Sustainable Cropping Systems

Global crop production must substantially increase to meet the needs of a rapidly growing population. This is constrained by the availability of nutrients, water, and land. There is also an urgent need to reduce the negative environmental impacts of crop production. Collectively, these issues represent one of the greatest challenges of the twenty-first century. Sustainable cropping systems based on ecological principles are the core of integrated approaches to solve this critical challenge. This special issue provides an international basis for revealing the underlying mechanisms of sustainable cropping systems to drive agronomic innovations. It includes review and original research articles that report novel scientific findings on improvement in cropping systems related to crop yields and their resistance to biotic and abiotic stressors, resource use efficiency, environmental impact, sustainability, and ecosystem services

Agronomic responses of corn to stand reducation at vegetative growth stages

Yield loss charts for hail associated with stand reduction assume that remaining plants lose the ability to compensate for lost plants by mid-vegetative growth. Yield losses and stand losses after V8 – leaf collar system – and throughout the remaining vegetative stages are 1:1 according to the current standards. We conducted field experiments from 2006 to 2009 at twelve site-years in Illinois, Iowa, and Ohio to determine responses of corn to stand reduction at the fifth, eighth, eleventh, and fifteenth leaf collar stages (V5, V8, V11, and V15, respectively). We also wanted to know whether these responses varied between uniform and random patterns of stand reduction with differences in within-row interplant spacing. When compared to a control of 36,000 plants per acre, grain yield decreased linearly as stand reduction increased from 16.7 to 50% (Table 3), but was not affected by the pattern of stand reduction. This rate of yield loss was greatest when stand reduction occurred at V11 or V15, and least when it occurred at V5. With 50% stand loss, yield was 83 and 69% of the control when stand loss occurred at V5 and V15, respectively. With 16.7% stand loss at V5, V8, or V11, yield averaged 96% of the control. Per-plant grain yield increased when stand loss occurred earlier and was more severe. With 50% stand loss at V11 or V15, per-plant grain yield increased by 37 to 46% compared to the control. Corn retains the ability to compensate for lost plants through the late vegetative stages, indicating that current standards for assessing the effect of stand loss in corn should be reevaluated

Maize Leaf Appearance Rates: A Synthesis From the United States Corn Belt

The relationship between collared leaf number and growing degree days (GDD) is crucial for predicting maize phenology. Biophysical crop models convert GDD accumulation to leaf numbers by using a constant parameter termed phyllochron (°C-day leaf−1) or leaf appearance rate (LAR; leaf oC-day−1). However, such important parameter values are rarely estimated for modern maize hybrids. To fill this gap, we sourced and analyzed experimental datasets from the United States Corn Belt with the objective to (i) determine phyllochron values for two types of models: linear (1-parameter) and bilinear (3-parameters; phase I and II phyllochron, and transition point) and (ii) explore whether environmental factors such as photoperiod and radiation, and physiological variables such as plant growth rate can explain variability in phyllochron and improve predictability of maize phenology. The datasets included different locations (latitudes between 48° N and 41° N), years (2009–2019), hybrids, and management settings. Results indicated that the bilinear model represented the leaf number vs. GDD relationship more accurately than the linear model (R2 = 0.99 vs. 0.95, n = 4,694). Across datasets, first phase phyllochron, transition leaf number, and second phase phyllochron averaged 57.9 ± 7.5°C-day, 9.8 ± 1.2 leaves, and 30.9 ± 5.7°C-day, respectively. Correlation analysis revealed that radiation from the V3 to the V9 developmental stages had a positive relationship with phyllochron (r = 0.69), while photoperiod was positively related to days to flowering or total leaf number (r = 0.89). Additionally, a positive nonlinear relationship between maize LAR and plant growth rate was found. Present findings provide important parameter values for calibration and optimization of maize crop models in the United States Corn Belt, as well as new insights to enhance mechanisms in crop models

Temperature-Driven Developmental Modulation of Yield Response to Nitrogen in Wheat and Maize

