Explain Yield Differences Research Articles

Site-Specific Mehlich 3-P Recommendations for Florida’s Sandy Soils

ABSTRACT In 2010, the Mehlich 3 (M3) soil extractant replaced Mehlich 1 (M1) as the official soil test for Florida. While a linear expression was initially established to reasonably estimate M3-P values based on M1-P recommendations for acid-mineral soils in Florida, Florida farmers have been skeptical of revised P recommendations and reported lower yields when following them, suggesting that adjustments to recommended P fertilizer application rates may be needed. This study evaluated different extraction protocols to estimate bioavailable P in major agricultural mineral soil orders, predominant in Florida. Extractions were conducted on 420 surface samples for M1- and M3-P and on 123 samples for FeO (iron oxide impregnated strip), Haney H3A, and anion exchange resin membrane (AERM). Our findings suggest that the current P fertilizer recommendations, which rely on the M1-P to M3-P linear relationship, may underestimate agronomic thresholds for both low and high P levels. The variability in P extraction by FeO compared to M3 appears to be site-specific and could explain yield differences observed with M3 testing. While promising, our revised P recommendations need further validation through additional yield response analyses across various locations to improve the accuracy of predicting crop yields based on soil P values.

Improving Rice Yield by Promoting Pre-anathesis Growth in Subtropical Environments

Rice yield is greatly influenced by climatic factors and soil fertility in the location where it is grown, but information about the individual effects of climatic factors and soil fertility variables is difficult to distinguish because they are often not independent. The objective of this study was to demonstrate the effect of climatic factors on grain yield when soil fertility was not a confounding factor for explaining yield differences across two subtropical environments. Field and pot experiments with six rice cultivars were conducted in Deyang and Luzhou, Sichuan Province, China. We found that rice yield was higher in Deyang than in Luzhou by 7.0–16.8% for field experiments and by 57.6–87.4% for pot experiments. Biomass production rather than harvest index was responsible for the yield difference. Maximum and minimum temperatures and cumulative solar radiation (CSR) before heading (HD) were higher in Deyang than in Luzhou, whereas after HD, maximum and minimum temperatures were lower in Deyang than in Luzhou. Rice yield was more closely related to maximum and minimum temperatures and CSR before HD than to these parameters after HD. There was no difference in yield between soil types from Deyang and Luzhou within the same ecological condition. Thus, the yield difference between the two subtropical environments was mainly caused by the difference in climatic factors. The differences in biomass between Deyang and Luzhou were mostly due to variations in pre-heading crop growth rate (pre-CGR) and pre-heading radiation use efficiency (pre-RUE), which were induced by varying temperatures and CSR. We concluded that lower yield in Luzhou was associated with lower pre-CGR and pre-RUE. Our study suggests that developing rice cultivars with high pre-CGR and pre-RUE through a breeding program may also be a feasible approach to achieve high yield in subtropical environments.

Cropping Practices and Effects on Soil Nutrient Adequacy Levels and Cassava Yield of Smallholder Farmers in Northern Zambia

Cassava is a staple food and a major source of income for many smallholder farmers. However, its yields are less than 6 t ha−1 compared to a potential yield of 20–25 t ha−1 in Zambia. Understanding cropping practices and constraints in cassava production systems is imperative for sustainable intensification. Therefore, a survey of 40 households each with three fields of cassava at 12, 24, and 36 months after planting (MAP) was conducted. Analyzed soil data, leaf area index (LAI), intercepted photosynthetically active radiation, and management practices from 120 fields were collected and subjected to descriptive statistics. To explain yield differences within the same cassava growth stage group, the data were grouped into low- and high-yield categories using the median, before applying a nonparametric test for one independent sample. Stepwise regressions were performed on each growth stage and the whole dataset to determine factors affecting tuber yield. Cassava intercropping and monocropping systems were the main cropping systems for the 12 and 24–36 MAP, respectively. Cassava yields declined by 209 and 633 kg ha−1 at 12 and 36 MAP due to soil nutrient depletion for each year of cultivation until field abandonment at 8–9 years. Fresh cassava yields ranged from 3.51–8.51, 13.52–25.84, and 16.92–30.98 t ha−1 at 12, 24, and 36 MAP, respectively. For every one unit increment in exchangeable K (cmol (+)/kg soil), cassava yield increased by 435, 268, and 406 kg ha−1 at 12, 24, and 36 MAP, respectively. One unit increment of magnesium (cmol (+)/kg soil) gave the highest yield increase of 525 kg ha−1 at 24 MAP. The low levels of soil organic carbon explained the deficient nitrogen in cassava fields, which limits the LAI growth and consequently reduced intercepted radiation and low yields. The effect of exchangeable K on growth was limited by the moderate availability of Mg and low N, thus the need for balanced fertilizer regimes.

