Increase In Daily Rate Research Articles

BIOLOGICAL CONTROL OF Corynespora cassicola AND Drechslera tritici-repentis

Chemical control is the most widely used method for disease management in significant crops such as soybeans and wheat. However, for a few years biological control has gained prominence. Thus, we evaluated the antagonism of bacteria Pseudomonas fluorencens, Pantoea aglomerans, and Bacillus sp. on the phytopathogens Corynespora cassiicola and Drechslera tritici-repentis, previously isolated from soybean and wheat leaves, respectively. The experiments were carried out under controlled conditions at the Phytobacteriology Laboratory of the Faculty of Agronomy and Veterinary Medicine (FAVM), University of Passo Fundo (UPF), Rio Grande do Sul, Brazil. The treatments were: T1: P. Fluorencens + pathogen; T2: P. aglomerans + pathogen; T3: Bacillus spp. + pathogen, and T4: pathogen (control). In each experiment (C. cassiicola and D. tritici-repentis), a completely randomized design with six replications was used. The data were submitted to linear regression analysis, obtaining the daily increase rate (slope). The final time data was submitted to the ANOVA, and the means were compared by the Tukey test (P < 0.05). P. fluorescens, P. agglomerans, and Bacillus sp. reduced mycelial growth by 74 and 87% of C. cassiicola and D. tritici-repentis, respectively. Although this study was carried out under in vitro conditions, it can serve as a basis for other biological control studies, especially about the management of leaf spots caused by C. cassiicola and D. tritici-repentis, under field conditions.

Modeling the growth dynamics of water lettuce, Pistia stratiotes L. in wastewater

This study was aimed at assessing water lettuce (Pistia stratiotes L.) biomass growth, which was tested at the Faculty of Civil Engineering and Architecture of Nis under partially controlled conditions during a 70-day-long test, with a mixture of communal wastewater and water from the shaft at the hydraulic engineering demonstration facility as a source of nutrient matter. The biomass measured after the 70-day experiment ranged from 4.31 to 4.71 kg WW/m2 (average 4.48 kg WW/ m2). The daily absolute growth rate (AGR) was 58.81 g/m2 day, the daily increase rate (DIR) was 16.16 %/day, the average daily relative growth rate (RGR) was 0.0359 g/g day, and the biomass doubling time (DT) was 32.94 days. The following models were used to model the dynamics of water lettuce biomass growth: the exponential model (average MSE 0.0485, average coefficient of determination (R2) to 0.9757); the logistic model (mean squared error (MSE) 0.0049, R2 0.9976), and the sigmoidal model (average MSE 0.0003, average R2 0.9999). All models have a high accuracy; however, the exponential models give a continuous increase in biomass over time, practically to infinity, without taking into account that under conditions of increased plant density and reduced availability of resources, biomass growth slows down and, therefore, they are not suitable for application in real conditions. The logistic model (environmental capacity 6.1680 kg/m2 after about 150 days, ti 53.8587 days, ta 32.8295 days, tb 74.8879), and sigmoidal model (environmental capacity 5.2903 kg/m2 after about 150 days, ti 50.2972 days, ta 34.3072 days, tb 66.2872 days) adequately describe the biomass growth of the growth phase of water lettuce with high precision, which is essential for planning appropriate preventive and active measures to control the spread of water lettuce as an invasive plant and minimize negative impacts on waterbodies in Serbia.

SafeCampus: Multimodal-Based Campus-Wide Pandemic Forecasting

The motivation of this work is to build a multimodal-based COVID-19 pandemic forecasting platform for a large-scale academic institution to minimize the impact of COVID-19 after resuming academic activities. The design of this multimodality work is steered by video, audio, and tweets. Before conducting COVID-19 prediction, we first trained diverse models, including traditional machine learning models (e.g., Naive Bayes, support vector machine, and TF-IDF) and deep learning models [e.g., long short-term memory (LSTM), MobileNetV2, and SSD], to extract meaningful information from video, audio, and tweets by 1) detecting and counting face masks, 2) detecting and counting cough for potential infected cases, and 3) conducting sentiment analysis based on COVID-19-related tweets. Finally, we fed the multimodal analysis results together with daily confirmed cases data and social distancing metrics into the LSTM model to predict the daily increase rate of confirmed cases for the next week. Important observations with supporting evidence are presented.

