesis and single-grain mass, across the rainfed environments, A negative correlation between line scores on the second component and numbers of late-developing tillers in the rainfed environments suggested that production of such tillers may be detrimental to high grain yield in these environments. However, they may be useful in realising high grain yield in some irrigated environments.

Processes determining intercrop productivity and yields of component crops

This review examines how intercrop productivity is determined, by analysing several key physiological processes which affect yields of component crops. Availability of environmental resources to each of the component crops is important in determining combined intercrop productivity, and hence the analysis is based on capture of environmental resources and efficiency of conversion of captured resources into growth of harvested organs of the component crops. It is emphasized that the competitive abilities of component crops, which determine their biomass production and often yields, vary greatly according to growth environment, and hence cultural manipulation can adjust the balance of their yields. Intercrops are most productive when their component crops differ greatly in growth duration so that their maximum requirements for growth resources occur at different times. For high intercrop productivity, plants of the early-maturing component should grow with little interference from the late-maturing crop. The latter may be affected somewhat by the associated crop, but a long time period for further growth after the harvest of the first crop should ensure good recovery and full use of available resources. Compared with a sole crop, the reduced size of non-harvested organs of the late-maturing crop can result in improved assimilate partitioning to the harvested organ during the later part of the growth period and consequently a higher harvest index. Because of the differences in growth rhythm between component crops, there tends to be little interaction between relative performance of component crops and growth environment and hence productivity of this type of intercrop is often insensitive to management interventions. In contrast, when growth durations of component crops are similar the crops compete more intensely for available resources. Their relative performances can then be greatly affected by small changes in growth environment. ‘Additive’ intercrops of this type may nevertheless be productive, particularly where growth resources are more completely captured than in corresponding sole crops. However, if non-replenished growth resources are utilized too rapidly, the less-competitive component may suffer greatly. ‘Replacement’ intercrops of this type are not so productive in high-yielding environments. When the growth environment is not favourable however, their total lower plant populations compared to additive intercrops may allow yields of replacement intercrops to be less depressed. Where similar-duration crops are grown in variable environments, replacement intercrops may therefore be preferred due to their greater yield stability. Where a dominant crop uses available resources excessively and inefficiently, agronomic manipulation in favour of the usually suppressed component seems most likely to improve the productivity of the whole intercrop. Intercrop productivity depends on the genetic constitution of component crops, growth environment (atmospheric and soil) and agronomic manipulations of microenvironment. The interaction of these factors should be optimized so that the limiting resource is utilized most effectively in the intercrop. An understanding of the sharing of resources among component crops will help identify more appropriate agronomic manipulations and cultivars for intercrops.

Genotype‐by‐Environment Interactions of Barley in the Mediterranean Region

In the Mediterranean region, progress in selection for yield in harsh environments is hampered by large environmental variation between seasons and locations. This study analyzes the genotype‐by‐environment (GE) interaction of 36 two‐rowed genotypes of barley (Hordeum vulgare L.), grown in 14 environments in Syria and North Africa. It assesses the effect of growth type (winter or spring type) and heading date on the GE interaction and determines whether or not high‐yielding (HY) environments are representative of low‐yielding (LY) ones. Average grain yield per environment ranged from 7 to 513 g m−2. Genotypes and environments were classified by a cluster analysis and the interaction was analyzed with an additive main effects and multiplicative interaction model. Genotypes were classified into four clusters, related to their growth type and earliness of heading. Environments were clustered in a HY and LY group; this classification was related to seasonal rainfall and temperature. Medium‐early heading winter types had a positive interaction with LY environments and a negative interaction with HY environments, whereas late heading genotypes (spring and winter types) had the opposite interaction pattern. Early heading spring types had above‐average mean yields; the highest‐yielding among them tended to have a low interaction with environments. High‐yielding environments did not discriminate well between genotypes with high or low yields in LY environments, and may thus have limited value for yield selection for LY environments. For a breeding program aimed at improving yield in environments where favorable conditions are rare, selection for yield should be done in representative less‐favorable environments.