In-field lucerne root morphology traits over time in relation to forage yield, plant density, and root disease under two cutting managements

Changes in lucerne (Medicago sativa L.) root morphology concurrent with forage growth have been little studied in multi-year field experiments with lucerne stands though they could provide explanations for differences in performance among tested treatments. Our objectives were: (i) to compare lucerne root trait development under three- and four-cut managements over a 4-year period, and (ii) to investigate relationships among root traits, and between root traits and lucerne varieties, cutting frequencies, root sampling periods, lucerne dry matter yield and evidence of root disease incidence and plant density, using multivariate methods. Treatments were a factorial combination of 15 lucerne cultivars with managements of three and four cuts per year. Each spring and autumn, plants were evaluated for root morphology traits and scored for root disease. Root morphology traits were strongly modified by sampling period and plant density, which together explained over 40% of total variability. The development over time was positively associated with an increase in tap-root diameter (TD) and root mass accumulation, whereas root density determined changes in root branching traits. The four-cut management reduced TD and root branching in association with lower forage yield. Variety effect was significant but contributed only 2.8% of total variability. Root branching showed a positive correlation with forage yield through a large increase of TD for branch-rooted plants, but more intensive root branching was associated with a significantly higher disease score than in tap-rooted plants. For optimization of evaluation of root traits, we proposed a root potential index (RPI) integrating TD and plant density. This RPI showed a closer relation to yield than TD, plant density or root biomass alone, in the arable cultivation layer. Our results reveal that monitoring of root morphology is an effective tool to characterize the production potential of lucerne as a sown field crop, and may explain yield differences among the various experimental treatments. Understanding these relationships between root morphology and lucerne stand performance can help in breeding selection as well as effective lucerne stand evaluation.

Simulation of genotype-by-environment interactions on irrigated soybean yields in the U.S. Midsouth

Dynamic crop models that incorporate the effect of environmental variables can potentially explain yield differences associated with location, year, planting date, and cultivars with different growing cycles. Soybean (Glycine max (L.) Mer.) cultivar coefficients for the DSSAT-CROPGRO model were calibrated from two growing seasons (2012−2013) comprising 58 irrigated environments (site×year×planting date combinations) for cultivars within maturity groups (MGs) 3 to 6 using end of season data (yield, seed weight, and seed oil and protein concentration) and previously calibrated phenology coefficients. Model accuracy after calibration of cultivar coefficients by MG (cultivars averaged within a MG) was similar compared to cultivar-specific coefficients. During the subsequent growing season in 2014 (33 environments), the model efficiency (ME) for predicting yield was 0.40, with a root mean square error (RMSE) of 571kgha−1. The model was less efficient predicting seed number and seed weight (ME=0.06 and −0.06, respectively) than yield. The model was able to simulate differences in seed oil concentration across environments and MGs (ME=0.52), but not protein concentration (ME=−0.25). The analysis of yield stability had similar slopes for the observed and predicted yield regressions against an observed environmental index (EI) that were only dependent on the MG. Simulated yields were significantly different from the observed when EI>0, but yield differences in the highest yielding environments were still relatively small (245 to 608kgha−1). The results indicate an overall robust model performance in capturing G×E responses with coefficients calibrated by MG.

High transpiration efficiency increases pod yield under intermittent drought in dry and hot atmospheric conditions but less so under wetter and cooler conditions in groundnut (Arachis hypogaea (L.))

