Soil Texture Research Articles

Assessing the Influence of Soil Physical Properties on the Puddling Quality: A Comprehensive Review

Puddling is a crucial step in rice cultivation, extensively practiced by farmers in Asia for its role in softening soil, aiding in transplanting, and enhancing water and nutrient management. However, the alteration of soil properties by puddling raises concerns about its long-term sustainability. This comprehensive review systematically examines the impact of puddling on soil parameters such as soil texture, bulk density, penetration resistance, hydraulic conductivity, puddling index, and percolation rate. By synthesizing existing literature, the review aims to inform sustainable agricultural practices and effective soil management strategies amidst escalating global concerns. The complexities of puddling's influence on soil structure underscore the need to consider variables like soil texture and aggregate stability. Sustainable practices such as organic manure application offer potential solutions to address puddling-induced compaction, thereby enhancing soil quality and rice production efficiency. Optimizing tillage methods and improving hydraulic conductivity are essential components of effective soil management strategies for sustainable rice cultivation. Additionally, assessing puddling quality through indices like the puddling index and optimizing percolation rates are vital steps toward improving water management and overall productivity in rice farming.

Humic Acid-Functionalized Lignin-Based Coatings Regulate Nutrient Release and Promote Wheat Productivity and Grain Quality.

The rational application of fertilizers is crucial for achieving high crop yields and ensuring global food security. The use of biopolymers for slow-release fertilizers (SRFs) development has emerged as a game-changer and environmentally sustainable pathway to enhance crop yields by optimizing plant growth phases. Herein, with a renewed focus on circular bioeconomy, a novel functionalized lignin-based coating material (FLGe) was developed for the sustained release of nutrients. This innovative approach involved the extraction and sustainable functionalization of lignin through a solvent-free esterification reaction with humic acid─an organic compound widely recognized for its biostimulant properties in agriculture. The primary objective was to fortify the hydration barrier of lignin by reducing the number of its free hydroxyl groups, thereby enhancing release control, while simultaneously harnessing the agronomic benefits offered by humic acid. After confirming the synthesis of functionalized lignin (FLGe) through 13C NMR analysis, it was integrated at varying proportions into either a cellulosic or starch matrix. This resulted in the creation of five distinct formulations, which were then utilized as coatings for diammonium phosphate (DAP) fertilizer. Experimental findings revealed an improved morphology and hardness (almost 3-fold) of DAP fertilizer granules after coating along with a positive impact on the soil's water retention capacity (7%). Nutrient leaching in soil was monitored for 100 days and a substantial reduction of nutrients leaching up to 80% was successfully achieved using coated DAP fertilizer. Furthermore, to get a fuller picture of their efficiency, a pot trial was performed using two different soil textures and demonstrated that the application of FLGe-based SRFs significantly enhanced the physiological and agronomic parameters of wheat, including leaf evolution and root architecture, resulting in an almost 50% increase in grain yield and improved quality. The results proved the potential of lignin functionalization to advance agricultural sustainability and foster a robust bioeconomy aligning with the premise "from the soil to the soil".

Climate Suitability Analysis of Robusta Coffee and Its Projections in South Sumatera Province

Climate suitability will support the growth of a plant such as Robusta coffee. This study aims to analyze the suitability of the Robusta coffee plant climate and its projection in South Sumatra. Climate suitability is assessed based on the weighting of air temperature, rainfall, number of dry months, altitude, soil texture, and slopes. This study used observation data on rainfall and air temperature at 48 rain post points in the Robusta coffee farming area. The projection uses scenarios shared socioeconomic pathways (SSP) 2-4.5 and 5-8.5 of the MIROC6 model with three projection periods of 2021-2030, 2031-2040, and 2041-2050. The results showed that baseline period 35% of the area as a very suitable class and 65% in fairly suitable class. Based on the projected results of scenario SSP2-4.5 period 1 to 3 have the same percentage of area, that is 91% in very suitable class and 9% in fairly suitable class. The projected results of the scenario SSP5-8.5 show an improvement but not better than scenario SSP2-4.5. The percentage of area very suitable class for periods 1 to 3 of 89%, 50%, and 85% respectively. Keywords: Climate suitability, Projection, Robusta coffee, SSP2-4.5, SSP5-8.5.

