Low Soil Moisture Levels Research Articles

Sex-specific phosphorus (P)-use and -acquisition in dioecious Populus euphratica as affected by soil moisture levels

Abstract Dioecious plants show sexual dimorphism in their phosphorus (P) availability responses. However, the understanding of sex-specific strategies for P utilization and acquisition under varying soil moisture levels remains unclear. Here, we assessed a range of root functional traits, soil P properties, total foliar P concentration ([P]), and leaf chemical P fractions – inorganic P ([Pi]), metabolite P ([PM]), lipid P ([PL]), nucleic acid P ([PN]), and residual P ([PR]) – as well as other leaf functional traits in female and male trees under different soil moisture levels (25% for high and 7% for low). Our results showed that females had larger specific root length (SRL) under well-watered conditions, resulting in greater root foraging capacity. This led to a 36.33% decrease in soil active inorganic P in the rhizosphere and a 66.86% increase in total foliar [P], along with all five foliar chemical P fractions ([Pi], [PM], [PL], [PN], and [PR]) compared to males. However, males exhibited significantly higher photosynthetic P utilization efficiency (PPUE) than females. Especially under low soil moisture levels, males exhibited a significant reduction in soil active organic P, coupled with a large increase in the exudation of soil phosphatases and carboxylates. Furthermore, the proportion of metabolite P in total foliar [P] was 41.96% higher in males than in females. Mantel and Spearman correlation analyses revealed distinct coordination and trade-offs between foliar P fraction allocation and below-ground P acquisition strategies between the two sexes. Leveraging these sex-specific strategies could enhance the resilience of dioecious populations in forest plantations facing climate-induced variability.

Analisis Ketersediaan dan Kebutuhan Air Sub DAS Rupit Menggunakan Remote Sensing dan GIS

The water balance of a river basin is crucial for estimating water availability to meet current and future domestic and economic water demand and supply. Parameters such as rainfall, temperature, evapotranspiration, deficit, and surplus soil water content determine the water availability of a river basin (DAS), influenced by factors like land use, soil type, seasonal variations, and other environmental factors. This research aims to estimate the water balance of the Rupit sub-watershed using the FJ Mock model. The Sentinel 1 image of the area was processed to produce a land use map. GIS modeling generated maps of rainfall, land use, soil, slope, morphometry catchment, excess moisture, evapotranspiration, and surface run-off. The analysis reveals that the highest rainfall and evapotranspiration occur in January, while other months average around 56 - 66 mm per month. Excess water during the wet months (November-March) leads to flooding, damaging infrastructure such as residential buildings, roads, and bridges. Conversely, April-October experiences water shortages. The annual weighted watershed deficit is 46.6 mm, with almost no surplus detected. Rainfall run-off simulations demonstrate significant and coherent watershed responses to rainfall patterns. Due to low rainfall and soil moisture levels from preceding months, March exhibits the highest discharge at 15.35 m3/s, with a run-off coefficient of 0.863.

Iot Based Smart Irrigation System using Artificial Intelligence

Sustainable agriculture depends on effective water management, and the Internet of Things (IoT) and artificial intelligence (AI) combine to offer a novel approach to irrigation process optimisation. In order to improve water utilization in agriculture, this research suggests a comprehensive system that includes buzzers, LCD displays, relays, water pumps, soil moisture sensors, AI algorithms, and water pumps. An AI algorithm at the centre of the system evaluates data collected in real time from field-installed soil moisture sensors. These sensors gather information on the soil’s moisture content, which offers important insights into the real water needs of the crops. After analysing this data, the AI programme decides how best to schedule irrigation. The system’s integration with a relay is intended to regulate when a water pump is activated. According to the suggestions of the AI algorithm, the relay provides accurate control over the irrigation operation, enabling on-demand watering. By avoiding over- irrigation and conserving water, this lowers the chance of waterlogging and associated problems. The system has an LCD display to improve user engagement and offer real-time feedback. Important details like irrigation status, soil moisture levels, and AI-driven suggestions are conveyed through the display. With the help of this function, farmers may monitor the system’s performance and make well-informed judgements. Furthermore, a buzzer is incorporated to deliver auditory notifications in the event of crucial occurrences, such low soil moisture levels or system faults.This guarantees timely resolution of problems that might affect crop health and system performance as a whole. A number of benefits are provided by the suggested AI-driven water management system, including improved agricultural output, water conservation, and operational effectiveness. Water scarcity and resource optimisation in irrigated fields are addressed by the system, which offers a comprehensive precision agriculture solution by utilising the capabilities of IoT devices, soil moisture sensors, relays, water pumps, buzzers, and LCD displays