Nitrogen management is central to the economic and environmental dimensions of agricultural sustainability. Yield response to nitrogen fertilisation results from multiple interacting factors. Theoretical frameworks are lagging for the interaction between nitrogen and air temperature, the focus of this study. We analyse the relation between yield response to nitrogen fertiliser and air temperature in the critical period of yield formation for spring wheat in Australia, winter wheat in the US, and maize in both the US and Argentina. Our framework assumes (i) yield response to nitrogen fertiliser is primarily related to grain number per m2, (ii) grain number is a function of three traits: the duration of the critical period, growth rate during the critical period, and reproductive allocation, and (iii) all three traits vary non-linearly with temperature. We show that “high” nitrogen supply may be positive, neutral, or negative for yield under “high” temperature, depending on the part of the response curve captured experimentally. The relationship between yield response to nitrogen and mean temperature in the critical period was strong in wheat and weak in maize. Negative associations for both spring wheat in Australia and winter wheat with low initial soil nitrogen ( 120 kg N ha-1) that favoured grain number and compromised grain fill, the relation between yield response to nitrogen and temperature was positive for winter wheat. The framework is particularly insightful where data did not match predictions; a non-linear function integrating development, carbon assimilation and reproductive partitioning bounded the pooled data for maize in the US and Argentina, where water regime, previous crop, and soil nitrogen overrode the effect of temperature on yield response to nitrogen fertilisation.Fil: Sadras, Victor O.. University of Adelaide; Australia. South Australian Research And Development Institute; AustraliaFil: Giordano, Nicolas. Kansas State University; Estados UnidosFil: Correndo, Adrian. Kansas State University; Estados UnidosFil: Cossani, C. Mariano. University of Adelaide; Australia. South Australian Research And Development Institute; AustraliaFil: Ferreyra, Juan M.. No especifíca;Fil: Caviglia, Octavio Pedro. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Entre Ríos; ArgentinaFil: Coulter, Jeffrey A.. University of Minnesota; Estados UnidosFil: Ciampitti, Ignacio Antonio. Kansas State University; Estados UnidosFil: Lollato, Romulo P.. Kansas State University; Estados Unido

Low N Fertilizer Application and Intercropping Increases N Concentration in Pea (Pisum sativum L.) Grains

Sustainable intensification of pulses needs reduced input of nitrogen (N) fertilizer with enhanced crop nutritional quality and yield. Therefore, increasing N harvest in grains (sink organs) by improving N remobilization is of key importance. Previous research has shown that a lower dose of N fertilizer effectively increases the rate of N remobilization, while intercropping improves the grain N concentration in pea (Pisum sativum L.). However, it is unknown whether intercropping can facilitate this N fertilizer effect to increase N remobilization, and thereby enhance the N harvest index (NHI). In this study, we determined N allocation among different organs of pea plants, N translocation from leaf and stem tissues to pods, N2 fixation, N utilization efficiency, and NHI of pea plants grown alone or intercropped with maize (Zea mays L.) with different N fertilization treatments in a field experiment in northwestern China from 2012 to 2014. A base application of 90 kg N ha−1 at sowing and top-dress application of 45 kg N ha−1 at flowering integrated with maize–pea intercropping increased N allocation to pod tissues, N translocation to grains, and NHI of pea plants. Compared with the application of 90 kg N ha−1 at sowing and 135 kg N ha−1 top-dressed at flowering, reducing the top-dress application of N fertilizer to 45 kg N ha−1 increased N allocation to intercropped pea plants by 8%. Similarly, N translocation to grains from leaf and stem tissues was increased by 37.9 and 43.2%, respectively, enhancing the NHI by 40.1%. A positive correlation between N2 fixation and NHI was observed, implying that N2 fixation improves N concentration in grain sinks. Thus, our data show that growing pulses in an intercropping system with reduced N fertilization are essential for maximizing N translocation, improving nutritional quality, and preventing the loss of N through leaching, thereby avoiding potential groundwater contamination

Soil–Plant Indices Help Explain Legume Response to Crop Rotation in a Semiarid Environment

