Vegetative Cycle Research Articles

The response of net primary productivity to climate change and its impact on hydrology in a water-limited agricultural basin.

Climate change has remarkably altered growing-season vegetation growth, but the impacts of vegetation variability on the regional hydrological cycle remain poorly understood. Exploring the relationships between climate change, vegetation dynamics, and hydrologic factors would contribute to the sustainable management of ecosystems. Here, we investigated the response of vegetation dynamics to climate change and its impact on hydrologic factors in a traditional agricultural basin with limited water resources in China, Nansi Lake Basin (NLB). To this end, CASA (Carnegie-Ames-Stanford Approach) model and the SWAT (Soil and Water Assessment Tool) model were applied to simulate the net primary productivity (NPP), evapotranspiration (ET), and soil water in the growing season (April-October) from 2000 to 2016. Results showed that the mean growing-season NPP (NPPGS) exhibited an ascending trend at a rate of 2.93 g C/m2/year during the 17-year period. The intra-annual variation of NPPGS displayed two peaks in May and July, respectively. The first peak in May was accompanied by relative deficits in soil water, which might inhibit vegetation productivity. Precipitation was the principal climatic factor controlling NPPGS dynamics in the water-limited NLB. The positive influence of temperature on NPPGS was relatively weak, and even future warming could negatively affect ecosystem productivity in the south-central regions of the NLB. Furthermore, a strongly positive relationship between NPPGS and ET was detected, suggesting that increasing NPP in the future might stimulate the rise in ET and then exacerbate drought at the watershed scale. This study provides an integrated model for a comprehensive understanding of the interaction between vegetation, climate, and hydrological cycle, and highlights the importance of water-saving agriculture for future food security.

Intragenomic Conflict between Knob Heterochromatin and B Chromosomes Is the Key to Understand Genome Size Variation along Altitudinal Clines in Maize.

In maize, we studied the causes of genome size variation and their correlates with cultivation altitude that suggests the existence of adaptive clines. To discuss the biological role of the genome size variation, we focused on Bolivian maize landraces growing along a broad altitudinal range. These were analyzed together with previously studied populations from altitudinal clines of Northwestern Argentina (NWA). Bolivian populations exhibited numerical polymorphism for B chromosomes (Bs) (from 1 to 5), with frequencies varying from 16.6 to 81.8 and being positively correlated with cultivation altitude. The 2C values of individuals 0B (A-DNA) ranged between 4.73 and 7.71 pg, with 58.33% of variation. The heterochromatic knobs, detected by DAPI staining, were more numerous and larger in individuals 0B than in those with higher doses of Bs. Bolivian and NWA landraces exhibited the same pattern of A-DNA downsizing and fewer and smaller knobs with increasing cultivation altitude, suggesting a mechanistic link among heterochromatin, genome size and phenology. The negative association between the two types of supernumerary DNA (knob heterochromatin and Bs), mainly responsible for the genome size variation, may be considered as an example of intragenomic conflict. It could be postulated that the optimal nucleotype is the result of such conflict, where genome adjustment may lead to an appropriate length of the vegetative cycle for maize landraces growing across altitudinal clines.

Estimating heterogeneous wildfire effects using synthetic controls and satellite remote sensing

Wildfires have become one of the biggest natural hazards for environments worldwide. The effects of wildfires are heterogeneous, meaning that the magnitude of their effects depends on many factors such as geographical region, climate and land cover/vegetation type. Yet, which areas are more affected by these events remains unclear. Here we present a novel application of the Generalized Synthetic Control (GSC) method that enables quantification and prediction of vegetation changes due to wildfires through a time-series analysis of in situ and satellite remote sensing data. We apply this method to medium to large wildfires (> 1000 acres) in California throughout a time-span of two decades (1996–2016). The method's ability for estimating counterfactual vegetation characteristics for burned regions is explored in order to quantify abrupt system changes. We find that the GSC method is better at predicting vegetation changes than the more traditional approach of using nearby regions to assess wildfire impacts. We evaluate the GSC method by comparing its predictions of spectral vegetation indices to observations during pre-wildfire periods and find improvements in correlation coefficient from R2 = 0.66 to R2 = 0.93 in Normalized Difference Vegetation Index (NDVI), from R2 = 0.48 to R2 = 0.81 for Normalized Burn Ratio (NBR), and from R2 = 0.49 to R2 = 0.85 for Normalized Difference Moisture Index (NDMI). Results show greater changes in NDVI, NBR, and NDMI post-fire on regions classified as having a lower Burning Index. We find that on average, wildfires cause a 25% initial decrease in the vegetation index (NDVI) and a larger than 80% drop in wetness indices (NBR and NDMI) after they occur. The GSC method also reveals that wildfire effects on vegetation can last for more than a decade post-wildfire, and in some cases never return to their previous vegetation cycles within our study period. We also find that the dynamical effects vary across regions and have an impact on seasonal cycles of vegetation in later years. Lastly, we discuss the usefulness of using GSC in remote sensing analyses.