Modelling, quantification and estimation of the soil water erosion using the Revised Universal Soil Loss Equation with Sediment Delivery Ratio and the analytic hierarchy process models

AbstractThis research used the Revised Universal Soil Loss Equation (RUSLE) with Sediment Delivery Ratio (SDR) model. The analytic hierarchy process (AHP) method, while also incorporating the use of a geographic information system (GIS) and remote sensing (RS) to predict the annual soil loss rate and spatialise the processes of water erosion at the scale of the Loukkos Watershed, Morocco. The RUSLE model and AHP parameters were estimated using RS data, and the erosion vulnerability zones were determined using GIS. We used five parameters, including precipitation erosivity, soil erodibility, slope length and steepness, vegetation cover, and soil erosion control practices in the RUSLE. For the AHP technique, we used seven geo‐environmental factors, including annual average precipitation, drainage density, lineament density, slope, soil texture, land use/land cover and landform maps. The results of RUSLE indicated that the average annual soil loss varied from 0 to 2388.27 . The total estimated annual potential soil loss was approximately 40 790 220.11 , and a sediment yield estimated by RUSLE‐SDR was 8 647 526.66 , equivalent to 6.65 Mm3. This value is very close to the measured value of 6.81 Mm3, for a difference of 0.16 Mm3. Furthermore, the results of the AHP indicate that the soil erosion potential index varies from 0 to 0.205315 . Overall, nearly 13.7% of the area suffered from severe soil erosion exceeding 50 . Approximately 80% of the Loukkos Watershed area experienced only slight erosion, while the remaining 6% incurred moderate erosion. Integrating GIS and RS into the RUSLE model and AHP helped us robustly estimate the extent and degree of erosion risk. Territorial decision‐makers should adopt our results to develop soil conservation strategies, water management plans and other necessary soil and water conservation measures for this region.

Assessment of Physico-chemical Properties of Soil from Various Regions of Different Taluk of Pathanamthitta District in the State of Kerala, India

The assessment of Physico-Chemical Properties of Soil from Various Regions of Different Taluk of Pathanamthitta District of Kerala in 2023-24 was a valuable endeavour. A total of 27 samples were collected at profile depths of 0-15, 15-30, and 30-45. It is interesting to note the variations in soil colour between dry and wet conditions, ranging from light brown to dark reddish brown.The soil textural class was identified as Sandy clay Loam, and the sand, silt and clay percentage varied from 45.18% to 50.64%, 17.21% to 20.70%, 30.91% to 34.61%. Bulk Density was varied from 1.08 Mg m-3 to 1.28 Mg m-3. The Particle Density varied from 2.02 Mg m-3 to 2.55 Mg m-3. The Pore Space (%) ranged from 40.18% to 50.62%. The Water Retaining Capacity (%) ranged from 39.19 to 48.98%. The pH value ranged from 4.9 to 6.9. The Electrical Conductivity ranged from 0.03 to 0.30 dS m-1. The value of total Organic Carbon (%) varied from 0.16 to 1.68 %. The available Nitrogen content of soil ranged from 119.45 to 286.07 kg ha-1. The available Phosphorus content of soil ranged from 13.23 to 64.20 kg ha-1. Available Potassium content of soil ranged from 100.80 to 382.40 kg ha-1. Exchangeable Calcium content of soil ranged from 1.7(meq 100g-1) to 9.1(meq 100g-1). Exchangeable Magnesium content of soil ranged from 0.23 (meq 100g-1) to 0.74(meq 100g-1). The Sulphur content of soil ranged from 0.03 to 0.44 kg ha-1. The findings revealed minor increases in bulk and particle density with depth, yet the overall physical condition of the soil seems favourable for plant growth. It is evident that the soils are slightly acidic but meet the acceptable EC limit. The high levels of Organic Carbon are promising, while Nitrogen is lower and Phosphorus and Potassium levels are moderate to high. However, secondary nutrients like Calcium, Magnesium, and Sulphur are relatively low. Nutrient levels appear to be influenced by soil depth, with leaching due to higher precipitation levels in the area contributing to nutrient deficiencies. The results suggest that improvements can be made by implementing strategies such as cover crops, green manure, legume cultivation, mulching, and specific cropping systems to address leaching concerns.