Modeling analysis reveals the transmission trend of COVID-19 and control efficiency of human intervention

BackgroundA novel coronavirus disease (COVID-19) has caused huge damage to public health around the world. Revealing the transmission dynamics of COVID-19 and control efficiency is important for containing the spread of the virus.MethodsBy using a logistic growth model, we estimated the transmission parameters of COVID-19 in China and six other countries (Republic of Korea, Iran, Italy, Spain, France and Germany). The transmission parameters represent the maximum daily increase rate in the early stages of the epidemic and the control efficiency under human intervention. The control efficiency was determined by the significant decrease of the daily increase rate in time and cumulative cases.ResultsWe found the daily increase rate of cumulative cases of COVID-19 decreased significantly in both time and cumulative cases in all countries, but the decreasing trend was not further reduced in other countries except for China and Republic of Korea. The response of the daily increase rate to control measures was much earlier than the number of new cases.ConclusionsOur results suggested that lockdown at the epicenter and social distancing effectively reduced the spread of COVID-19 in the early stage, but identification and isolation of patients, suspected cases and people with close contact at a community level is essential in further reduction of the daily increase rate of COVID-19.

Spatio-temporal distribution characteristics of COVID-19 in China: a city-level modeling study

BackgroundThe coronavirus disease 2019 (COVID-19) has become a pandemic. Few studies have been conducted to investigate the spatio-temporal distribution of COVID-19 on nationwide city-level in China.ObjectiveTo analyze and visualize the spatiotemporal distribution characteristics and clustering pattern of COVID-19 cases from 362 cities of 31 provinces, municipalities and autonomous regions in mainland China.MethodsA spatiotemporal statistical analysis of COVID-19 cases was carried out by collecting the confirmed COVID-19 cases in mainland China from January 10, 2020 to October 5, 2020. Methods including statistical charts, hotspot analysis, spatial autocorrelation, and Poisson space–time scan statistic were conducted.ResultsThe high incidence stage of China’s COVID-19 epidemic was from January 17 to February 9, 2020 with daily increase rate greater than 7.5%. The hot spot analysis suggested that the cities including Wuhan, Huangshi, Ezhou, Xiaogan, Jingzhou, Huanggang, Xianning, and Xiantao, were the hot spots with statistical significance. Spatial autocorrelation analysis indicated a moderately correlated pattern of spatial clustering of COVID-19 cases across China in the early phase, with Moran’s I statistic reaching maximum value on January 31, at 0.235 (Z = 12.344, P = 0.001), but the spatial correlation gradually decreased later and showed a discrete trend to a random distribution. Considering both space and time, 19 statistically significant clusters were identified. 63.16% of the clusters occurred from January to February. Larger clusters were located in central and southern China. The most likely cluster (RR = 845.01, P < 0.01) included 6 cities in Hubei province with Wuhan as the centre. Overall, the clusters with larger coverage were in the early stage of the epidemic, while it changed to only gather in a specific city in the later period. The pattern and scope of clusters changed and reduced over time in China.ConclusionsSpatio-temporal cluster detection plays a vital role in the exploration of epidemic evolution and early warning of disease outbreaks and recurrences. This study can provide scientific reference for the allocation of medical resources and monitoring potential rebound of the COVID-19 epidemic in China.

Effects of non-pharmaceutical interventions against COVID-19: A cross-country analysis.

Prolonging non‐pharmaceutical interventions (NPIs) used in the control of pandemics can cause a devastating effect on the overall economic and social welfare levels. Therefore, policymakers are facing a difficult duty in terms of implementing economically and socially sustainable and acceptable measures. The aim of this study is to investigate the effectiveness of NPIs implemented to control the COVID‐19 pandemic. To this end, eight NPI measures were analysed, and their effects on the number of cases were investigated for France, Spain, China, and South Korea. In the study, the treatment effect of these mechanisms on the daily increase rate of the total number of cases during a certain period was analysed by using logarithmic linear regression with a dummy variables model. The findings indicate that the measures are effective against the spread of the pandemic at different levels. The findings also suggest that the most effective measure in decreasing the number of cases is workplace closure. An analysis comparing the effectiveness of countrywide measures and regional measures shows that school closing is the most effective measure to decrease the number of cases when implemented countrywide as opposed to regional implementation.