Agronomic Performance and Economic Value of High-Seed-Protein Soybean

The long-term trend in relative value of soybean (Glycine max (L.) Merr.] protein and oil is toward greater value of protein, thus furthering interests in the potential for increasing seed protein concentration in soybean. If a change in U.S. soybean breeding strategy for improving seed protein levels is required, it should be based on sound economic and biological principles. This research was conducted to: (i) develop high-protein soybean germplasm adapted to Mid-Atlantic latitudes; and (ii) compare agronomic performance, economic value, and stability of performance of resulting genotypes with that of normalprotein soybean cultivars. Fifty-two high-protein soybean lines were developed and evaluated in field tests in 1988 and 1989. Seven of the highest yielding high-protein lines, seven advanced commercial lines, and 'Essex' were evaluated in 11 field tests in 1990 [...]

Management practices to reduce lodging and maximize grain yield and protein content of fall-sown irrigated hard red spring wheat

Management practices which reduce lodging and increase grain protein concentration were studied in two short-statures wheat ( Triticum aestivum L.) cultivars in four high-yielding environments in northern California. Management factors included planting densities of 200, 300, and 400 seeds m −2 with the plant growth regulator ethephon [ (2-chloroethyl) phosphonic acid] (0.56 kg a.i. ha −1) to suppress lodging, and nitrogen topdressing (45 kg N ha −1) at anthesis in conjunction with an irrigation for increased grain protein content. The hard red spring wheat cultivars, Serra and Yolo, which differ in grain quality characteristics and relative susceptibility to lodging and some foliar diseases, were used. Ethephon did not provide complete lodging control, but reduced plant height, delayed the onset of severe lodging until later stages of grain-fill, and increased grain yield by 5–21% depending on cultivar and lodging severity. Height reduction due to ethephon was expressed as reduced length of the peduncle and upper internodes. Ethephon was more effective on Serra, the more lodging-susceptible cultivar, increasing grain yield of Serra by more than 1200 kg ha −1 in one experiment. In most cases, yield response to increased planting density was nonsignificant due to increased lodging at the higher densities and to compensation by yield components (increased spike number plant −1 and kernel number spike −1) at lower densities. Nitrogen topdressing at anthesis caused grain protein content to be increased by 1.6 to 7.4% with differences depending largely on the level of N fertilizer supplied prior to anthesis and residual N fertility from previous crops. Although increases in grain protein content due to N topdressing at anthesis were small, grain protein, and thus grain quality were increased without increasing lodging. Management practices which include reduced planting density, ethephon application, and N topdressing at anthesis followed by irrigation, should be considered in wheat production environments where lodging and low grain protein concentration are expected to occur.

Soil and Plant Factors Associated with Sudden Death Syndrome of Soybean

Sudden death syndrome (SDS) of soybean (Glycine max [L.] Merr.) is a soilborne disease of increasing importance in high-yield environments. This study was conducted to determine which combinations of soil fertility parameters and soybean cyst nematode (Heterodera glycines Ichinoe) (SCN) second stage juvenile (J2) population levels were associated with SDS disease severity. Also, the effect of SDS disease severity on leaf nutrient content and on soybean yield and seed germination were determined. These studies were conducted at the Pine Tree Station, in Colt, on a Crowley milt loam (fine, montmorillonitic, thermic Typic Albaqualfs) over 3 yr with the soybean cultivar Lee 74 [...]