Negative Effect of Soil Compaction and Investigation of Its Relation with Soil Physiochemical Properties in Mechanization Farming System

The primary source of soil compaction is weight bearing down on the soil, which occurs frequently on agricultural land due to foot movement, livestock tramples, or the heavy weight of farm equipment. The primary cause of significant soil compaction is the driving of heavy machinery over moist soils. In this paper, the negative side of soil compaction and its influence on soil physical and chemical characteristics at the Awash Melkassa farm field located in Ethiopia were investigated. Compaction of soil test was taken at three different depths which are 10 cm, 20 cm, and 30 cm with the help of a hydraulically operated cone penetrometer integrated into the tractor. The three depths were expanded into 15 sample locations (designated as point A to point O) to collect 35 data points on soil compaction using a hydraulic-powered Spot-on digital soil cone penetrometer across a 0.6-hectare farmland area. A correlation analysis was conducted on the 15 sample points (A to O) to assess soil compaction in the field. In addition, soil samples were collected from specific farm locations at depths ranging from 0 to 10 cm, 10–20 cm, and 20–30 cm for subsequent physical and chemical tests in the laboratory. During the harvesting season, sample location A exhibited the highest soil compaction values, reaching 6,159 kPa, while the lowest values were observed at sample point F, measuring 327 kPa. For the seeding season, the sample point B showed the highest soil compaction values at 6,052 kPa, while the lowest values were recorded at sample point K, measuring 563 kPa. Moreover, the data indicates a consistent increase in soil compaction with depth during both experimental seasons. The laboratory test for soil texture revealed that the soil composition was classified as a clay loam, consisting of 36.7% sand, 30.3% clay, and 33% silt. The moisture content ranged from a high of 16.04% to a low of 13.97%. In addition, it was observed that total organic carbon, organic matter, and total nitrogen levels tend to rise with increased soil compaction, and conversely, decrease as soil compaction decreases. This study’s insights are invaluable for agricultural mechanization. Given the substantial weight of farm machinery, comprehending soil properties and their correlation with compaction rates is imperative for optimizing farming practices.

Assessment of Soil Spatial Variability in Agricultural Ecosystems Using Multivariate Analysis, Soil Quality Index (SQI), and Geostatistical Approach: A Case Study of the Mnasra Region, Gharb Plain, Morocco

Accurate assessment of soil quality is crucial for sustainable agriculture and soil conservation. Thus, this study aimed to assess soil quality in the agricultural ecosystem of the Mnasra region within the Gharb Plain of Morocco, employing a comprehensive approach integrating multivariate analysis and geostatistical techniques. Thirty soil samples were collected from the surface layers across thirty selected sites. The results showed significant variations in soil properties across the study area, influenced by factors such as soil texture, parent material, and agricultural practices. Pearson correlation and principal component analysis (PCA) were employed to analyze the relationships among soil properties and compute the Soil Quality Index (SQI). The SQI revealed values ranging from 0.48 to 0.74, with 46.66% of sampled soils classified as “Good” and 53.33% as “Fair”. Geostatistical analysis, particularly ordinary kriging (OK) interpolation and semivariogram modeling, highlighted the spatial variability of soil properties, aiding in mapping soil quality across the landscape. The integrated approach demonstrates the importance of combining field assessments, statistical analyses, and geospatial techniques for comprehensive soil quality evaluation and informed land management decisions. These findings offer valuable insights for decision-makers in monitoring and managing agricultural land to promote sustainable development in the Gharb region of Morocco.

Effect of Soil Texture on Agricultural Machine Performance in Sylhet, Bangladesh.

Soil texture is one of the primary soil physical properties that largely affects agricultural machine performance. Before implementing an agricultural machine at the farm level, it is important to test the machine to gain an understanding of its technical functionality and economic viability to get the best output from it. The research was carried out to assess how soil texture influences the performance of machinery, aiming to determine the effectiveness of agricultural equipment on a particular type of land. Soil samples were collected from nine different fields, and their textures were determined using hydrometer analysis. To correlate soil textural classes with machine performance, machinery data—effective field capacity, forward speed, and field efficiency—were calculated by operating a combine harvester on the study areas during the harvesting season of Boro rice. Two types of soil were identified: loamy sand and sandy loam. The findings of the study showed that machine efficiency has a positive correlation with sand proportion and a negative correlation with clay and silt fractions. It was observed that soil with loamy sand-type textural classes demonstrated better field efficiency, higher effective field capacity, and higher forward speed compared to sandy loam soil. Small and irregularly shaped fields also caused variation in performance. The study identified significant variation in speed between these two types of soils but no significant effect on effective field capacity or field efficiency at the 5% level of significance. The outcomes of this research will help farmers make informed decisions when selecting appropriate equipment for their agricultural operations.