Water limitation is a major yield limiting factor in groundnut and transpiration efficiency (TE) is considered the main target for improvement, but TE being difficult to measure it has mostly been screened with surrogates. The paper re-explore the contribution of TE to grain yield in peanut by using a novel experimental approach in which TE is measured gravimetrically throughout the crop life cycle, in addition to measurement of TE surrogates. Experimentation was carried out with the groundnut reference collection (n=288), across seasons varying for the evaporative demand (vapor pressure deficit, VPD) and across both fully irrigated and intermittent water stress conditions. There was large genotypic variation for TE under water stress in both low and high VPD season but the range was larger (5-fold) in the high- than in the low-VPD season (2-fold). Under water stress in both seasons, yield was closely related to the harvest index (HI) while TE related directly to yield only in the high VPD season. After discounting the direct HI effect on yield, TE explained a large portion of the remaining yield variations in both seasons, although marginally in the low VPD season. By contrast, the total water extracted from the soil profile, which varied between genotypes, did not relate directly to pod yield and neither to the yield residuals unexplained by HI. Surrogates for TE (specific leaf area, SLA, and SPAD chlorophyll meter readings, SCMR) never showed any significant correlation to TE measurements. Therefore, TE is an important factor explaining yield differences in groundnut under high VPD environments, suggesting that stomatal regulation under high VPD, rather than high photosynthetic rate as proposed earlier, may have a key role to play in the large TE differences found, which open new opportunities to breed improved groundnut for high VPD.

Soybean Maturity Group Choices for Maximizing Radiation Interception across Planting Dates in the Midsouth United States

Cumulative interception of photosynthetically active radiation (CIPAR) is a key factor affecting soybean [Glycine max (L.) Merr.] yield. Under well‐watered conditions, differences in CIPAR across planting dates, maturity groups (MGs) and row spacing in the US Midsouth could partially explain yield differences. Irrigated experiments were conducted for 2 yr at three locations in Arkansas with four planting dates and 16 cultivars (MG 3–6) using a narrow (0.46–0.48 m) and a twin‐row spacing (0.19–0.20 m twin rows on 0.96 m beds) with a seeding density of 35 plants m−2. The fraction of radiation intercepted (FRI) from emergence to beginning seedfill (or complete canopy closure) was well defined for each row spacing as a sigmoidal relationship with cumulative thermal time. A bilinear relationship between CIPAR and relative yield explained 46% of the yield variation. Relative yield increased with CIPAR, reached a maximum at 687 MJ m−2 and then declined. Simulations estimated the FRI and CIPAR for a range of planting dates, MG choices, narrow and twin‐row spacings, and two locations with 30‐yr of historical weather data. Simulations identified scenarios where management of row spacing and MGs avoid low FRI during flowering and at the start of seedfill. Simulations also identified management scenarios that ensure sufficient CIPAR to obtain 95% of maximum yields. Late MGs provided greater CIPAR compared with earlier MGs, but yield decreased at high values of CIPAR emphasizing the importance of understanding mechanisms underlying the yield response to CIPAR across planting dates and MGs.

Using satellite remote sensing to understand maize yield gaps in the North China Plain

Substantial gaps have been reported between the average farmer’s maize yield and yield potential in China, especially the North China Plain (NCP). This maize yield gap as identified by previous studies indicates large opportunities for raising yield by improving agronomy. Agronomic factors are either transient or persistent. Transient factors, which explain yield differences depending on unpredictable weather conditions, can have significantly different optimums from one year to another. While those transient factors are difficult to improve without reliable forecasts, persistent factors influence yield more consistently and therefore represent the best near-term targets for shrinking yield gaps. In this study, multi-year satellite images are used to quantify field-scale maize yield variation in Quzhou County of NCP, and this variation is then analyzed to determine the role of soil type and persistent management factors in explaining yield gaps. Results indicate that (i) remote sensing can provide reasonably reliable estimates of maize yields in this region; (ii) soil type has a clear effect on maize yields, and one that interacts strongly with growing season rainfall amounts; and (iii) on average roughly 20% of yield differences that appear within any one year are related to factors that persist in other years. Overall, the study presents a generalizable methodology of assessing yield gap as well as the proportion arising from persistent factors using satellite data. Our results suggest that the majority of yield gap is dominated by transient factors, and shrinking this gap may require high quality forecasts to make informed optimal management decisions.