Seasonal soil moisture thresholds inhibit bacterial activity and decomposition during drought in a tallgrass prairie

Soil moisture reductions during drought often inhibit soil microbial activity and inhibit decomposition rates by reducing microbial biomass or by altering microbial communities. Evidence suggests that soil water must drop below a critical threshold to inhibit microbial activity. Thus, it is likely that the seasonal timing of drought will determine the extent to which belowground processes are adversely impacted by drought. Specifically, the effects of drought might be minimal during cool, wet periods typical of late spring but dramatic during hot summer months with high evapotranspiration rates that lower soil moisture levels below the critical threshold. Here, we present results from a study designed to quantify the effect of drought on soil microbial abundance, community composition, and soil water diffusion across four months, and to then assess how drought impacts the microbial decomposition of leaf matter. We imposed a season‐long drought in a Wisconsin tallgrass prairie and measured soil moisture, bacterial composition and abundance, microbial respiration, and decomposition rates throughout the growing season. Bacterial communities varied considerably among dates, but drought did not affect either bacterial abundance or community composition. Microbial respiration declined significantly during periods of drought when soil pores likely became hydrologically isolated, ultimately reducing cumulative microbial respiration by 10%. The reduction in microbial activity in drought treatments caused a 50% decline in the decomposition of refractory material. Our study highlights that sublethal effects of drought on microbial communities, occurring only when soil moisture declined below a tolerance threshold, can have large impacts on microbial carbon release or decomposition, highlighting the need to incorporate such measures into future studies.

Effect of Incorporation Techniques and Soil Properties on NH3 and N2O Emissions after Urea Application

Ammonia (NH3) emissions affect the environment, the climate, and human health and originate mainly from agricultural sources like urea fertilizers. Such losses from urea fertilizer can be avoided by different application techniques like incorporation. However, the knowledge of the effect of these techniques on NH3 emissions is very limited and ambiguous since incorporation can also promote nitrous oxide (N2O) emissions. Three different principles of fertilizer incorporation methods were compared in three different soils (sandy, loamy, and clayey) at two moisture levels of 70% and 30% water-holding capacity (WHC), shallow mixing at 2 cm, injection with the slit technique at 5 cm, and deep complete incorporation at 5 cm simulating plow incorporation. The laboratory study was conducted with open dynamic incubation chambers where NH3 emissions were monitored with washing bottles while N2O emissions were studied with gas chromatographic (GC) measurements. The highest cumulative NH3 emissions occurred at low soil moisture levels in sandy soil (34% of the N applied). A maximum reduction in emissions by 87% was achieved with slit injection and 82% with deep injection compared to standard surface application. The reduction effect was positively related to increasing clay content. N2O emissions were delayed and highest from sandy soil. Overall, all urea incorporation techniques showed great potential for mitigating NH3 emissions on the clayey soil; for sandy and drier soils, only deeper or closed slot injection were consistently effective. However, connected to the surface incorporation at the higher moisture level, a relevant increase in N2O emissions compared to surface application was observed. Therefore, an increase in N2O emissions by urea incorporation may rule out specific incorporation techniques for NH3 emissions reduction from field-applied urea. In agricultural practice, a lower reduction in NH3 by fertilizer incorporation can be assumed in sandy soils or under dry soil conditions, as well as a more challenging technical implementation.