Crop productivity is typically affected by various soil–plant factors systematically as they influence plant photosynthesis, soil fertility, and root systems. However, little is known about how the productivity of legumes is related to crop rotation systems. The objectives of this study were to determine the effect of rotation systems on legume productivity and the relationships among legume productivity and soil–plant factors. Three annual legumes – chickpea (Cicer arietinum L.), pea (Pisum sativum L.), and lentil (Lens culinaris Medikus), were included in various diversified rotation systems and compared with legume monoculture in the 8-year rotation study. Soil N and water conditions, and canopy and root systems were evaluated at the end of 8-year rotation in the semiarid Canadian prairies. Results showed that diversified rotation systems improved leaf greenness by 4%, shoot biomass by 25%, nodule biomass by 44%, and seed yield by 95% for chickpea and pea, but such effects were not found for lentil. Pea monocultures increased root rot severity by threefold compared with diversified rotations, and chickpea monoculture increased shoot rot severity by 23%, root rot severity by 96% and nodule damage by 219%. However, all the legume monocultures improved soil N accumulation by an average 38% compared to diversified systems. Pea and chickpea displayed considerable sensitivity to plant biotic stresses, whereas lentil productivity had a larger dependence on initial soil N content. The 8-year study concludes that the rotational effect on legume productivity varies with legume species, the frequency of a legume appearing in the rotation, and the integration of relevant soil and plant indices

Searching for time reversal invariance violation in polarized neutron decay

Time reversal invariance violation is tightly constrained in the Standard Model, and the existence of a T-violating effect above the predicted level would be an indication of new physics. A sensitive probe of this symmetry in the weak interaction is the measurement of the D-coefficient in neutron decay. This parameter characterizes the triple-correlation of neutron spin, electron momentum, and neutrino (or proton) momentum, which changes sign under time reversal. The emiT experiment, now on line, attempts to improve the measurement of D,D, whose current average is 0.3±1.5×10−3.0.3±1.5×10−3. © 1997 American Institute of Physics.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/87907/2/399_1.pd

Carnivore Translocations and Conservation: Insights from Population Models and Field Data for Fishers (Martes pennanti)

Translocations are frequently used to restore extirpated carnivore populations. Understanding the factors that influence translocation success is important because carnivore translocations can be time consuming, expensive, and controversial. Using population viability software, we modeled reintroductions of the fisher, a candidate for endangered or threatened status in the Pacific states of the US. Our model predicts that the most important factor influencing successful re-establishment of a fisher population is the number of adult females reintroduced (provided some males are also released). Data from 38 translocations of fishers in North America, including 30 reintroductions, 5 augmentations and 3 introductions, show that the number of females released was, indeed, a good predictor of success but that the number of males released, geographic region and proximity of the source population to the release site were also important predictors. The contradiction between model and data regarding males may relate to the assumption in the model that all males are equally good breeders. We hypothesize that many males may need to be released to insure a sufficient number of good breeders are included, probably large males. Seventy-seven percent of reintroductions with known outcomes (success or failure) succeeded; all 5 augmentations succeeded; but none of the 3 introductions succeeded. Reintroductions were instrumental in reestablishing fisher populations within their historical range and expanding the range from its most-contracted state (43% of the historical range) to its current state (68% of the historical range). To increase the likelihood of translocation success, we recommend that managers: 1) release as many fishers as possible, 2) release more females than males (55–60% females) when possible, 3) release as many adults as possible, especially large males, 4) release fishers from a nearby source population, 5) conduct a formal feasibility assessment, and 6) develop a comprehensive implementation plan that includes an active monitoring program

Reduced evolutionary rate in reemerged Ebola virus transmission chains

On 29 June 2015, Liberia’s respite from Ebola virus disease (EVD) was interrupted for the second time by a renewed outbreak (“flare-up”) of seven confirmed cases. We demonstrate that, similar to the March 2015 flare-up associated with sexual transmission, this new flare-up was a reemergence of a Liberian transmission chain originating from a persistently infected source rather than a reintroduction from a reservoir or a neighboring country with active transmission. Although distinct, Ebola virus (EBOV) genomes from both flare-ups exhibit significantly low genetic divergence, indicating a reduced rate of EBOV evolution during persistent infection. Using this rate of change as a signature, we identified two additional EVD clusters that possibly arose from persistently infected sources. These findings highlight the risk of EVD flare-ups even after an outbreak is declared over