Using satellite-derived estimates of plant phenological rhythms to predict sage-grouse nesting chronology.

The “green wave” hypothesis posits that during spring consumers track spatial gradients in emergent vegetation and associated foraging opportunities. This idea has largely been invoked to explain animal migration patterns, yet the general phenomenon underlies trends in vertebrate reproductive chronology as well. We evaluated the utility of this hypothesis for predicting spatial variation in nest initiation of greater sage‐grouse (Centrocerus urophasianus), a species of conservation concern in western North America. We used the Normalized Difference Vegetation Index (NDVI) to map the green wave across elevation and then compiled dates and locations of >450 sage‐grouse nests from 20 study sites (2000–2014) to model nest initiation as a function of the start of the growing season (SOS), defined here as the maximum daily rate of increase in NDVI. Individual sites were drawn from three ecoregions, distributed over 4.5° latitude, and spanning 2,300 m in elevation, which captured the climatic, edaphic, and floristic diversity of sagebrush ecosystems in the southern half of current sage‐grouse range. As predicted, SOS displayed a significant, positive relationship with elevation, occurring 1.3 days later for each 100 m increase in elevation. In turn, sage‐grouse nest initiation followed SOS by 22 ± 10 days (r2 = .57), with hatch dates falling on or just prior to the peak of the growing season. By timing nesting to the green wave, sage‐grouse chicks hatched when the abundance of protein‐rich invertebrate biomass is hypothesized to be nearing a seasonal high. This adaptation likely represents a strategy for maximizing reproductive success in the arid, variable environments that define sagebrush ecosystems. Given projected changes in climate and land use, these results can be used to predict periods of relative sensitivity to habitat disturbance for sage‐grouse. Moreover, the near real‐time availability of satellite imagery offers a heretofore underutilized means of mapping the green wave, planning habitat restoration, and monitoring range conditions.

Pandemic Spread-an Empirical Analysis.

The coronavirus disease-2019 (COVID-19) epidemic started in late 2019, and was upgraded to a pandemic on March 11, 2020 by the World Health Organization (WHO). Well established epidemiological models have been used over the last few months in an attempt to predict how the virus would spread. The predictions were frightening, and the resulting panic caused many governments to impose lockdowns or other severe restrictions, with lasting effects. This short paper discusses another way of looking at the spread of COVID-19, by focusing on the daily rate of infection, defined as the daily rate of increase in the number of infected persons. It is shown that the daily rate is monotonically decreasing, after a short initial period, in all countries, and that the pattern is similar in all countries. This appears to be a universal phenomenon. Based on these calculations, the April 1, 2020 data for Western Europe were sufficient to predict the beginning of the end of COVID-19 in that region before the end of that month.

CLE-CLAVATA1 Signaling Pathway Modulates Lateral Root Development under Sulfur Deficiency.

Plant root system architecture changes drastically in response to availability of macronutrients in the soil environment. Despite the importance of root sulfur (S) uptake in plant growth and reproduction, molecular mechanisms underlying root development in response to S availability have not been fully characterized. We report here on the signaling module composed of the CLAVATA3 (CLV3)/EMBRYO SURROUNDING REGION (CLE) peptide and CLAVATA1 (CLV1) leucine-rich repeat receptor kinase, which regulate lateral root (LR) development in Arabidopsis thaliana upon changes in S availability. The wild-type seedlings exposed to prolonged S deficiency showed a phenotype with low LR density, which was restored upon sulfate supply. In contrast, the clv1 mutant showed a higher daily increase rate of LR density relative to the wild-type under prolonged S deficiency, which was diminished to the wild-type level upon sulfate supply, suggesting that CLV1 directs a signal to inhibit LR development under S-deficient conditions. CLE2 and CLE3 transcript levels decreased under S deficiency and through CLV1-mediated feedback regulations, suggesting the levels of CLE peptide signals are adjusted during the course of LR development. This study demonstrates a fine-tuned mechanism for LR development coordinately regulated by CLE-CLV1 signaling and in response to changes in S availability.