Moisture and temperature influences on nonlinear vegetation trends in Serengeti National Park

While long-term vegetation greening trends have appeared across large land areas over the late 20th century, uncertainty remains in identifying and attributing finer-scale vegetation changes and trends, particularly across protected areas. Serengeti National Park (SNP) is a critical East African protected area, where seasonal vegetation cycles support vast populations of grazing herbivores and a host of ecosystem dynamics. Previous work has shown how non-climate drivers (e.g. land use) shape the SNP ecosystem, but it is still unclear to what extent changing climate conditions influence SNP vegetation, particularly at finer spatial and temporal scales. We fill this research gap by evaluating long-term (1982–2016) changes in SNP leaf area index (LAI) in relation to both temperature and moisture availability using Ensemble Empirical Mode Decomposition and Principal Component Analysis with regression techniques. We find that SNP LAI trends are nonlinear, display high sub-seasonal variation, and are influenced by lagged changes in both moisture and temperature variables and their interactions. LAI during the long rains (e.g. March) exhibits a greening-to-browning trend reversal starting in the early 2000s, partly due to antecedent precipitation declines. In contrast, LAI during the short rains (e.g. November, December) displays browning-to-greening alongside increasing moisture availability. Rising temperature trends also have important, secondary interactions with moisture variables to shape these SNP vegetation trends. Our findings show complex vegetation-climate interactions occurring at important temporal and spatial scales of the SNP, and our rigorous statistical approaches detect these complex climate-vegetation trends and interactions, while guarding against spurious vegetation signals.

Potential of C-band Synthetic Aperture Radar Sentinel-1 time-series for the monitoring of phenological cycles in a deciduous forest

Annual time-series of the two satellites C-band SAR (Synthetic Aperture Radar) Sentinel-1A and 1B data over five years were used to characterize the phenological cycle of a temperate deciduous forest. Six phenological metrics of the start (SOS), middle (MOS) and end (EOS) of budburst and leaf expansion stage in spring, and the start (SOF), middle (MOF) and end (EOF) of leaf senescence in autumn were extracted using an asymmetric double sigmoid function (ADS) fitted to the time-series of the ratio (VV/VH) of backscattering at co-polarization VV (vertical–vertical) and at cross polarization VH (vertical-horizontal). Phenological metrics were also derived from other four vegetation proxies (Normalized Difference Vegetation Index NDVI time-series from Sentinel-2A and 2B images, and in situ measurements of NDVI measurements, Leaf Area Index LAI and litterfall temporal dynamics). These estimated phenological metrics were compared to phenological observations obtained by visual observations from the ground, achieved using binoculars by three inter-calibrated observers, on a bi-weekly basis during the budburst and weekly during the senescence. We observe a decrease in the backscattering coefficient (σ0) at VH cross polarization during the leaf development and the expansion phase in spring and an increase during the senescence phase, contrary to what is usually observed on various types of crops. In vertical polarization, σ0VV shows very little variation throughout the year. S-1 time-series of VV/VH ratio provide a good description of the seasonal vegetation cycle allowing the estimation of spring and autumn phenological metrics. Estimates provided by VV/VH of budburst dates using MOS criterion differ by approximately 8 days on average (mean average deviation) from phenological observations. During senescence phase, estimates using MOF criterion are later and deviate by about 20 days from phenological observations of leaf senescence while the differences are of the order of 2 to 4 days between the phenological observations and estimates based on in situ NDVI and LAI time-series, respectively. A deviation of about 7 days, comparable to that observed during budburst, is obtained between the estimates of senescence (MOF) from S-1 and those determined from the in situ monitoring of litterfall. While in spring, leaf emergence and expansion described by LAI or NDVI explain the increase of VV/VH (or the decrease of σ0VH), during senescence, S-1 VV/VH is decorrelated from LAI or NDVI and is better explained by litterfall temporal dynamics. This behavior resulted in a hysteresis phenomenon observed on the relationships between VV/VH and NDVI or LAI. For the same LAI or NDVI, the response of VV/VH is different depending on the phenological phase considered. This study shows the high potential offered by Sentinel-1 SAR C-band time-series for the detection of forest phenology, thus overcoming the limitations caused by cloud cover in optical remote sensing of vegetation phenology.