Yield stability of cowpea cultivars in rice-based cropping systems: Experimentation and simulation

There is potential in cultivating cowpeas ( Vigna unguiculata (L.) Walp.) in rice-based cropping systems in the humid tropics as a source of proteins for humans, forage for ruminants, and for improvement of soil fertility. Seasonal and yearly variability is, however, a major constraint. A statistical stability model and a mechanistic simulation model were used to quantify yield variability of early and medium maturity groups of cowpea cultivars in pre- and post-rice environments at Los Baños, Philippines. Four field experiments, with 24 cultivars in each experiment, were conducted in pre- and post-rice environments, to determine the response of the cultivars to varying moisture and to water table depth regimes, and a stability analysis was performed across the regimes using a statistical model. In the post-rice environment, irrespective of moisture and water table depth regimes, the medium maturing cultivars tended to outyield early maturing cultivars, whereas in the pre-rice environment, early maturity demonstrated a distinct yield advantage. The statistical stability model indicated that medium maturing cultivars performed well in high-yielding environments, whereas in low-yielding environments their yields were comparable with those of early maturing types. However, results of the statistical stability model are limited because of the short time series of basic data. To broaden the analysis, a simulation model of the cowpea crop was calibrated and validated for its performance. Measured and simulated dry weights of crop parts (leaves, stems and pods) and soil moisture contents at 10-cm soil depths throughout the growing season indicated satisfactory performance of the simulation model. Long-term simulation results using the validated model indicate that TVX1948-012F (medium maturity) performs betters (800–2250 kg ha −1) than IT82D-889 (early maturity) (430–1620 kg ha −1) with a fluctuating shallow water table in the post-rice environment, whereas IT82D-889 is superior (80–1150 kg ha −1) to TV1948-012F (30–1150 kg ha −1) in the pre-rice environment. Yields are highest and least variable for the 15 January planting in the post-rice environment, and for the 15 April planting in the pre-rice environment.

Increasing the Yield Plateau in Rice and the Role of Global Climate Change

To cope with estimated population growth in Asia, attainable rice yield potential must increase in the irrigated lowlands. At odds with this goal is the fact that yield potential of released high yielding rice varieties has remained constant since the release of IR8 in the late 1960s, although yield per day increased as a result of shorter growth duration and host plant resistance was improved. For example, highest rice yields of IR72 (released in 1987) were 6 and 9.5tha-1, in the 1991 wet season and the 1992 dry season, respectively, in a tropical environment with good agronomic management. These yields are comparable but no higher, than the highest yields attained by IR8 in the same environment more than 20 years ago. Detailed growth analysis from these recent studies allowed us to improve an eco-physiological model for rice growth. Subsequent simulations demonstrated accurate prediction of wet and dry season rice yield. The model was then used to evaluate the effects of global climate change as expected by the year 2020. Changes in temperature and atmospheric CO2 had relatively small effects on simulated rice growth and yield compared with (1) the impact of crop management practices in high-yielding environments and (2) genetic improvement that could further increase yield potential. Varieties with a longer grain filling duration will be needed to increase the yield plateau and to reverse negative effects of increased temperature.

Evaluation of Methods for Quantification of Drought Tolerance in Wheat

Quantification of the drought tolerance of wheat (Triticum spp.) genotypes is of interest to physiologists investigating traits associated with adaptation to dry conditions and to breeders developing cultivars for dry areas. The objective of this research was to assess drought tolerance in terms of minimal depression of yield in dry compared with favorable environments (drought susceptibility index, S) with a superiority measure (P) based on the sum across environments of the mean‐squared differences between genotype yield and the maximum yield in each environment. Twenty‐five hexaploid (T. aestivum L.) and 16 tetraploid (T. turgidum L. var. durum) wheat genotypes were grown in separate experiments under dry and irrigated conditions on a Swinton loam (Aridic Haploboroll) soil. There was year‐to‐year variation in S within genotypes and changes in genotype ranking within years. No single cause for this variability was identified. The S index did not differentiate between potentially drought‐tolerant genotypes and those that had low yield potential from other causes. P was correlated with mean yield in both the hexaploid (−0.96**) and tetraploid (−0.94**) groups (both significant at P = 0.01). However, P was strongly influenced by high yield environments; this was alleviated by standardization of the yield data. Although P appears to be a possible method to quantify average superiority of genotypes across locations, its suitability requires further assessment. There seems to be no simple technique to quantify drought tolerance that would assist physiologists in choosing genotypes in which to evaluate putative drought tolerance mechanisms.