The Incidence and the Implications of Natural Infection with Nomuraea rileyi (Farlow) Samson on the Life-Table Parameters of Laboratory-Reared Culex pipiens L. Mosquitoes

During routine mass rearing of Culex pipiens L., 46 % mortality rate was recorded among 3-day-old larvae in the late summer, 2014, at Cairo University, Giza, Egypt. An analysis of the water in the rearing plastic cups and the dead larvae revealed the presence of the fungus Nomuraea rileyi (Farlow) Samson. A comparative study was carried out using life-table parameters of the fungal-infected population of Cx. pipiens and fungus-free population (control) under laboratory conditions (30 ± 0.10 °C, RH 52.5 ± 7.8 % and photoperiod 16L:8D). Fungal-infected stages of Cx. pipiens exhibited a decrease in longevity (larvae, 5.89 ± 0.063 days; adult males, 7.8 ± 0.75 days; adult females, 10.83 ± 1.6 days). The mean generation time of the healthy population (22.09 ± 0.82 days) was not significantly different from that of the infected population (22.25 ± 0.08 days), nearly the same mean generation time. The fungal-infected Cx. pipiens population replicated itself 4.62 ± 1.45 times with a very low exponential rate of daily increase of 0.0688 ± 0.0154/day. However, the fungus-free population showed a higher replication rate of 38.10 ± 11.80 times, with a higher daily rate of increase (0.1648 ± 0.0167/day). Females of the fungal-infected Cx. pipiens, exhibited a decrease in the fertility, 25.67 ± 7.70 eggs/female, as compared to the females from the control population, 163.29 ± 40.64 eggs/female. Data of the present study suggested the possibility of using N. rileyi as a safe bio-control agent against the development of the larvae of Cx. pipiens.

Socioeconomic Drivers of PM2.5 in the Accumulation Phase of Air Pollution Episodes in the Yangtze River Delta of China.

Recent studies in PM2.5 sources show that anthropogenic emissions are the main contributors to haze pollution. Due to their essential roles in establishing policies for improving air quality, socioeconomic drivers of PM2.5 levels have attracted increasing attention. Unlike previous studies focusing on the annual PM2.5 concentration (Cyear), this paper focuses on the accumulation phase of PM2.5 during the pollution episode (PMAE) in the Yangtze River Delta in China. This paper mainly explores the spatial variations of PMAE and its links to the socioeconomic factors using a geographical detector and simple linear regression. The results indicated that PM2.5 was more likely to accumulate in more developed cities, such as Nanjing and Shanghai. Compared with Cyear, PMAE was more sensitive to socioeconomic impacts. Among the twelve indicators chosen for this study, population density was an especially critical factor that could affect the accumulation of PM2.5 dramatically and accounted for the regional difference. A 1% increase in population density could cause a 0.167% rise in the maximal increment and a 0.214% rise in the daily increase rate of PM2.5. Additionally, industry, energy consumption, and vehicles were also significantly associated with PM2.5 accumulation. These conclusions could serve to remediate the severe PM2.5 pollution in China.

Effect of photoperiod on adult size and weight in Harmonia axyridis (Coleoptera: Coccinellidae)