Ecological impacts of fungal wood decay types: A review of current knowledge and future research directions

AbstractI summarize current knowledge about the ecosystem functions of wood decomposition in forests with a particular focus on the effects of fungal wood decay types (traditionally categorized into white‐, brown‐, and soft‐rot) on the community composition of saproxylic organisms, forest tree regeneration, and carbon sequestration. Deadwoods of different decay types show markedly different physicochemical and biological properties. High carbohydrate availability in white‐rotted wood promotes the activities of nitrogen‐fixing bacteria; thus white‐rotted wood is a good dietary source for many wood‐eating invertebrates. In contrast, brown‐rotted wood is unattractive to saproxylic communities due to the high recalcitrance of accumulated lignin, low nutrient content, and low pH. Nevertheless, some species have adapted to these conditions and form distinctive communities on brown‐rotted wood. Tree seedlings that are associated with brown‐rotted wood are symbiotic with arbuscular and ericoid mycorrhizal fungal species, but not ectomycorrhizal species. Thus, the diversity of fungal communities associated with a variety of wood decay types produces habitat diversity for saproxylic communities and promotes biodiversity in forest ecosystems. Wood decay type also affects carbon sequestration in forests as brown‐rotted wood might be more instrumental in soil organic matter accumulation than white‐rotted wood. An important aspect of wood decay type is that the wood decay activities of fungi can have indirect long‐lasting cascading impacts on forest biodiversity by altering the physicochemical properties of deadwood. Including the effects of wood decay type in ecological models is thus important for predicting the long‐term dynamics of biodiversity, vegetation, and carbon cycling in forest ecosystems.

Impact of microclimatic conditions and resource availability on spring and autumn phenology of temperate tree seedlings.

Summary Microclimatic effects (light, temperature) are often neglected in phenological studies and little information is known about the impact of resource availability (nutrient and water) on tree’s phenological cycles.Here we experimentally studied spring and autumn phenology in four temperate trees in response to changes in bud albedo (white‐painted vs black‐painted buds), light conditions (nonshaded vs c. 70% shaded), water availability (irrigated, control and reduced precipitation) and nutrients (low vs high availability).We found that higher bud albedo or shade delayed budburst (up to +12 d), indicating that temperature is sensed locally within each bud. Leaf senescence was delayed by high nutrient availability (up to +7 d) and shade conditions (up to +39 d) in all species, except oak. Autumn phenological responses to summer droughts depended on species, with a delay for cherry (+7 d) and an advance for beech (−7 d).The strong phenological effects of bud albedo and light exposure reveal an important role of microclimatic variation on phenology. In addition to the temperature and photoperiod effects, our results suggest a tight interplay between source and sink processes in regulating the end of the seasonal vegetation cycle, which can be largely influenced by resource availability (light, water and nutrients).