Relationship between barley grain yield measured in low- and high-yielding environments

The paper addresses the general question of identifying the optimum environment for selection in plant breeding programs for low input agricultural systems. After defining low-yielding and high-yielding environments based on the average grain yield of large numbers of barley genotypes in different cropping seasons, we examined: 1) the phenotypic relationships between the highest yielding genotypes in low- and high-yielding environments, and 2) the genetic correlation coefficients between grain yield in low- and high-yielding environments. The results indicate that the alleles controlling high grain yield in low-yielding conditions are at least partially different from those controlling high grain yield in high-yielding conditions. Therefore, selection in high-yielding environments is expected to produce a negative response or no response in low-yielding environments. This may explain why crop varieties bred under high-yielding conditions failed to have an impact in low-yielding agricultural systems. The results may be extrapolated to systems where environmental concern suggests a reduction of inputs by raising the question of whether crop breeding programs based on selection under high inputs are likely to generate the right type of germplasm for an environmentally friendly agriculture.

Evaluation of the performance of sweet potato genotypes by joint regression analysis

SUMMARYTwo experiments, each involving a set of six sweet potato clones, the first set developed in sites differing in altitude, and the second in sites differing in soil type, were done at three locations in 4 years in Cameroon. Data obtained were subjected to analyses of variance to determine the presence of genotype × environment (G × E) interactions, and to joint regression analyses to measure the performance of clones across environments. The first experiment produced higher yields and contained more stable clones than the second. In both experiments, mean yields were almost twice as high in 1984 (21·1 t/ha) as in each of the other years (c. 11·0 t/ha), and highest at Nyombe (18·0 t/ha). In Expt 1, the G × E interaction mainly concerned interaction with location, whereas in Expt 2 it concerned interaction with years.Clones 1611 (Expt 1) and 048 (Expt 2) yielded above average and gave linear regressions significantly above unity (b> 1·0) for most traits, indicating specific adaptation to high-yielding environments and hence below average stability. Clones 1112, 1639 and TIbl (Expt I) yielded above average and had regression slopes equal to unity (b= 1·0), indicating average stability and thus general adaptability. Clones TIb2 (Expt 1) and 1487 (Expt 2) produced below average yields (b< 1·0), indicating specific adaptation to low-yielding environments. Since sweet potato is grown mainly for human consumption in Cameroon, a preferred clone must have stable marketable yields. Only clones 1112, TIbl and 1639 could be considered desirable for release to growers.

Corn Yield Response to Varied Producer Controlled Factors and Weather in High Yield Environments

Much of the corn (Zea mays L.) yield increases in the past five decades can be attributed to the identification and adjustment of controllable factors that limit production. This process must continue if we are to meet the food requirements of the future. The objectives of these experiments were to determine what combination of the producer controlled variables (e.g., N, P, and K fertilization, plant density, row spacing, hybrid, and timing of N application) would give maximum yields under the prevailing climatic conditions in the western Corn Belt. Eight field experiments were conducted in eastern and central Iowa from 1982 through 1984. Treatments varied with location but the treatment ranges were as follows: plant density—20 000 to 36 000 plants/acre; row spacing—20 and 30 in.; N rate—60 to 333 lb/acre; fertilizer P rate—0 to 99 lb/acre; fertilizer K rate—0 to 249 lb/acre; N timing—preplant vs. split (preplant and side dress); plus four different hybrids. Weather had a moderating effect on all but one experiment by either delaying planting or providing severe moisture stress. Mean experiment grain yields ranged from 103 to 178 bu/acre, with the combination of controlled variables giving maximum yields varying with site-year. Grain yields did not respond to fertilizer N rates above the initial rate. Soil P levels were sufficient to produce maximum yields with or without added fertilizer P, and in 1983, added P resulted in a negative yield response. Grain yields responded to fertilizer K rates of 166 and 249 lb/acre in 1982 on plots with soil tests averaging 67 and 91 ppm K, respectively. The rate of 166 lb/acre resulted in grain yield increases in 1984 on plots with soil tests averaging 85 ppm K. The lowest plant densitities, which ranged from 20 000 to 26 000 plants/acre, gave maximum yields in all experiments. The row-spacing variable resulted in a grain yield difference only in 1982 when 20-in. rows showed an advantage over 30-in. rows. Hybrid had a significant effect on yield in all but one experiment. These experiments demonstrate the increased risk to the producer who is striving for high yields but who cannot control or predict the weather.