Does Pollen ‘Neighborhood’ Affect Berry Yield In Lowbush Blueberry (Vaccinium Angustifolium Ait)?

Proximally growing individuals of wild, lowbush blueberry (Vaccinium angustifolium Ait.) vary widely in yield despite being grown under conditions in which environmental heterogeneity is minimized by cultivation practices. We recently established that the relative self-fertility of the bearing plant is a significant predictor of its outcross yield. Further, although the species has historically been characterized as largely self-infertile, we, and others, have documented large variation in this trait among individuals within fields, and, thus, relative self-fertility stands as a partial explanation of yield variation in addition to other genetic factors, such as significant general and specific combining abilities. Here, we extend our scope by experimentally addressing whether pollen neighborhood affects yield. Lowbush blueberry is not sown, rather individuals have colonized fields by natural processes. Commercial fields of lowbush are generally pollinated by rented honey bees, which tend to pollinate nearby flowers. Our hypothesis is that clones may have become situated in differentially suitable pollen environments, at least partly explaining yield differences. We identified two high and two low natural yielders from each of two managed fields and collected pollen mixes from five donors surrounding each (n = 8). Under field conditions, each recipient received four pollination treatments including its' own neighborhood and the other three donor neighborhoods within the same field. Results showed that one of the low producers in each field had significantly higher yields when pollinated by any but their own neighborhood, thus substantiating our hypothesis that pollen neighborhood has an effect on yield.

Genotypic Responses of Cowpea (Vigna unguiculata) to Sub-Optimal Phosphorus Supply in Alfsols of Western Kenya: A Comparative Analysis of Legumes

Western parts of Kenya are characterized by acid soils with phosphorus (P) deficiency and aluminum (Al) phytotoxicity. Reports indicate a declining trend in yields of legumes such as cowpeas. Though legumes can fix N, starter phosphorus need to be supplied for better yields and more often plants develop adaptive strategies for better P acquisition; probably through increased Al tolerance by carboxylates exudation, improved nodulation as a result of high P and better root development. Present study examined mutual relationship between P and nodulation in explaining yield dif ferences between Cowpea (Vigna unguiculata) varieties: Elanda (ELn, high yielding) and Inzeku (INz; moderate yielding), Ground nut (Arachis hypogea)-GN and Bambara nuts (Vigna subterrenea (Verdc) - BBN with proven P efficiency and Bean (Phaseolus vulgaris L) varieties Rosecoco (RCC) and Edwin (ED); low P efficient formed basis for comparison. The experiment was conducted at Masinde Muliro University field station from April 2009 and experimental design was CRBD having split plot with P as main plots (+P; or -P), whereas GN, BBN, ELn, INz, RCC and ED legumes were randomized within the P treatments. Legume genotypes were replicated four times. There were no differences in shoot biomass with +P and -P (INz), but ELn showed higher shoot DM with +P as compared with -P (significant p<0.05). Similar trends were replicated with nodulation with P supply. Shoot DM and nodulation were positively correlated for ELn (r2=0.99; +P and r2=0.68; -P) but not INz. Correlations were negative for beans and performance of BBN with +P and -P showed trends similar with Inz genotype. Sub-optimal P supply with concomitant enhancing nodulation in INz could not explain genotypic differences in yields, since high yielding BBN lacked this trait with additional P. Factors like high proton concentration and Al saturation need to be assessed and likely an interaction between P and Al through enhanced exudation of carboxylates may give more insights to cowpea genotypic dif ferences.