The response of dry bean to water stress at various growth cycles in a semi-arid region

Poor irrigation management is resulted from some reasons such as lack of information relevant to the crop water use. That kind of information is necessarily prerequisites for both planners and producers to obtain irrigation program to minimize the yield losses under water stress conditions. A two-year, 2013-2014 growing season, field experiment was performed to determine the response of dry bean to the water deficiency in different growth stages at Konya plain of Turkey. The study was organized as randomized complete block design with three replications. Vegetative (V), reproductive (R), and pod filling-maturation (P) three plant growth cycles as were examined with including rain-fed total eight irrigation treatments were researched. A 100% crop water requirement (VRP) was considered full-irrigation treatment. Irrigation was not performed during vegetative, reproductive, and pod filling-maturation cycles or during a combination of those stages in other treatments. In results, depending on the irrigation treatments, actual evapotranspiration (ETa) for 2013 and 2014 varied from 104 to 544 mm and from 110 to 558 mm, respectively. The average crop coefficients ( K c ) among the years were 0.75 for vegetative, 1.01 for reproductive, and 0.82 for pod filling-maturation stages. Depending on irrigation time, as decreasing the irrigation water resulted reducing seed yield. It was obvious that higher seed yield as well as yield components obtained full irrigation at entire growing season, which was preferable. An alternative to full irrigation in whole growth stages particularly in areas with insufficient water resources, performing full irrigation till initial of the filling-maturation cycle and then ending irrigation can be highly recommended as ideal, as it resulted water saving of 38%, and rise 27% in irrigation water use efficiency (IWUE) as well as 20% seed yield loss by comparison to full irrigation.

Biofuels Reserve Controlled Wildfire Regimes Since the Last Deglaciation: A Record From Gonghai Lake, North China

AbstractWildfire activity is an important activity in evolution of vegetation and carbon cycling. Whether wet weather will suppress wildfire or promote them by increasing fuel reserves during the Holocene is not clear. We obtained a record of black carbon from a sediment core spanning the last 14.8 kyr from Gonghai Lake, in North China. There is a close relationship between the timing of wildfire activity and vegetation development driven by the East Asian summer monsoon intensity. On a millennial timescales, wet climatic conditions provide a sufficient biofuels reserve, in the same period wildfire increase; thus, the regional potential biofuels reserve is shown to be an important controlling of regional wildfire activity in the monsoon region of China, under natural conditions. We infer that with the strengthening of Asian summer monsoon caused by global warming, the wildfire carbon emission in Asian monsoon region may increase in the future.

Qualitative characteristics of the fungus Cyclocybe aegerita strains 2229, 2230, 2231 IBK under industrial cultivation conditions

Poplar mushroom is characterised by attractive fruiting bodies in terms of appearance and taste. Cyclocybe aegerita mushrooms are also known to contain unique substances, including proteins, polysaccharides, and aromatic substances with proven nutritional value and medicinal effects. However, the lack of a sound cultivation technology using available plant material limits the saturation of the domestic market with mushrooms of this species. Three strains of C. aegerita from the IBK National Collection of Agaricale Cultures of the Institute of Ecology and Natural Resources were studied for their potential introduction into commercial culture. It was determined that strains 2230 and 2231 have a vegetation cycle of 42 days compared to 46-64 days for the previously studied strains. The highest yield in the experiment was obtained for strain 2231, which ranged from 217 to 220 g per kilogram of a substrate over three cultivation cycles. The biological efficiency of the strains according to the results of the first wave of fruiting ranged from 20.2 (2229) to 60.4% (2231), which is consistent with the published data of other researchers. The appearance and parameters of the fruiting bodies of the strains, which differed in both the colour of the pileus and the size, were described in detail. Under microclimatic conditions of the experiment, strains 2230 and 2231 had a rich brown colour of pilei, while the formed fruit bodies of strain 2229 were distinguished by a pleasant milky cream colour. The largest fruiting bodies in terms of weight were obtained by cultivation of strain 2229 (7.5 ± 0.4 g), which is on average 2 g higher than the weight of mushrooms of other studied strains. The highest fruiting bodies were discovered in strain 2230 having a height of 91.0 ± 1.8 mm, which also had the widest pilei with a diameter of 29.5 ± 0.9 mm. The largest stem diameter, which reached an average of 10.8 ± 0.3 mm, was detected in the fruiting bodies of strain 2229. This study investigated the variability of morphological traits and identified trends in the number of fruiting bodies of a certain size in the total volume of collected mushrooms, which facilitates the design of packaging and marketing campaigns