Short photoperiods often accelerate preimaginal development in insects that overwinter as adults and thus ensure the timely development of the diapausing stage. However, fast development usually results in small adults with few reserves whereas successful overwintering is dependent on sufficient reserves of nutrients. Thus, an insect faces two opposite challenges: increase adult weight or speed up pre-adult development. One solution to this time-size trade-off is fast development resulting in relatively light-weight but not too small adults, which are able to survive if there is an early onset to winter and have the possibility of further increasing their weight if conditions in autumn remain favourable for longer than usual. To test this hypothesis, we determined the effect of different photoperiods (day lengths of 12 and 18 h at 20°C) on the duration of preimaginal development, size of emerging adults and dynamics of adult weight in Harmonia axyridis. The larvae reared under conditions tended to develop faster and invest resources in structural growth rather than in increasing weight: the daily rate of increase in size under a 12 h long photoperiod was greater than that under a 18 h long photoperiod, whereas the rate of gain in weight showed the opposite tendency. This resulted in a significant decrease in the weight /size ratio of emerging adults. However, their low initial nutritional status was partly compensated for by adult feeding: the relative gain in adult weight of short-day individuals was greater than that of the beetles that developed under long day conditions.

Gypsum attack: performance of silicic pozzolans and Portland cements as determined by ASTM C 452-68

An earlier study with metakaolin and 10 Portland cements (PC) suggested that the ASTM C 452-68 test could be used to characterise and differentiate 28-day blended cements prepared with metakaolin. ASTM C 452-68 testing was once again conducted on 67 cements: the above 10 PC and 57 blended cements (POZC) containing 20%, 30% or 40% silica fume or diatomites (D or N) (= Z pozzolan). ASTM C 452-68 specimens were made from all the cements and their daily rate of increase in length was determined. The results showed that in a gypsum and water environment, the pozzolanic reactions induced by the reactive silica, SiO2r−, present in Z pozzolans, prevailed over the sulfatic hydration of the pozzolans themselves, reaching completion within 28 days. The explanation is that the formation rate (Vf) of the calcium silicate hydrate gel and silanol groups from the SiO2r− present in the Z pozzolan finishes being greater than the Vf observed for the ettringite forming slowly (ett-lf) from the C3A of ordinary Portland cement, which declines to zero, even though sulfatic hydration continues. The positive 7 and/or 28-day results obtained with the Frattini test (EN 196-5) and the tests set out in standards EN 450, ASTM C 311-07, EN 13263-1 or ASTM 618-95a provided proof that the ASTM C 452-68 test can be validly used to characterise 28-day POZC prepared with any natural or artificial pozzolan, subject, however, to the establishment of suitable standard physical-chemical requirements and specifications.

On the thermal performance of low income housing during heat waves

This paper investigates the indoor thermal conditions in fifty low income non air conditioned houses in Athens, Greece, during the extremely hot summer of 2007. Hourly indoor temperature data have been analysed during three extended heat waves. Indoor temperatures as high as 40°C were recorded and the average indoor minimum temperature was always above 28°C. Mean indoor temperatures during the hot season were up to 4.2K above the normal climatic period, while the daily increase rate varied from 0.2K/day during the first up to 0.8K/day for the peak days of the heat wave. The exposure of inhabitants to high temperatures is very important because for almost 85% of the hot period, indoor temperature exceeded 30°C. Periods of about 216 continuous hours above 30°C, and six days above 33°C were recorded in many buildings. The dynamics and the evolution of indoor temperatures as a function of the outdoor climatic characteristics and the thermal capacitance of the buildings are analysed. Possible techniques to improve the indoor environmental quality in low income housing during extremely hot periods are discussed.

LOGISTIC MODELS FOR ESTIMATING EPIDEMIC INCREASE RATES OF BLUEBERRY FOLIAR DISEASES, BASED ON METEOROLOGICAL AND LEAF SENESCENCE VARIABLES

Alternaria tenuissima is one of the most important pathogens on blueberry (Vaccinium corymbossum) in Argentina, causing leaf spots, twig blight and fruit rot. The severity of leaf spots caused by A. tenuissima was estimated in crops located in San Pedro, Gualeguaychu and Concordia (Argentina), during spring and summer of 2008 and 2009. Each linearised disease progress curve (3-4 observations per crop cycle) adjusted to Logistic and Gompertz epidemiological models (R2>0.77 to 0.98) for Concordia and San Pedro. Every 14 days, epidemic daily increase rate (DI) was estimated from disease epidemic curves. DI values were binary categorized according to median values (DI=0.04253) for the 36 severity percentages estimated every 14 days, into severe (DI≥0.04253), and slight to null (DI 0.55). The best logistic regression model of binary response, that integrated LS, RF and the interaction MMT×RF, showed a prediction accuracy of 97%. Among ordinal response models, the bivariate one that integrated LS factor and the interaction MMT×RF was chosen (92% prediction accuracy). These results add information for the development of a predictive system for blueberry leaf diseases, in a context of sustainable crop health management.