Oat companion seeding rate, herbicide, and irrigation effects on alfalfa stand establishment

AbstractAlfalfa (Medicago sativa L.) is often grown in water‐limited climates where available soil moisture is a key factor in determining the success or failure of new stand establishment. This study was conducted to determine optimal oat (Avena sativa L.) companion seeding rates for alfalfa establishment across a range of soil moisture levels. The effects of five oat seeding rates (0 [with and without herbicide], 11, 22, 45, and 89 kg ha−1) under five water levels on alfalfa stand establishment, forage yield, and nutritive value were evaluated at North Logan, UT, on a Millville silt loam soil (coarse‐silty, carbonatic, mesic Typic Haploxeroll) in 2019 and 2020. When soil moisture was adequate, first cut alfalfa stem density increased twofold as oat seeding rates decreased from 89 to 11 kg ha−1, but at low soil moisture levels stem density increased fivefold to sevenfold. At second cut, the only stem density differences that remained were at low irrigation. First cut forage yields were lowest in 0 kg ha−1 treatments and increased with increasing oat seeding rates. The opposite was true at second cutting, where yields were greatest where no oat had been planted. Yield differences were more extreme as soil moisture was reduced. The highest oat seeding rate had comparable weed control effects to the herbicide. Generally, the presence of either oat or weeds reduced forage nutritive value when compared to alfalfa alone. Reducing oat seeding rates or eliminating the companion crop altogether appears to improve alfalfa stand establishment when soil moisture is limited.

How Weather Affects over Time the Repeatability of Spectral Indices Used for Geological Remote Sensing

Geologic remote sensing studies often targets surface cover that is supposed to be invariant or only changing on a geological timescale. In terms of surface material characteristics, this holds for rocks and minerals, but only to a lesser degree for soils (including alluvium, colluvium, regolith or weathered outcrop) and not for vegetation cover, for example. A view unobstructed by clouds, vegetation or fire scars is essential for a persistent observation of surface mineralogy. Sensors with a continuous multi-temporal operation (e.g., Landsat 8 OLI and Sentinel-2 MSI) can provide the data volume needed to come to an optimal seasonal acquisition and the application of data fusion approaches to create an unobstructed view. However, the acquisition environment always changes over time, driven by seasonal changes, illumination changes and the weather. Consequently, the creation of an unobstructed view does not necessarily lead to a repeatable measurement. In this paper, we evaluate the influence of weather and resulting soil moisture conditions over a 3-year period, with alternating dry and wet periods, on the variance of several “geological” spectral indices in a semi-arid area. Sentinel-2 MSI data are chosen to calculate band ratios for green vegetation, ferric and ferrous iron oxide mineralogy and hydroxyl bearing alteration (clay) mineralogy. The data were used “as provided”, meaning that the performance of the atmospheric correction and geometric accuracy is not changed. The results are shown as time-series for selected areas that include solid rock, beach sand, bare soil and natural vegetation surfaces. Results show that spectral index values vary not only between dry and wet periods, but also within dry periods longer than 45 days, as a result of changing soil moisture conditions long after a last rain event has passed. In terms of repeatability of measurements, an overall low soil-moisture level is more important for long-term stability of spectral index values than the occurrence of minor rain events. In terms of creating an unobstructed view, we found that thresholds for NDVI should not be higher than 0.1 when masking vegetation in geological remote sensing, which is lower than what usually is indicated in literature. In conclusion, multi-temporal data are not only important to study dynamic Earth processes, but also to improve mapping of surfaces that are seemingly invariant. As this work is based on a few selected pixels, the obtained results should be considered only indicative and not as a numerical truth. We conclude that multi-temporal data can be used to create an unobstructed view, but also to select the data that give the most repeatability of measurements. Images selection should not be based on a certain number of days without rain in the days preceding data acquisition but aim for the lowest soil moisture conditions. Consequently, weather data should be incorporated to come to an optimal selection of remote sensing imagery, and also when analyzing multi-temporal data.