A Modeling Approach to Simulate Effects of Intercropping and Interspecific Competition in Arable Crops

Interspecific competition between species influences their individual growth and performance. Neighborhood effects become especially important in intercropping systems, and modeling approaches could be a useful tool to simulate plant growth under different environmental conditions to help identify appropriate combinations of different crops while managing competition. This study gives an overview of different competition models and their underlying modeling approaches. To model intercropping in terms of neighbouring effects in the context of field boundary cultivation, a new model approach was developed and integrated into the DSSAT model. The results indicate the possibility of simulating general competition and beneficial effects due to different incoming solar radiation and soil temperature in a winter wheat/maize intercropping system. Considering more than the competition factors is important, that is, sunlight, due to changed solar radiation alone not explaining yield differences in all cases. For example, intercropped maize could compensate low radiation due to its high radiation use efficiency. Wheat benefited from the increased solar radiation, but even more from the increased soil temperature.

A Model Analysis of Yield Differences among Recombinant Inbred Lines in Barley

Crop models can support plant breeding if they can predict differences in performance of different genotypes. In this study, the ability of a crop model to explain yield differences among genotypes in a recombinant inbred line (RIL) population of two‐row barley (Hordeum vulgare L.) was explored. Yield and model‐input traits of 94 RILs and their parents, ‘Prisma’ and ‘Apex’, were measured in field experiments conducted in Wageningen, Netherlands, in 1996 at low and in 1997 at high N levels. The major gene, denso, with the dwarfing allele from Prisma, was segregating in this population. Short denso RILs outyielded tall types in both years, and this yield advantage was stronger in 1997, largely because the tall genotypes lodged. A crop model based on existing routines for biomass production explained only 26 to 38% of the yield variation among genotypes. The model, using input traits measured from the 1997 data, did not accurately predict growth of genotypes in 1996 because some traits varied with plant N status, which the model did not account for. Model analysis in the high‐N environment showed that of the seven model‐input traits examined, only lodging score, preflowering duration, and fraction of biomass partitioned to spikes had a significant effect on yield. When these three traits were used while fixing others at their across‐genotype means, the model explained 65% of yield variation. To allow effective use of crop modeling in breeding, the ability of crop models to explain yield differences among genotypes has to be improved.

Yield, Flowering, and Leaf Area Index of Okra‐Leaf and Normal‐Leaf Cotton Isolines

Cotton (Gossypium hirsutum L.) with alternative leaf morphologies, such as the cleft‐shaped okra‐leaf types, offers production advantages such as earlier maturity. However, okra‐leaf types have not been commercially viable in the USA. The objectives of this study were to test okra‐leaf types in genetic backgrounds varying in maturity and region of adaptation and to provide growth data that might explain yield differences. Four to seven pairs of selected cotton okra‐ and normal‐leaf isolines (and check cultivars) were grown in the field in one 2‐yr (Exp. A) and two 1‐yr experiments (Exp. B and C) from 1994 to 1996 near Stoneville, MS, in row spacings of 76 and 102 cm. In Exp. A, average lint yields of okra‐leaf isolines were greater overall than normal‐leaf lines (847 vs. 749 kg ha−1), but in Exp. C, the opposite was true (1020 kg ha−1 for okra‐ vs. 1130 kg ha−1 for normal‐leaf types). No yield difference was found between leaf types in Exp. B. Yields of okra‐leaf lines were either equal to or less than those of recently released high‐yielding commercial types whose okra‐leaf isolines are not yet available. Okra‐leaf types were usually 1 to 4 d earlier in maturity than their normal‐leaf counterparts, possibly contributing to their overall yield advantage in Exp. A. When only okra‐leaf isolines were considered, Tamcot HQ95 ranked first or second highest for yield and was the earliest to mature in all three tests. In general, the row‐spacing effect and interactions with row spacing were not significant. The results indicate that the okra‐leaf trait should be considered for producing future cultivars.

Validation of the Principal Axis Model (PAM) and its Application to Genotype Selection in Field Pea (Pisum sativumL.) Crops

The principal axis model (PAM) uses a principal axis and an ellipse to characterize the variation in the relationship between the seed (SWT) and plant (PWT) weights of individual plants within a crop. The theoretical linkage between the magnitude and variability of plant harvest index (PHI), and therefore seed yield per unit area, and changes in the components of the PAM was examined using data from four field pea (Pisum sativumL.) genotypes sown at 9, 49, 100, 225 and 400 plants m-2. A strong linear relationship (R2>93.8%) between SWT and PWT and a negative SWT-axis intercept were confirmed for all crops. Analyses indicated that decreased variability of PHI within a crop would result from selection to: (a) increase the SWT-axis intercept of the PAM; (b) increase the slope of the PAM; (c) optimize the ellipse location; and (d) minimize the deviation around the principal axis. The first three methods were used to explain yield differences (P<0.05) among genotypes of different populations. A potential strategy for single plant selection based on the PAM is proposed. This may enable early generation (F4) selection of small, high performing plants that may be ideal crop ideotypes. A theoretical example of the strategy is presented, with differences among selections based on the PAM, SWT or harvest index highlighted.