Early rise in human chorionic gonadotropin (hCG) is associated with maternal and perinatal outcome

hCG levels in early pregnancy are hypothesized to reflect trophoblast function and placental health. The goal of this study was to examine the association between serial hCG levels and maternal and perinatal outcomes. Retrospective cohort study. Patients with symptomatic unassisted pregnancies were followed with early first trimester serial hCGs. Only singleton live births were included. The slope for daily rate of increase in log transformed hCG levels (hCG rise) was estimated and analyzed as a continuous variable and by quartile (Q). Primary outcomes were birth weight and gestational age at delivery. Secondary outcomes were preterm birth, low birth weight (<2,500g), and hypertensive disorders. The relationship of hCG rise with each outcome was assessed with t-tests, chi-square tests, and linear and logistic regression. 159 singleton live births were analyzed. The median two-day increase in hCG was 105% (lower Q 70%; upper Q 142%). Linear regression models demonstrated no significant association between hCG rise and birth weight or gestational age. However, quartile of hCG rise was significantly associated with low birth weight (P=0.002). Compared to the first Q (slowest), subjects with a more rapid hCG rise (second-fourth Qs) had increased odds of low birth weight (OR 18.78, 6.54, and 5.14, respectively). A composite outcome, including small for gestational age, low birth weight, preterm birth, and preeclampsia was also more prevalent in higher Qs of hCG rise (P=0.006, OR 5.83, 3.75, and 1.54, respectively). A similar trend was observed for a composite adverse infant outcome (P=0.023, OR 4.62, 7.93, and 3.26, respectively). The rise in hCG may reflect trophoblast cell differentiation and function. A fast rise may indicate suboptimal placental function. These findings could lead to an early method to identify women at risk for later pregnancy complications.

Asia: Changing Times and Changing Problems

Asia: Changing Times and Changing Problems

Cropping system effects on giant foxtail (Setaria faberi) demography: I. Green manure and tillage timing

Manipulation of cropping systems to improve weed management requires a better understanding of how crop- and soil-related factors affect weed life cycles. Our objective was to assess the impacts of timing of primary tillage and use of legume green manure on giant foxtail demography and soil properties. We measured giant foxtail seed survival and dormancy, seedling emergence and survival, and fecundity, in addition to soil phytotoxicity, chemical properties affecting soil fertility and soil water, in the transition between the wheat and corn phases of a wheat–corn–soybean crop sequence. Postdispersal predation of giant foxtail seeds was measured in all three phases of the crop sequence. Wheat was grown either as a sole crop (W) or underseeded with red clover (R), and residues from this phase were rototilled either in the fall (FT) or in spring (ST). There were strong interactions between Red clover and Tillage timing in their effects on giant foxtail recruitment and fecundity in corn. Giant foxtail seedling emergence was 30% lower, and time to 50% emergence was more than 1 wk later, in the ST/R treatment than in the ST/W, FT/W, and FT/R treatments, which did not differ. However, fecundity of giant foxtail was 200% greater in the ST/R treatment than in the other three treatments because of suppressed early corn growth. The net effect of the ST/R treatment on giant foxtail demography in corn was to greatly increase inputs to the seedbank compared with the ST/W, FT/W, and FT/R treatments. Giant foxtail demography in the wheat phase was also affected by Red clover. There was a 200% increase in daily rates of postdispersal seed predation in the wheat phase of the R treatment compared with the W treatment. High-seed predation in the wheat phase and low fecundity in the corn phase of the FT/R treatment suggest that population growth rate of giant foxtail will be lower in this treatment than in the other treatments. The degree of soil phytotoxicity from red clover residues, the changes in the amount of interference from the corn crop early in the growing season, and the differential suitability of crop residues in the different rotations as habitat for seed predators all contributed to changes in giant foxtail demography. Understanding the effects of cropping system characteristics on entire weed life cycles will facilitate the design of integrated suites of complementary weed management tactics.