Disentangling temperature and water stress contributions to trends in isoprene emissions using satellite observations of formaldehyde, 2005–2016

Isoprene, produced by plants in response to multiple drivers, affects climate and air quality when released into the atmosphere. In turn, climate change may influence isoprene emissions through variations in occurrence and intensity of types of stress that affect plant functions. We test the effects of multiple drivers (temperature, precipitation, soil moisture, drought index, biomass, aerosols, burned fraction) on space retrievals of formaldehyde (HCHO) column concentrations, as a proxy for isoprene emissions, at global and regional scales over the period 2005–2016. We find declines in HCHO column concentrations over the study period across Europe, the Amazon Basin, southern Africa, and southern Australia, and increases across India, China, and mainland Southeast Asia. Temporal effects and the interactions among drivers are analyzed using generalized linear mixed-effects models to explain trends in HCHO column concentrations. Results show that HCHO column concentrations increase with temperature at the global scale and across the Amazon Basin and India–China regions, even under low levels of precipitation, provided that sufficient soil moisture can maintain vegetation functions and the associated isoprene emissions. Water availability sustains isoprene emissions in dry regions such as Australia, where HCHO column concentrations are positively associated with mean precipitation, with this relation intensifying at low levels of soil moisture. In contrast, isoprene emissions increase under water stress across the Amazon Basin and Europe, where HCHO column concentrations are negatively associated with levels of soil moisture and drought as calculated by the Standardized Precipitation–Evapotranspiration Index (SPEI). This study confirms the key role of temperature in modulating global and regional isoprene emissions and highlights contrasting regional effects of water stress on these emissions.

Arbuscular mycorrhizal fungi improve nutrient status of Commiphora myrrha seedlings under drought

In dryland ecosystems, tree and shrub seedling establishment, growth and survival are limited by access to water and nutrients. Arbuscular mycorrhizal fungi (AMF) increase seedling establishment and survival by enhancing nutrient and water acquisition. We executed a fully-factorial greenhouse experiment to determine the interactive effect of AMF (with and without), water deficit (four levels), and soil layer (topsoil and subsoil) on the biomass, growth, nutrient concentrations, and mycorrhizal root colonization of seedlings of Commiphora myrrha, a tree species that dominates large areas of dry forest and woodland in the Horn of Africa. Mycorrhizal seedlings had higher root and shoot biomass than non-mycorrhizal seedlings. They also had higher nutrient concentrations in root and shoot. Plant biomass was higher when plants were grown in topsoil at lower soil moisture levels. Mycorrhizal responsiveness was highest at lower soil moisture. The drought response index was higher for mycorrhizal than for non-mycorrhizal plants, indicating enhanced mycorrhizal benefits at lower water supply. Seedlings grew better in topsoil than in subsoil. Mycorrhizal colonization of roots of C. myrrha seedlings was higher with lower moisture and higher in topsoil than in subsoil. The increased performance of mycorrhizal C. myrrha indicates that mycorrhization is a major component of the adaptive strategy of seedlings of this species, similar to other species in these dryland deciduous ecosystems. We conclude that for restoration purposes with this species, nursery seedlings should be mycorrhized because of their enhanced growth performance.

Temperature and Soil Moisture Drive Coumestrol Concentration in Annual Medicago spp. in the Presence but Not Absence of Phoma Black Stem and Leaf Spot (Phoma medicaginis)