The 1BL/1RS Translocation: Agronomic Performance of F3‐Derived Lines from a Winter Wheat Cross

Cultivar comparisons have suggested that the 1BL/1RS wheat (Triticum aestivum L.)‐rye (Secale cereale L.) chromosomal translocation enhances agronomic performance and environmental stability of wheat. This advantage has been attributed either to disease resistance genes or to unproved adaptation genes on the 1RS segment. The objective of this study was to determine the effect of 1BL/1RS without the confounding effect of cult!var background by evaluating 17 homogeneous 1B, 20 heterogeneous 1B:1BL/1RS, and 22 homogeneous 1BL/ 1RS lines. The lines were randomly selected from the cross ‘Siouxland’/ ‘Ram’. The 59 progeny lines and the two parents were tested in seven Nebraska field environments with a randomized complete‐block design. Data were obtained for grain yield, components of yield, grain volume weight, anthesis date, plant height, and leaf rust infection. The 1BL/ 1RS class was 9% higher yielding than 1B and heterogeneous classes. This yield advantage was attributed to increased kernel weight, which was generally expressed in lower yielding environments. Differential response to disease pressure did not explain yield differences. Within chromosome classes, differences in grain yield were attributed more to variation in number of spikes per square meter not kernel weight. The grain yield advantage of the 1BL/1RS appeared to be associated with a postanthesis stress tolerance, which resulted in increased kernel weight of the 1BL/1RS genotypes.

A Model for Drainage Benefits

ABSTRACT A regression model for corn yield was developed which includes rainfall during two critical periods of the growing season: (a) the time during which spring tillage and planting operations occur, (b) the time during pollination. The regression model was applied to three widely dif-ferent situations: (a) eight counties in Illinois that could be grouped according to soil associations with relatively similar drainage problems, (b) three University of Illinois farms (Allerton Farms) in close proximity but with dif-ferent levels of drainage, (c) drainage research plots at the University of Illinois Brownstown Research Center. Rainfall during period 1 was found to significantly affect yields on farms with inadequate drainage systems. The model has potential to be useful in explaining yield dif-ferences between well drained and poorly drained farms.

Night Respiration of a Maize Crop in the Lowland Humid Tropics

(1) High night temperatures (minimum temperature in range 22-25 $^\circ$C), could contribute to the lower yields of maize crops grown in the humid tropics compared with temperate areas because of higher rates of respiration. (2) Overnight respiration losses of whole plants were measured in a young maize crop grown in the humid tropic zone of Western Nigera. In an older crop, overnight leaf respiration was measured. (3) In the younger plants, respiration rates initially were high (c. 15% overnight reduction in dusk plant dry weight) but they declined to c. 5% by 27 days after emergence (d.a.e.). Overnight leaf respiration caused 4% reduction in dusk lamina dry weight. Nightly dry weight losses by whole plants averaged 40% of daily dry weight gain. (4) Assuming a value of 12 mg g$^{-1}$ per 12 h with a Q$_{10}$ of 2 for the maintenance component of respiration for the period 11 to 27 d.a.e., overnight dry weight loss could be reduced to 37% and 35% of daily gain for a 10 $^\circ$C and 20 $^\circ$C decrease in night minimum temperature. Such dry weight conservation, if maintained through the remaining period of crop growth could give yield increases of 200 and 300 kg ha$^{-1}$ respectively, and at best. c. 5% improvement on Experimental Station yields of elite varieties. (5) On this basis it appears that high night temperatures are of minor importance in explaining yield differences between the humid tropics and temperate zones.