Unmodified cassava starches with high phosphorus content

Our study was based on the fact that physiological changes in the plant resulting from the growth conditions alter the properties of the starch. An experimental trial was installed with cassava plants in poor phosphorus soil. A part of plants received phosphate fertilization at a level three times higher than the recommended dose, in order to provide high availability of phosphorus in the soil. The plants grew for two years and the starches were isolated at three times in the second vegetative cycle. The starches had A-type X-ray pattern. Starches isolated from cassava plants grown in soils with high phosphorus had increases of more than 100% in the content of bound phosphorus, which caused changes in the size of the granules, amylose, swelling power, solubility, pasting and thermal properties. These results indicate possibilities of increasing the commercial value of native cassava starch due to the expansion of use, considering the range of uses of phosphate starches for food and non-food purposes.

Effects of Different Types of Fertilizers on Rice Productivity in the Irrigated Perimeter of Toula (Niger)

AIM: Assessment of various fertilizers type effects on rice productivity in Niger.
 Study Design: The experiment was laid by using a complete randomized block design with different types of fertilizers and was replicated four times.
 Place and Duration of Study: The field experiment was conducted during the dry and wet season of 2020 on the irrigated perimeter of Toula (Niger).
 Methodology: The experiment was performed with four treatments in complete randomized blocks. The treatments applied are: T1=Bokashi, T2=Compost, T3=Biochar and T4=NPK-Urea. The monitored parameters were the rice plant development cycle and agronomic characteristics. Observations of the crop evolution during the experimentation were recorded at regular intervals. The significance of treatment impact was examined by the statistical test. 
 Results: The results showed that bio-fertilizers had significant effects on 1000 grain weight and the length of the vegetative cycle. As for the chemical treatments, the effects were significant on most of the rice growth parameters (height, number of grains per panicle, number of tillers per rice plant) as well as on paddy and feed biomass yield. These results also showed a positive correlation between rice growth parameters and yield irrespective of the type of treatment.

Severidade do míldio da cebola em plantio direto fertirrigado sob parcelamento de nutrientes e densidades populacionais

The study analyzed the relationship between nutrient splitting (N and K) and population density on the severity of onion downy mildew under no-tillage cultivation within the conditions of Alto Vale do Itajaí (Brazil). For this purpose, field trials were conducted in the years 2017, 2018 and 2019, in Ituporanga (Brazil). The treatments corresponded to four plant densities (300, 400, 500 and 600 thousand plants ha-1) submitted to applications of nitrogen (150 kg N ha-1) and potassium (127.5 kg K2O ha-1). The doses of nutrients were distributed along the vegetative cycle of the culture via fertigation on a weekly, biweekly and monthly, based on the absorption curve of nutrients for the cultivar Empasc 352 - Bola Precoce. In fertigated no-tillage systems, the distribution of nutrients (N and K) does not influence the severity of downy mildew. Mildew severity increases linearly with increasing population density especially from 500 thousand plants per ha-1.

Bayoud and Belaat diseases of date palm (Phoenix dactylifera L.) in Figuig oasis of Morocco

From 2016 to 2017, a survey was carried out during four vegetative cycles of date palm tree (Phoenix dactylifera L.) in Figuig oasis of Morocco. Two types of date palm culture were surveyed, that is traditional and modern plantations. The aim of the survey was mainly to explore date palm diseases, their incidence and geographic distribution in Figuig oasis. Results revealed the presence of two major diseases: the harmful Bayoud disease and Belaat disease. The rate of contamination of each disease reached respectively 3.38% and 3.31%. Spatial distribution of each disease varies for each one both in traditional and modern plantations, as shown in kernel density maps of diseases infestation. Bayoud disease spread more in traditional oasis. In fact, 60.96% of infested date palm trees by Bayoud disease were recorded in traditional plantations. On the contrary, in modern ones, Belaat disease was the main disease and the rate of infestation reached 67.13%. The survey also focuses on the influence of occurred farming practices in infested plantations which are often characterized by a lack of phytosanitary treatment, fertilization and weeding. Furthermore, pruning, gravity irrigation and the presence of underlying culture were also identified as increasing factors for pathogens dissemination.