Application of Phototrophic Microorganisms as Biofertilizer Isolated from South Gujarat, India

Chemical fertilizers have impact on soil texture and also affects the plant growth upto certain level. Due to overuse of chemicals, soil profile has major changes in Gujarat. South Gujarat having major agricultural practices in vegetables, fruits and Sugarcane. The phtotrophic microorganisms isolated from wetland of Nanikakrad situated near to Navasari. The impact of algal biofertilizers on the growth of Solanum melongena, Solanum lycopersicum, and Capsicum annum was researched through a pot study. Plant height, width, and the number of leaves at different time intervals were measured, and soil nutrient levels were analysed by measuring Carbon, Nitrogen, Phosphorus and Sulphur content. A total of 30 pots (10 for each plant species) were used, and eight different isolates were applied across treatment. Two pots of plants were maintained as controls; one including chemical fertilizers. Plant growth was significantly promoted by isolates I1 and I2 in Solanum melongena, while in Solanum lycopersicum and Capsicum annum, all treatments improved growth compared with controls. Chlorophyll content was significantly increased in chemical fertilized Solanum melongena, whereas in Solanum lycopersicum and Capsicum annum, I1 significantly increased Chlorophyll content. These findings underline the potential of algal biofertilizers as a smarter, safer alternative to chemical fertilizers that promise to drive sustainable growth in agriculture.

Ecological risk and spatial distribution, sources of heavy metals in typical purple soils, southwest China

The identification and quantification of the ecological risks, sources and distribution of heavy metals in purple soils are essential for regional pollution control and management. In this study, geo-accumulation index (Igeo), enrichment factor (EF), pollution index (PI), potential ecological risk index (RI), principal component analysis (PCA) model and geographical detector (GD) were combined to evaluate the status, ecological risk, and sources of heavy metals (HMs) in soils from a typical purple soil areas of Sichuan province. The results showed that the average contents of As, Cd, Cr, Cu, Hg, Ni, Pb and Zn in purple soil were 7.77, 0.19, 69.5, 27.9, 0.077, 30.9, 26.5 mg/kg and 76.8 mg/kg, and the Igeo, EF and RI of topsoil Hg and Cd in designated area was the highest, and the average contents of Hg and Cd in topsoil were obviously greater than respective soil background value in Sichuan province and purple soil. The hot spots for the spatial distribution of 8 HMs were mainly focused in the southwest and northeast of the designated area, and there were also significant differences for 8 HMs distribution characteristics in the profile soil. Cu comes from both anthropogenic and natural sources, Zn, Ni and Cr mainly come from natural sources, but As, Pb, Hg and Cd mainly derived from human activities. GD results showed that soil texture (X18), altitude (X4), total nitrogen (TN), clay content (X3), sand content (X2) and silt content (X1) had the greatest explanatory power to 8 HMs spatial differentiation.This study provides a reference for understanding the status and influencing factors of HM pollution in typical purple soil, and lays a theoretical foundation for the environmental treatment of purple soil in China.

Use of electrical resistivity tomography measurements for investigation of different grouting materials for very shallow geothermal applications within varying seasonal conditions; Applied on a geothermal earth-air heat exchanger system

To achieve the current climate targets, heat pump systems like very shallow geothermal applications are gaining ground. However, the dimensioning of these ground coupled systems is soil-dependent and thus subject to significant differences in efficiency. Furthermore, the thermal properties of the grouting materials are essential for heat transfer in the direct vicinity of the geothermal application. To provide a non-invasive assessment of relevant soil and grouting characteristics, electrical resistivity tomography (ERT) measurements were performed.In this case, the surrounding of an Earth Air-Heat Exchanger – system (EAHE) with different grouting materials (fine sand and fine sand with bentonite) was investigated. For investigation the electrical resistivity (ER) of initial and modified soil conditions were measured regarding soil texture and moisture content. Thereby, the different grouting materials are clearly identified. Thus, based on the ERT measurements, a characterisation of key soil and grouting material properties for applications focusing on heat transfer in soil has been carried out.Furthermore, the depth of soil disturbance due to the EAHE installation could have been traced.Due to a monitoring over different season (February and May) changes in raw ER data could have been ascribed to temperature changes.