Studies were undertaken to determine the impact of environmental variables temperature (12.5/9.5, 20/17, 27/24 °C day/night) and soil moisture (100, 50% WHC), and their interaction with Phoma medicaginis infection, on production of the phytoestrogen coumestrol in annual Medicago rugosa cv. Paraponto and M. scutellata cv. Sava. Disease factors measured included leaf disease incidence/severity, petiole/stem disease incidence/severity, and leaf yellowing severity. Coumestrol levels were determined using gas chromatography–mass spectrometry (GC–MS). Increasing temperature from 12.5/9.5 °C to 27/24 °C in inoculated plants significantly (p < 0.05) increased coumestrol from 193 mg kg−1 to 390 mg kg−1, but there were no differences in coumestrol production across all three temperatures in uninoculated plants. Reducing soil moisture from 100% to 50% WHC at the highest temperature (27/24 °C) caused the greatest increase in coumestrol production from 156 to 269 mg kg−1 in inoculated plants. The greatest coumestrol production (600 mg kg−1) was under 27/24 °C/50% WHC for Sava infected with P. medicaginis and least coumestrol (1.6 mg kg−1) was Sava under 20/17 °C/50% WHC in the absence of P. medicaginis. Clearly, situations of higher temperatures in conjunction with lower soil moisture levels cause greatest elevation in coumestrol in the presence of P. medicaginis, levels far exceeding the animal risk threshold of 25 mg kg−1.

Grid-based simulation of soil moisture in the UK: future changes in extremes and wetting and drying dates

Soil moisture, typically defined as the amount of water in the unsaturated soil layer, is a central component of the hydrological cycle. The potential impacts of climate change on soil moisture have been less specifically studied than those on river flows, despite soil moisture deficits/excesses being a factor in a range of natural hazards, as well as having obvious importance for agriculture. Here, 1 km grids of monthly mean soil moisture content are simulated using a national-scale grid-based hydrological model, more typically applied to look at changes in river flows across Britain. A comparison of the soil moisture estimates from an observation-based simulation, with soil moisture deficit data from an operational system developed by the UK Met Office (Meteorological Office Rainfall and Evaporation Calculation System; MORECS), shows relatively good correspondence in soil drying and wetting dates, and in the month when soils are driest. The UK Climate Projections 2018 Regional projections are then used to drive the hydrological model, to investigate changes in occurrence of indicative soil moisture extremes and changes in typical wetting and drying dates of soils across the country. Analyses comparing baseline (December 1981–November 2011) and future (December 2050–November 2080) time-slices suggest large increases in the spatial occurrence of low soil moisture levels, along with later soil wetting dates, although changes to soil drying dates are less clear. Such information on potential future changes in soil moisture is important to enable the development of appropriate adaptation strategies for a range of sectors vulnerable to soil moisture levels.

Field response of N2O emissions, microbial communities, soil biochemical processes and winter barley growth to the addition of conventional and biodegradable microplastics

Microplastic contamination in agroecosystems is becoming more prevalent due to the direct use of plastics in agriculture (e.g., mulch films) and via contamination of amendments (e.g., compost, biosolids application). Long-term use of agricultural plastics and microplastic pollution could lead to soil degradation and reduced crop health due to the slow degradation of conventional plastics creating legacy plastic. Biodegradable plastics are more commonly being used, both domestically and in agriculture, to minimise plastic pollution due to their biodegradable nature. However, the influence of a biodegradable plastics on soil function at the field scale is largely unknown. We investigated the effect of conventional (polyethylene) and biodegradable (PHBV) microplastics on N2O emissions and soil biochemical processes in a field trial of winter barley. Microplastic was added to the soil at realistic levels (100 kg ha-1) for both conventional and biodegradable treatments. N2O emissions were measured throughout the growing season alongside key soil quality indicators (microbial community composition, ammonium, nitrate, moisture content, pH and EC). Overall, microplastic addition had no observable effect on crop yield, microbial communities or soil biochemical properties. Yet, we found cumulative N2O emissions were reduced by two-thirds following conventional microplastic addition compared to the no-plastic and biodegradable microplastic treatments. We believe this response is due to the lower soil moisture levels over the winter in the conventional microplastic treatment. Overall, the response of key soil parameters to microplastic addition show fewer negative effects to those seen in high dose laboratory mesocosm experiments. Thus, it is imperative that long-term field experiments at realistic dose rates be undertaken to quantify the real risk that microplastics pose to agroecosystem health.