Modelagem matemática e propriedades termodinâmicas na secagem do quiabo

Okra is a vegetable that stands out agronomically due to its fast vegetative cycle, of high yield, besides presenting considerable nutritional value. Due to its composition and to be consumed still green, its useful life is quite short, requiring some conservation process to maintain acceptability. In this sense, the objective was to dry the okra in slices, approximately 2 mm thick, at temperatures of 50, 60, 70 and 80 ° C, adjust mathematical models to the experimental data and determine the diffusion coefficients, activation energy and thermodynamic properties. It was observed that the increase in drying temperature at 30 ° C reduced the total process time by 50.55%. Among the mathematical models tested, the Midilli model presented the best parameters of adjustments to the experimental data. The effective diffusion coefficients increased with increasing temperature, in the order of 10-11 m2 s-1, and their dependence on temperature was described by the Arrhenius Equation, which indicated an activation energy of 26.12 kJ mol-1. The enthalpy and entropy values ​​decreased with the increase of the drying temperature, while the Gibbs free energy was increased in the temperature range evaluated.

Estimating and Monitoring Land Surface Phenology in Rangelands: A Review of Progress and Challenges

Land surface phenology (LSP) has been extensively explored from global archives of satellite observations to track and monitor the seasonality of rangeland ecosystems in response to climate change. Long term monitoring of LSP provides large potential for the evaluation of interactions and feedbacks between climate and vegetation. With a special focus on the rangeland ecosystems, the paper reviews the progress, challenges and emerging opportunities in LSP while identifying possible gaps that could be explored in future. Specifically, the paper traces the evolution of satellite sensors and interrogates their properties as well as the associated indices and algorithms in estimating and monitoring LSP in productive rangelands. Findings from the literature revealed that the spectral characteristics of the early satellite sensors such as Landsat, AVHRR and MODIS played a critical role in the development of spectral vegetation indices that have been widely used in LSP applications. The normalized difference vegetation index (NDVI) pioneered LSP investigations, and most other spectral vegetation indices were primarily developed to address the weaknesses and shortcomings of the NDVI. New indices continue to be developed based on recent sensors such as Sentinel-2 that are characterized by unique spectral signatures and fine spatial resolutions, and their successful usage is catalyzed with the development of cutting-edge algorithms for modeling the LSP profiles. In this regard, the paper has documented several LSP algorithms that are designed to provide data smoothing, gap filling and LSP metrics retrieval methods in a single environment. In the future, the development of machine learning algorithms that can effectively model and characterize the phenological cycles of vegetation would help to unlock the value of LSP information in the rangeland monitoring and management process. Precisely, deep learning presents an opportunity to further develop robust software packages such as the decomposition and analysis of time series (DATimeS) with the abundance of data processing tools and techniques that can be used to better characterize the phenological cycles of vegetation in rangeland ecosystems.

Genetic diversity of Algerian sorghum (Sorghum bicolor (L.) Moench) landraces by using agro-morphological markers

The present study was performed to assess the native Algerian sorghum germplasm,20 accessions originating from the South of Algeria and one introduced commercial hybrid were evaluated for 12quantitative agro-morphological markers. Analysis of variance revealed significant differences (p ˂ 0.05) between accessions for all characters. Comparison of means by Duncan’s least significant test separate accessions into several homogeneous groups. It was found that sorghum landrace Ai19 showed the highest scores of final height (317 cm) and biomass dry yield (38 tons), Ai13 showed shortest vegetative cycles by 75 days to 50% flowering and the highest exploration of water to accumulate dry matter. The first two-principle component showed together more than 76% of the total variation. Clustering analysis showed that the 20 accessions were divided into four groups, mainly differentiated by forage production, days to 50% of flowering, final height, tillering capacity and leaf characteristics. The current study demonstrates that the characterization of the entire collection revealed a great phenotypic variability within the accessions and showed those that have markers of agronomic interest. Agro-morphological traits were very practical in detecting variation between local and commercial hybrid sorghum. Landraces Ai19, Ai13 and Fr1, through their valuable agro-morphological markers, could be used in sorghum genetic breeding programs.