CHARACTERS ASSOCIATED WITH YIELD STABILITY OF IRISH POTATO GENOTYPES IN GEORGIA

Three experiments, each with 100 potato (Solanum tuberosum L.) genotypes, were conducted using triple lattice designs from 1988-1989. The use of lattice designs did not improve the efficiency of these experiments over randomized complete blocks. The phenotypic stability of tuber yields of 91 genotypes, common to three experiments, was measured by regression of genotype means over environmental means. Regression coefficients indicated that 60 days after planting (DAP), genotypes adapted to high yielding environments (b > 1), had significantly higher tubers/plant, leaf area index, and yield/plant, as compared to genotypes suited to low-yielding environments. At final harvest, approximately 100 DAP, genotypes specifically adapted to high yielding environments had significantly higher tubers/plant and yield/plant than genotypes adapted to low yielding environments (b < 1). Green Mountain, Kennebec, and Norchip were adapted to high-yielding environments whereas La Chipper, Ontario, and Superior were adapted to low-yielding environments.

Predicting the relative effectiveness of direct versus indirect selection for oat yield in three types of stress environments

In breeding crop varieties for stress environments, it must be decided whether to select directly, in the presence of stress, or indirectly, in a nonstress environment. The relative effectiveness of these two strategies depends upon the genetic correlation (r g ) between yield in stress and nonstress environments and upon heritability in each. These parameters were estimated for grain yield of 116 random oat lines grown in nonstress, P-deficient, N-deficient, and late-planted environments. Estimates of r g between yield in nonstress and yield in P-deficient, N-deficient, and late-planted environments were 0.52±0.24, 1.08±0.16, and 0.06±0.24, respectively. No consistent relationship between heritability and environment mean yield was observed. Direct selection in the presence of stress was predicted to be superior for yield in low-P and late-planted environments, but indirect selection in high-N environments was predicted to be as effective as direct selection in producing yield gain in low-N environments. These results confirm that neither high-yield environments nor environments in which the heritability of yield is maximized are necessarily optimum when the goal is to maximize yield gain in stress environments.

Response of Two Maize Populations to Reciprocal Recurrent Selection in a High-yield Environment

A selection program using reciprocal recurrent selection procedures in maize (Zea mays L.) was developed. Intra-and interpopulation selection procedures were used for two maize populations BS10 and RSSSC. Intrapopulation selection procedures included phenotypic mass selection for multiple leaf and multiple stalk-rot disease resistance and S1 family selection for grain yield in a high-yield environment. Interpopulation improvement involved selection of testcrosses of S1 family×inbred tester in a high-yield environment. Evaluations of populations per Se, population crosses and populations×testers for response to three cycles of selection for grain yield were conducted at four environments. Evaluation of populations per se and population crosses for response to three cycles of selection for multiple leaf disease and multiple stalk-rot resistance was conducted at disease nursery in 1985. The results indicate that selection response was consistent among environments. Gain from selection was satisfactory in populations per Se, population crosses and populations x testers for grain yield, multiple leaf disease resistance and multiple stalk-rot resistance. Linear response to three cycles of selection for grain yield for BS10, RSSSC, BS10×RSSSC, BS10×B37, and RSSSC×B79 were: 0.95, 0.69, 0.65, 0.65 and 0.24 Mg/ha/cycle, respectively. The rates of gain for grain yield obtained in the present study compare favorably with published reports. Linear response for stalk lodging for BS1O, BS10×RSSSC and BS10×B37 were: -9.0, -5.4 and -3.5%/cycle, respectively. All populations per Se, population crosses and populations×testers showed significant increase in penetrometer reading. Increase in plant height and ear height were observed for RSSSC, BS10×RSSSC and RSSSC×B79. Population BS10 showed an increase in 300-kernel weight and kernel number per ear, and a decrease in ear number per 100 plants. Population RSSSC only showed an increase in 300-kernel weight. Three cycles of selection slightly increased grain moisture in BS10 and BS10×B37. This result indicates the procedures of selection in a high-yield environment are beneficial in improving grain yield, multiple disease resistance and stalk lodging resistance in maize populations per se and their hybrids.