The effect of soil moisture content and soil texture on fast in situ pH measurements with two types of robust ion-selective electrodes

Abstract. In situ soil pH measurements with ion-selective electrodes (ISEs) are receiving increasing attention in soil mapping for precision agriculture as they can avoid time-consuming sampling and off-site laboratory work. However, unlike the standard laboratory protocol, in situ pH measurements are carried out at lower and varying soil moisture contents (SMCs), which can have a pronounced effect on the sensor readings. In addition, as the contact with the soil during in situ measurements should be relatively short, effects of soil texture could be expected because texture controls the migration of protons to the electrode interface. This may be exacerbated by the fact that the electrodes used for in situ measurements are made of less sensitive but more robust materials as compared to the standard glass electrode. Therefore, the aim of the present study was to investigate the effect of soil moisture and soil texture on pH measurements using robust antimony and epoxy-body ISEs pressed directly into the soil for 30 s. The SMC was gradually increased from dry conditions to field capacity. A wide range of soil texture classes were included, with sand, silt, and clay contents ranging from 16 % to 91 %, 5 % to 44 %, and 4 % to 65 %, respectively. An exponential model was fitted to the data to quantify the relationship between SMC and pH. The results show that an increase in SMC causes a maximum increase in pH of approximately 1.5 pH units, regardless of the type of pH ISE used. Furthermore, for sandy soil textures, a rather linear relationship between pH and SMC was observed, whereas, with decreasing mean particle diameter (MPD), the model had a pronounced exponential shape, i.e., a greater pH increase at low SMC and a plateau effect at high SMC. With increasing SMC, the pH values asymptotically approached the standard pH measured with a glass electrode in 0.01 M CaCl2 (soil : solution ratio of 1:2.5). Thus, at high SMC, subsequent calibration of the sensor pH values to the standard pH value is negligible, which may be relevant for using the sensor pH data for lime requirement estimates. The pH measurement error decreases exponentially with increasing soil moisture and increases with decreasing MPD. Using a knee point detection, reliable pH values were obtained for SMC > 11 %, irrespective of the pH ISE used. An analysis of the regression coefficients of the fitted exponential model showed that the maximum pH increase also depends on soil texture; i.e., the influence of soil moisture variation on the pH value increases with decreasing MPD. Moreover, the concavity of the exponential curve increases with decreasing MPD.

Source Analysis and Bioavailability of Soil Cadmium in Poyang Lake Plain of China Based on Principal Component Analysis and Positive Definite Matrix Factor

In order to identify the source and bioavailability of soil Cd in the alluvial geological high background area, 3799 topsoil samples and 140 root soil samples were collected from the Jiulong area on the south bank of Poyang Lake, Jiangxi Province. The results confidently indicate that the range of topsoil Cd content is 0.02~8.12 ppm, with an exceedance rate of 14.6%. It is noteworthy that exceedance points were mostly distributed in quaternary sediments. The geostatistical analysis clearly shows that the spatial distribution characteristic of topsoil Cd is higher in the north and lower in the south. The area with extremely high values (>90% quantile) is predominantly located in the tidal flat and low-lying areas of the mainstream of the Xinjiang River. The PCA analysis confirms that the main source of topsoil Cd is man-made activities related to industry and mining. Soil Cd is primarily derived from upstream industrial and mining discharge (58.5%), as revealed by the PMF model analysis. The active Cd content in root soil is 77 ppb, with higher levels observed in the north and lower levels in the south. These findings suggest a significant risk of Cd diffusion along the upstream stream and deposition in the low-lying parts of the north. It is worth noting that Cd’s bioavailability and active forms in paddy fields are the highest, which can have a detrimental effect on food security. The correlation analysis suggests that genetic sources primarily control the bioavailability of soil Cd, followed by soil physicochemical properties such as SOC, Fe-Al oxides, and soil texture. Preventing source pollution and cutting off water system transmission are effective methods for preventing and controlling soil Cd pollution. These methods ensure the safety of cultivated land in the lakeside area of Poyang Lake Plain.