Genetic diversity of Algerian sorghum (Sorghum bicolor (L.) Moench) landraces by using agro-morphological markers

The present study was performed to assess the native Algerian sorghum germplasm,20 accessions originating from the South of Algeria and one introduced commercial hybrid were evaluated for 12quantitative agro-morphological markers. Analysis of variance revealed significant differences (p ˂ 0.05) between accessions for all characters. Comparison of means by Duncan’s least significant test separate accessions into several homogeneous groups. It was found that sorghum landrace Ai19 showed the highest scores of final height (317 cm) and biomass dry yield (38 tons), Ai13 showed shortest vegetative cycles by 75 days to 50% flowering and the highest exploration of water to accumulate dry matter. The first two-principle component showed together more than 76% of the total variation. Clustering analysis showed that the 20 accessions were divided into four groups, mainly differentiated by forage production, days to 50% of flowering, final height, tillering capacity and leaf characteristics. The current study demonstrates that the characterization of the entire collection revealed a great phenotypic variability within the accessions and showed those that have markers of agronomic interest. Agro-morphological traits were very practical in detecting variation between local and commercial hybrid sorghum. Landraces Ai19, Ai13 and Fr1, through their valuable agro-morphological markers, could be used in sorghum genetic breeding programs.

Cultivar diversification of banana production in Brazil

Bananas fruits are widely consumed in the world. In Brazil, the role of agriculture activities in the economy and society is huge, especially for banana farmers. The most popular variety of bananas in Brazil are Prata, Grand Naine, Williams and Nanicão; however, all of them have at least one undesirable trait such as height, yield, vegetative cycle, pests and diseases tolerances, drought or cold resistance and fruit quality. This literature review aims to evaluate agronomic performance and fruit quality of new genotypes of the Prata and Cavendish subgroups, and to make further recommendations on high quality genotypes to Brazilian banana producers. Therefore, a literature review of previously acquired data was conducted and the outcomes indicated genotypes’ adaptability to specific region that assessed vegetative and productive attributes of new cultivars, in comparison to most commercially exploited ones, which have already shown high vulnerability to pests and diseases. These outcomes will then facilitate banana producers the opportunity to select the most stable and adaptable genotypes according to environmental conditions.

Sun-induced fluorescence and near-infrared reflectance of vegetation track the seasonal dynamics of gross primary production over Africa

Abstract. The carbon cycle of tropical terrestrial vegetation plays a vital role in the storage and exchange of atmospheric CO2. But large uncertainties surround the impacts of land-use change emissions, climate warming, the frequency of droughts, and CO2 fertilization. This culminates in poorly quantified carbon stocks and carbon fluxes even for the major ecosystems of Africa (savannas and tropical evergreen forests). Contributors to this uncertainty are the sparsity of (micro-)meteorological observations across Africa's vast land area, a lack of sufficient ground-based observation networks and validation data for CO2, and incomplete representation of important processes in numerical models. In this study, we therefore turn to two remotely sensed vegetation products that have been shown to correlate highly with gross primary production (GPP): sun-induced fluorescence (SIF) and near-infrared reflectance of vegetation (NIRv). The former is available from an updated product that we recently published (Sun-Induced Fluorescence of Terrestrial Ecosystems Retrieval – SIFTER v2), which specifically improves retrievals in tropical environments. A comparison against flux tower observations of daytime-partitioned net ecosystem exchange from six major biomes in Africa shows that SIF and NIRv reproduce the seasonal patterns of GPP well, resulting in correlation coefficients of >0.9 (N=12 months, four sites) over savannas in the Northern and Southern hemispheres. These coefficients are slightly higher than for the widely used Max Planck Institute for Biogeochemistry (MPI-BGC) GPP products and enhanced vegetation index (EVI). Similarly to SIF signals in the neighboring Amazon, peak productivity occurs in the wet season coinciding with peak soil moisture and is followed by an initial decline during the early dry season, which reverses when light availability peaks. This suggests similar leaf dynamics are at play. Spatially, SIF and NIRv show a strong linear relation (R>0.9; N≥250 pixels) with multi-year MPI-BGC GPP even within single biomes. Both MPI-BGC GPP and the EVI show saturation relative to peak NIRv and SIF signals during high-productivity months, which suggests that GPP in the most productive regions of Africa might be larger than suggested.