Estimating soil moisture conditions for drought monitoring with random forests and a simple soil moisture accounting scheme

Abstract. Soil moisture is a key variable for drought monitoring, but soil moisture measurements networks are very scarce. Land-surface models can provide a valuable alternative for simulating soil moisture dynamics, but only a few countries have such modelling schemes implemented for monitoring soil moisture at high spatial resolution. In this study, a soil moisture accounting model (SMA) was regionalized over the Iberian Peninsula, taking as a reference the soil moisture simulated by a high-resolution land-surface model. To estimate the soil water holding capacity, the sole parameter required to run the SMA model, two approaches were compared: the direct estimation from European soil maps using pedotransfer functions or an indirect estimation by a machine learning approach, random forests, using as predictors altitude, temperature, precipitation, potential evapotranspiration and land use. Results showed that the random forest model estimates are more robust, especially for estimating low soil moisture levels. Consequently, the proposed approach can provide an efficient way to simulate daily soil moisture and therefore monitor soil moisture droughts, in contexts where high-resolution soil maps are not available, as it relies on a set of covariates that can be reliably estimated from global databases.

Seasonal ecosystem vulnerability to climatic anomalies in the Mediterranean

Abstract. Mediterranean ecosystems are particularly vulnerable to climate change and the associated increase in climate anomalies. This study investigates extreme ecosystem responses evoked by climatic drivers in the Mediterranean Basin for the time span 1999–2019 with a specific focus on seasonal variations as the seasonal timing of climatic anomalies is considered essential for impact and vulnerability assessment. A bivariate vulnerability analysis is performed for each month of the year to quantify which combinations of the drivers temperature (obtained from ERA5-Land) and soil moisture (obtained from ESA CCI and ERA5-Land) lead to extreme reductions in ecosystem productivity using the fraction of absorbed photosynthetically active radiation (FAPAR; obtained from the Copernicus Global Land Service) as a proxy. The bivariate analysis clearly showed that, in many cases, it is not just one but a combination of both drivers that causes ecosystem vulnerability. The overall pattern shows that Mediterranean ecosystems are prone to three soil moisture regimes during the yearly cycle: they are vulnerable to hot and dry conditions from May to July, to cold and dry conditions from August to October, and to cold conditions from November to April, illustrating the shift from a soil-moisture-limited regime in summer to an energy-limited regime in winter. In late spring, a month with significant vulnerability to hot conditions only often precedes the next stage of vulnerability to both hot and dry conditions, suggesting that high temperatures lead to critically low soil moisture levels with a certain time lag. In the eastern Mediterranean, the period of vulnerability to hot and dry conditions within the year is much longer than in the western Mediterranean. Our results show that it is crucial to account for both spatial and temporal variability to adequately assess ecosystem vulnerability. The seasonal vulnerability approach presented in this study helps to provide detailed insights regarding the specific phenological stage of the year in which ecosystem vulnerability to a certain climatic condition occurs.

Application of a Structured Water Generator for Crop Irrigation: Structured Water, Drought Tolerance, and Alteration of Plant Defense Mechanisms to Abiotic Stressors