Comparative Carotenoid Accumulation and Retention in Near-isogenic rprp and RPRP Inbred Carrot Lines

The rp allele causes a significant reduction in total carotenoid pigmentation in carrot (Daucus carota L.) roots. The objective was to investigate the effect of rp on the composition, accumulation, and retention of carotenoids in two near-isolines of carrot, W266RPRP and W266rprp, during vegetative growth and postharvest storage. Field experiments were conducted during 1996 and 1997 in which roots were sampled weekly from 62 to 100 days after seed-sowing and biweekly during postharvest storage at 4 °C up to 386 days after sowing. Linear increases in total carotenoid concentration were observed for W266RPRP and W266rprp during vegetative growth. The average daily rate of increase in total carotenoid concentration in W266RPRP and in W266rprp was 12.7 and 1.3 mg·g-1 dry weight, respectively. A linear decrease in carotenoid concentration was measured for W266RPRP but not for W266rprp during postharvest storage. At 100 days after sowing, high-performance liquid chromatography analyses showed W266rprp had 20-fold lower concentrations of a-carotene and 50-fold lower concentrations of β-carotene in root tissue compared to W266RPRP. Levels of β-carotene and lutein in the first true leaves were reduced by ≈50% in W266rprp compared to W266RPRP. Results from this investigation suggest that the rp allele affects the concentration of root and foliage carotenoids, as well as the rate of carotenoid accumulation and degradation in carrot roots. The impact of the rp allele is far greater in root tissue than in foliage, suggesting it may act as a transcription factor or structural gene affecting primarily root carotenoid biosynthesis.

Predicting leaf area development in response to temperature in three tropical annual forage legumes

Ley legumes are an important option in nitrogen (N) management in cropping–livestock systems in Australia’s northern cropping region. The complexity of managing N and water in these systems is increasingly being aided by the use of crop models which require quantitative estimates of the various components of growth. A study to predict plant leaf area (PLA) of 3 tropical forage legumes as a function of temperature under irrigated conditions was conducted at Gatton, south-eastern Queensland. The legumes were phasey bean [Macroptilium lathyroides (L.) Urban.], vigna [Vigna trilobata (L.) Verdc.], and sesbania (Sesbania cannabina Retz.). The PLA was to be predicted by establishing a relationship between plastochron index (PI) and accumulated thermal time, and then between PLA and PI. Daily rate of increase in PI (DIPI) was strongly related to accumulated thermal time in all species, with DIPI higher for phasey bean (0.51 degree-days) and sesbania (0.54 degree-days) than for vigna (0.14 degree-days). At a plant density of 50 plants/m2, the relationship between PI and PLA was largely dependent upon the proportion of PLA originating from branches rather than from the main stem. In sesbania, &lt;20% of the PLA was contributed from leaves originating from branches, compared with about 40% in phasey bean and about 75% in vigna. The slope of the linear component of the relationship between PLA and PI in sesbania (85 cm2) was slightly less than the maximum leaf area per node recorded. The comparable slope for phasey bean was 57 cm2, being greater than the area of any individual leaf (40–50 cm2) because of the greater contribution of leaves originating from branches. In vigna, the very large contribution of leaves originating from branches to PLA, together with the slower DIPI for that species, resulted in the relationship between PI and PLA being much steeper than in either of the other species. The parameters developed for each species were successfully validated using independent data from other experiments in south-eastern Queensland. Increase in PLA in response to accumulated thermal time can be successfully predicted for these 3 tropical legumes at the set plant density. The successful prediction of PLA for legumes with a high degree of branching is of special significance, as it indicates that these methods may have application in predicting leaf growth in legumes which are being grazed and which have a number of active growing points. Nevertheless, the stability of the derived parameters needs to be assessed under a range of plant densities before they can be widely used to predict leaf area development in ley legumes.