Predicting wheat yield gap and its determinants combining remote sensing, machine learning, and survey approaches in rainfed Mediterranean regions of Morocco

Wheat plays a crucial role in Morocco’s food security, economic stability, and livelihoods of farming communities. Assessing key vegetation indices (as yield predictors), along with understanding potential yield, yield gap, and major determinants for this gap at regional and national scales, is vital for improving food security with resilience in variable climatic conditions. Analysing the yield gap and its causes during drought and optimal weather conditions can reduce crop failure risks and enhance productivity specially in variable rainfed production systems. This study aimed to develop scalable methodology to predict field- and landscape-level yield and yield gaps for wheat and their underlying causes examplifying Morocco’s rainfed production environment combining remote sensing, machine learning, and ground information. By analysing six vegetation indices (EVI2, CGVI, MSR, NDVI, OSAVI, and RVI) derived from Sentinel-2 satellite imagery (10 m resolution) over three successive growing seasons (2018–2019, 2019–2020, and 2020–2021), the study employed advanced vegetation index models for accurate prediction of wheat yields and yield gaps at plot and on a larger regional scale within the Rabat-Sale-Kenitra region. To identify the determinants of yield gap, climate and soil datasets were merged with crop management information and the random forest model was fine-tuned and assessed for each season and cumulatively. The findings highlighted that RVI, GCVI, and NDVI vegetation indices were particularly effective in predicting wheat yields, showing the highest R2 and the lowest prediction errors (RMSE). Such predictive methodologies are crucial for policymakers to proactively plan and mitigate risk minimization and adaption plans at regional and national levels. The models predicted rainfed potential yields of 5.99, 1.53, and 4.66 t ha−1, with corresponding yield gap of 3.38, 0.73, and 1.58 t ha−1 for the seasons of 2018/2019 (favorable); 2019/2020 (drought) and 2020/2021 (favorable), respectively. Across three periods, critical factors determining yield include soil moisture, total rainfall during the crop growing period, evapotranspiration, and soil texture and carbon content. To minimize drought risks and maximize benefits during variable rainfall conditions, it is essential to implement pre-season drought forecasts, customize seeding dates based on soil moisture, adopt technologies that enhance soil moisture retention, and utilize climate-adapted farming practices in the semi-arid and arid rainfed regions.

A comprehensive analytical and computational assessment of soil water characteristics curves in Atlantic Canada: Application of a novel SelectKbestbased GEP model

For sustainable agriculture, irrigation is one of the most important management practices in a semi-arid climate. Determining the site-specific soil type-based irrigation water requirements requires the development of a soil water characteristics curve (SWCC). This study focuses on exploring the suitability of analytical SWCC models based on the observed data of SWCC developed using the pressure membrane apparatus. A novel SelectKbest gene expression programming (GEP) model is used to create the generalized machine learning SWCC model for Atlantic Canadian soils. The composite soil samples with representative soil textures of loamy sand, loam, and sandy loam are collected from the selected locations in Prince Edward Island and New Brunswick provinces of Canada. The suitability of models at three regions shows that at all sites, including PEI-1 (loam soil) 1, PEI-2 (loamy sand), and NB-3 (sandy loam) if SWCC data has four measured suction potential levels, then McBee & Bomb and Tani exponential models may be selected. Van Genuchten, double exponential, Ruso, Kosuki, and Gardner's four parameters models should be a good choice for five-section potential. Similarly, for six measured suction potential values, the Fredlund & Xing, Omuto, and Van Genuchten models having parameters should be selected for determining the optimum soil hydraulic parameters. The HydroMe program with Brooks and Corey, four, and five parameters Van Genuchten models performed well. The HydroMe program is calibrated and validated with standard RETC for selected regions of Atlantic Canada, which suggests that the HydroMe program is flexible in developing efficient agricultural water management algorithms. Various performance metrics like R2 and RMSE are employed to assess the robustness of the model. A generalized SWCC model (R2=0.976 and RMSE=0.04) is developed using a novel SelectKbest-based GEP modeling approach for Atlantic Canadian soils. These novel approaches can significantly improve site-specific agricultural water management and decision support systems.