A greenhouse study was conducted to enhance drought tolerance in velvet bean plants (Mucuns pruriens) using structured irrigation water. The study combined magnetized seed treatments with watering plants with structured water treatments. A closed-loop, water system was custom-built to generate the structured irrigation water. The custom water generator utilized two energy fields (magnetic and ultra-violet radiation) to generate the structured water. The objectives of the study were to: 1) determine the effects of a magnetized seed treatment on velvet bean plants, 2) determine the effects of magnetized water treatments on velvet bean plants, 3) determine the effects of water treated with a hydroxylated water generator on velvet bean plants, 4) determine the effects of three soil moisture levels on velvet bean plants. The plant responses included: 1) foliage gas exchange rates 2) soil moisture, 3) cumulative water volume for each plant, 4) plant water use efficiency, and 5) oven-dry foliage biomass. The foliage gas exchange responses showed that the magnetized seed and structured water treatments disassociated the relationships between photosynthesis, stomatal conductance, transpiration and internal carbon dioxide rates from soil moisture and leaf temperature. The optimal, combined magnetized seed and structured water treatments increased water savings from 32 to 52% over the unstructured water treatments, under the low soil moisture level. The maximum plant water use efficiency was 2.81, which occurred with a structured water treatment under the high soil moisture level. There was a 6.8 % decrease in oven-dry foliage biomass for the optimal magnetized seed and structured water treatment when compared with the control treatment. However, the tradeoff in reduced biomass was compensated with a 41% savings in water usage, 25% reduction in Pn, 34% reduction in stomatal conductance, and a 7% reduction in internal carbon dioxide under the low soil moisture level for the optimal magnetized seed and structured water treatment. The combined seed and water treatments fundamentally alter drought adaptation plant responses to water stress conditions which resulted in a significant reduction in irrigation water usage. The interactions between magnetized seed treatments and structured water treatments on plant stress physiology need to be further investigated to confirm these water conservation findings. Structured water generators should be evaluated for physicochemical water properties and stability of water in soil and plant matrices.

English

Studies have shown arbuscular mycorrhizal fungi (AMF) enhance phosphorus (P) uptake and drought tolerance in maize (Zea mays L.) grown in semiarid soils. However, little is known regarding the contribution of AMF to maize treated with different levels of phosphorus and grown in different soil moisture levels. This study was conducted to determine the effects of AMF (Glomus fasciculatum) inoculation on growth and P uptake of maize treated with different levels of soil P and soil moisture. Different P levels (0, 50, and 100 kg P ha-1) were applied on maize grown in soils with and without mycorrhizal fungi, and at different moisture levels producing -0.05, -0.4, -0.8, and -1.5 MPa of drought stress. Increasing P rates significantly (p < 0.05) reduced mycorrhizal colonization. Mycorrhizal colonization was higher under moderate than under lower soil moisture levels. Drought stress × soil P content × AMF inoculation interaction had significant (p < 0.05) effect on maize shoot and root dry weight and tissue P concentration. Overall, results of this study suggest that mycorrhizal inoculation enhances P uptake and maximizes maize biomass under low, moderate, and high soil moisture conditions without P applications. Except for the lowest soil moisture level (-1.5 MPa), mycorrhizal plants produced higher biomass, with greater tissue P content than nonmycorrhizal plants at all soil P and soil moisture levels. These results indicate that establishing efficacious AMF with maize could be an efficient alternative for growers than relying on P fertilizer application and its associated costs and environmental concerns. Keywords: Arbuscular Mycorrhiza Fungi, Drought Tolerance, Phosphorus Levels, Maize Plants.

Semar Sandy-app: monitoring system for sandy soil irrigation based on android application

Indonesia’s population increase leads to increase in food needs. The increasing need for food requires national food security. However the country faces the problem of agricultural land diminishing. Sandy soil is one of the suboptimal land that can be used for agricultural cultivation. Sandy soil leads to problems such as low water-holding capacity that will result in low levels of soil moisture. Soil moisture content is a very important factor in plant growth. Accordingly, we need an alternative solution to solve the problem. One of technology used in agriculture is an irrigation system. Therefore, the author proposes an idea in forms of Semar Sandy-App. Semar Sandy-App is a monitoring system as well as a system that provides direct supply water in the plant root zone. The system uses subsurface drip irrigation with perforated pipes then water comes out of the hole to wet the soil. This system can be a solution to optimize sandy soil through efficiency and effectiveness in providing water. The system can control and monitor the plant water requirements through the use of microcontroller that is connected directly to the android system, so it will increase agricultural productivity to support the availability of food for the community.