Optimizing Row Spacing and Seeding Rate for Soft Red Winter Wheat

AbstractIntensive management practices, such as high fertility, fungicides, and plant growth regulators, have substantially increased grain yield of soft red winter wheat (Triticum aestivum L.) in the northeastern and mid‐Atlantic USA. Our objective was to determine the effects of row spacing and seeding rate on grain yield and yield components of several cultivars in a high‐yield environment in the southeastern USA. Five cultivars, Coker 916, Coker 983, Hunter, Florida 301, and Florida 302, were grown during 1985 and 1986 on a Greenville sandy clay loam (clayey, kaolinitic, thermic Rhodic Paleudult) in row spacings of 0.10 and 0.20 m at seeding rates of 288 and 576 seeds m−2. Management practices included a high rate of fertilizer‐N (176 kg ha−1) in multiple applications, fungicide and plant growth regulator applications, irrigation, and adequate levels of P, K, S, and Mg. Grain yields ranged from 3.9 to 6.3 Mg ha−1 and averaged 5.0 Mg ha−1. Narrow row spacing (0.10 m) yielded 0.4 Mg ha−1 or about 8% greater than the 0.20‐m spacing. Grain yield was not influenced by seeding rates when averaged over years. Number of spikes per square meter was the yield component most affected by row spacing and seeding rate. Neither the cultivar × row spacing nor cultivar × seeding rate interaction for grain yield was significant. Therefore, new cultivars should react similarly to those studied here.

STABILITY ANALYSIS IN SHORT DURATION VARIETIES OF RICE (Oryza sativa L.)

Ten short duration varieties of rice (Oryza sativa L.) evaluated under three environ- ments showed genotype-environment interaction for days to 50 per cent flowering, plant height, number of ear-bearing tillers, panicle length, number of filled grains per ear, spikelet fertility, harvest index and plot yield. Although both the components of geno- type-environment interaction namely, linear and non-linear, contributed to the total geno- type-environment interaction, preponderance of linear component was there. It was found that IR 50 was the widely adapted genotype over environments. Co 41 faired well under low yield environment and the genotypes ADT 36 and ACM 2 faired well under high yield environment.

Source of variation in yield in international Mungbean Trials

Analysis of variance and two-way classification analysis were used to identify the source and nature of variation in yield among orthogonal subsets of genotypes and environments included in the 7th and 8th, and 9th and 10th International Mungbean Nursery Trials. Most of the variation was environmental (70–80%) with 17–21% due to genotype X environment interaction, and less than 3% being variation among genotypes. High-yielding environments were identified as those where water supply to plants was good, and where climatic conditions favoured an extended crop duration and avoidance of severe disease epidemics. No plant attribute consistently characterised high-yielding genotypes although those in the highest-yielding groups were usually significantly taller than the mean in those environments where their yield advantage was expressed. They also had moderate to good resistance to one or more diseases. There was evidence that yield increases due to recent improved cultivars exceeded 10%.