Mitigative translocation of Singleton Mint Bush (Prostanthera cineolifera) on the NSW North Coast: Effects of soil texture, horticultural practice and bushfire on the translocation outcome

SummaryTranslocation of the threatened species Singelton Mint Bush (Prostanthera cineolifera R.T.Baker & H.G.Sm.) was carried out for a highway project on the New South Wales North Coast to mitigate development impact on this species. The translocation aimed to augment an existing population with propagated plants to compensate for cleared plants and conduct field research to better understand the effects of soil properties, horticultural practices and a wildfire on translocation results. A novel soil seedbank and fire method applied ex‐situ was used to propagate plants for introduction. After an initial attempt at site‐wide introduction resulted in widespread mortality of seedlings from a wilt disease, three plot‐based experiments were carried out to examine how disease incidence was related to spatial variation in soil properties and horticultural practices. The experiments showed that relatively subtle changes in the clay and sand content of soil strongly affected susceptibility of Singelton Mint Bush seedlings to wilt disease; 12 month old seedlings performed much better than 6 month old seedlings; plants propagated from seed performed better than cuttings, and most of the recipient site represented unsuitable habitat for Singelton Mint Bush. Sufficient Singelton Mint Bush seedlings were established after 3 years, but after a bushfire, the translocated cohort recruited poorly from seed, so that after 6 years, <10% of the total Singelton Mint Bush population in the recipient site was of translocated origin and >90% of in‐situ (pre‐translocation) origin. Lessons learnt from the translocation project were that: (i) microhabitat is as important as macrohabitat in selecting a translocation recipient site; (ii) short‐term survival may not be a reliable indicator of a self‐sustaining population; (iii) translocation incorporating designed experiments can greatly improve understanding of how certain factors influence species performance and (iv) horticultural practices can be as important as ecology in determining the translocation outcome.

The de‐domestication of Ornithopus sativus Brot. to develop cultivars with physical dormancy (hardseed)

AbstractOrnithopus sativus Brot. (French serradella) is a forage legume that is well adapted to acidic coarse textured soils (sands) which are characterized by poor nutrition and an inability to retain water. During the process of domestication of O. sativus, there was an unintentional loss of seed physical dormancy (PY) thus compromising its self‐regeneration after a cropping interval. Through mass screening of seed, we identified for the first time that heritable sources of PY exist in three populations of O. sativus. This rare genetic material was then incorporated into suitable genetic backgrounds of differing maturity through targeted hybridization. We demonstrated that the heritability of PY was dominant in the population of 97ZAF5sat but inconsistently recessive in the population of cv. Emena. Flowering time was variable in each source population, with a large variation in time to emergence of first flowers (95–175 days). Selection for early flowering maturity was heritable and stable. F6 generations selected for PY in different maturity classes were then evaluated in situ to establish whether PY would allow a proportion of seeds to survive in the soil through consecutive seasons exposed to a Mediterranean climate. The breeding lines FHS3, 7 and 23 remained dormant, thus viable, in the soil for up to 3 years, indicating the likelihood that O. sativus with PY could survive and persist in a ley farming system. The de‐domestication program in O. sativus has resulted in commercially successful cultivars (most recently cv. Fran2o) suited to sustainable dryland agriculture in a Mediterranean climate.

Simulating bare soil evaporation for undisturbed soil cores—Using HYDRUS 3D simulation on X‐ray µCT determined soil macrostructures

AbstractEvaporation of soil water depends not only on climatic conditions, soil surface roughness, soil texture, and soil hydraulic properties but also on the soils’ macrostructure. Evaporation is characterized by water losses over time for a defined soil volume, where soils are assumed to be homogeneous in texture and structure. In this technical note, we investigated the potential and limitations of 3D modeling of evaporation processes on 250 cm3 soil cores with structural features ≥480 µm determined by X‐ray computed tomography. For this, we used isothermal Richards equation as the main governing equation, accounting also for isothermal vapor flow. We simulated two evaporation experiments with same soil texture but contrasting macrostructures, that is, the spatial arrangement of voxels classified as soil matrix and air‐filled voids, of a ploughed and non‐ploughed grassland soil with HYDRUS 3D. In both simulations, we fixed the potential evaporation rates to the experimental rates and evaluated simulation results with measured matric potential data at two depths (1.25 cm and 3.75 cm) continuously recorded at 10 min intervals. We could show that the simulations of bare soil evaporation were able to predict the tensiometer dynamics and water losses for the full experimental time of 7 days. The simulation provided unique spatial information of water content and flow velocities as a function of time, which are important when studying the effect of air‐filled macropores, macro‐connectivity of soil matrix, and water dynamics on soil evaporation.