Effects of precipitation intermittency on vegetation patterns in semi-arid landscapes

Patterns of vegetation are a characteristic feature of many semi-arid regions. The limiting resource in these ecosystems is water, which is added to the system through short and intense rainfall events that cause a pulse of biological processes such as plant growth and seed dispersal. We propose an impulsive model based on the Klausmeier reaction–advection–diffusion system, analytically investigate the effects of rainfall intermittency on the onset of patterns, and augment our results by numerical simulations of model extensions. Our investigation focuses on the parameter region in which a transition between uniform and patterned vegetation occurs. Results show that decay-type processes associated with a low frequency of precipitation pulses inhibit the onset of patterns and that under intermittent rainfall regimes, a spatially uniform solution is sustained at lower total precipitation volumes than under continuous rainfall, if plant species are unable to efficiently use low soil moisture levels. Unlike in the classical setting of a reaction–diffusion model, patterns are not caused by a diffusion-driven instability but by a combination of sufficiently long periods of droughts between precipitation pulses and water diffusion. Our results further indicate that the introduction of pulse-type seed dispersal weakens the effects of changes to width and shape of the plant dispersal kernel on the onset of patterns.

Assessing the Response of Sesame to Inorganic and Organic Nutrient Sources

Sesame (Sesamum indicum. L) is one of the main sources of livelihoods in northern Uganda. However, its production is constrained by low soil fertility and moisture levels. A study was conducted at Serere, Uganda in 2013 and 2014 to investigate the effect of organo-mineral fertilizers on growth, seed yield and nutritional quality of sesame. The design of the experiment was a randomized complete block design with three replications. The treatments comprised: control (no soil amendment), mixtures of 4 crop residues each at (3 and 6 t/ha) and two rates of N, P and K. Finger millet husks (3 t/ha) plus lower fertilizer rate (30 kg N-25 kg P-40 Kg K/ha) had significantly higher seed yield of sesame; while finger millet husks (6 t/ha) plus higher fertilizer rate (60 kg N-50 kg P-80 Kg K/ha) significantly increased vegetative growth of sesame. Finger millet husks (6 t/ha) plus lower fertilizer rate had significantly higher seed crude protein content of sesame; while cowpea husks (3 t/ha) plus higher fertilizer rate and groundnut shells (3 t/ha) plus lower fertilizer rate produced significantly higher seed total ash and seed oil content of sesame, respectively. This study has demonstrated that application of a mixture of crop residues and inorganic fertilizers is the best treatment in enhancing growth, seed yield and nutritional seed quality of sesame.

Growth of prairie plants and sedums in different substrates on an experimental green roof in Mid-Continental USA

Many prairie plant habitats have similarities to the harsh and stressful growing environments of green roofs. In the Mid-Continent Region of the USA under a hot summer climate, little research has been done to study prairie plant communities and their performance with different substrates on green roofs. To explore more sustainable, diverse green roof ecosystems, this research assessed the first-year growth (June to October 2018) on an experimental green roof in the Flint Hills Ecoregion, which has some of the most extensive coverage of intact tallgrass prairie in North America. A mixture of plants (four native prairie grasses and two sedums) were grown on two substrates—a commercial substrate (rooflite® extensive 800) and a regionally mixed substrate (Kansas BuildEx)—placed at two depths: 6.0–13.0 cm (called the “shallow depth”) and 16.5–25.5 cm (called the “deep depth”). Plant height, coverage, survival, visual appearance, leaf stomatal resistance, and volumetric substrate water content were measured. Supplemental irrigation was provided equally to each experimental plot during the growing season. It was shown that the regionally mixed substrate had greater effect on plant height at the shallow depth and on coverage at the deep depth. However, volumetric water content was usually higher in the commercial substrate. Substrate type did not affect visual appearance and leaf stomatal resistance. Substrate moisture was inversely related to leaf stomatal resistance at low soil moisture levels. All prairie species survived, while Sedum reflexum had poor survival and coverage. Bouteloua curtipendula, Bouteloua gracilis, Schizachyrium scoparium, and Sedum rupestre performed well in a green roof community. Bouteloua dactyloides grew very well, but may be too aggressive when planted with sedums. The findings of this study will be of practical value for the design of mixed-species green roof systems in similar mid-continental regions with hot summers.