1H-NMR Spectroscopy Coupled with Chemometrics to Classify Wines According to Different Grape Varieties and Different Terroirs

In this study, 1H-NMR spectroscopy coupled with chemometrics was applied to study the wine metabolome and to classify wines according to different grape varieties and different terroirs. By obtaining the metabolomic fingerprinting and profiling of the wines, it was possible to assess the metabolic biomarkers leading the classification (i.e., phenolic compounds, aroma compounds, amino acids, and organic acids). Moreover, information about the influence of the soil in shaping wine metabolome was obtained. For instance, the relationship between the soil texture and the content of amino acids and organic acids in wines was highlighted. The analysis conducted in this study allowed extraction of relevant spectral information not only from the most populated and concentrated spectral areas (e.g., aliphatic and carbinolic areas), but also from crowded spectral areas held by lowly concentrated compounds (i.e., polyphenols). This may be due to a successful combination between the parameters used for data reduction, preprocessing and elaboration. The metabolomic fingerprinting also allowed exploration of the H-bonds network inside the wines, which affects both gustatory and olfactory perceptions, by modulating the way how solutes interact with the human sensory receptors. These findings may have important implications in the context of food traceability and quality control, providing information about the chemical composition and biomolecular markers from a holistic point of view.

Yield Maximization of Rice (Oryza sativa) through Integrated Nutrient Management

This experiment was conducted on a permanent layout at the west byde of BRRI farm, Gazipur during T. Aman 2019 to Boro 2021-22 to find out the suitable management practices for yield maximization of rice and soil health. Seven treatments in Randomized Complete Block (RCB) Design with three replications were imposed and each treatment was assigned in 5m × 4m sized plot. The treatments combinations were T1= Absolute Control (No nutrient supply), T2 = BRRI dose N-P-K-S@83-17-53-12 kg ha-1 in T. Aman and 138-21-75-21 kg ha-1 in Boro season, T3= Soil Test Based (STB) Fertilizer Dose N-P-K-S @ 67-10-40-10 kg ha-1 in T. Aman and 134-16-75-10 kg ha-1 in Boro, T4 = STB dose + 1 t ha-1 Cowdung, T5 = STB dose + 1 t ha-1 Poultry manure, T6 = STB dose + 1 t ha-1 Vermicompost and T7 = STB dose + 0.33 t ha-1 CD + 0.33 t ha-1 PM + 0.33 t ha-1 VC. Thirty-days old seedling of BRRI dhan87 in T. Aman and fourty-two days old seedling of BRRI dhan89 in Boro season were transplanted at 20 cm × 20 cm spacing in both seasons. All manures, soil and plant samples analysis were done by the help of soil Science Division BRRI, Gazipur. Initial soil (0-15 cm depth) properties were: soil texture, clay loam; pH, 6.94; organic Carbon, 1.59%; Nitrogen, 0.18%; Phosphorus, 21.88 ppm and Potassium, 0.19meq/100g soil. Thirty days old seedling of BRRI dhan87 in T. Aman and 42 days old seedling of BRRI dhan89 in Boro season were transplanted at 20cm x 20cm spacing. Grain yield, tiller number, panicle number, plant height and grain number were significantly affected by the different integrated nutrient management during both T. Aman and Boro season. Grain yield, tiller number, panicle number, plant height and grain number were significantly affected by the different nutrient management in both T. Aman and Boro season. Poultry manure related treatments and BRRI recommended dose performed better than the others in all the parameter except 1000-grain weight. On the other hand, Absolute Control (No nutrient supply) produced the lowest result. Every parameter, Poultry manure treatments have been performed the best. STB dose with one t ha-1 poultry manure is better for maximization of rice yield.