Optimum Soil Moisture Research Articles

Performance Evaluation of Rain Hose Irrigation System for Enhancing Water Productivity in Kerala, India

A field experiment was conducted to evaluate the performance of rain hose irrigation system in terms of discharge variation, moisture distribution, and uniformity coefficient at different operating pressures. The study revealed a linear relationship between operating pressure and discharge for rain hose irrigation system. Specifically, at pressures of 0.5 and 1.0 kg cm- ², increased pressure correlated well with higher soil moisture content along with 20% to 23% increase in moisture with greater water-infiltration depth. The distribution of moisture was found to be more uniform at higher pressures, achieving a uniformity coefficient of 74%. This uniformity was enhanced in the multilateral rain hose irrigation system with reduced spatial variation as compared to the single lateral system. As operating pressure increased, discharge per unit length also showed an increase, alongside the throw distance. The rain hose system is particularly advantageous for closely-spaced and shallow-rooted crops like onion, groundnut, and leafy green vegetables, ensuring consistent and high flow rates. The study suggested that regulating operating pressure is crucial for optimizing soil moisture levels, as higher pressures lead to deeper water infiltration. Notably, at a pressure of 1.5 kg cm- ², the system performed the best, yielding the optimum results for irrigation efficiency. In summary, the rain hose irrigation system proved effective at higher operating pressures, providing a reliable method for achieving uniform water distribution and adequate soil moisture for crops, which is essential for effective irrigation management.

Pengaruh Kadar Air Dan Porositas Tanah Terhadap Efisiensi Pemberian Pupuk Pada Tanaman Jagung

This study aims to analyze the effect of soil moisture content and soil corrosiveness on fertilizer efficiency in maize crops. The method employed is an experimental approach with treatments of different soil moisture levels (low, medium, and high) and the measurement of soil corrosiveness. The results showed that optimal soil moisture positively contributes to plant growth, with higher average plant height and yields at high moisture levels compared to low moisture levels. Additionally, soils with low corrosiveness are better at retaining water and nutrients, thereby enhancing fertilizer uptake efficiency. The interaction between soil moisture and soil corrosiveness was found to significantly affect crop yields. This study concludes that effective management of soil moisture and corrosiveness can improve fertilizer efficiency, and it provides recommendations for farmers to adopt precise fertilization strategies for sustainable agriculture practices.

Role of Soil Moisture in Disease Development of Charcoal Rot of Strawberries Caused by Macrophomina phaseolina.

Charcoal rot, caused by the soilborne fungus Macrophomina phaseolina, is one of the most economically important diseases affecting strawberry (Fragaria ×ananassa) production in California. Previous studies on non-strawberry hosts have shown that proper soil moisture management can limit pathogen colonization of plants and decrease disease severity. We performed field and greenhouse studies for two seasons with the objective of investigating the role of soil moisture in disease development and management of charcoal rot of strawberries. Bare-root transplants of cultivars Monterey and Fronteras were inoculated or not inoculated and maintained at either a high, optimal, or low soil moisture level using tensiometers. Randomly selected plants from each treatment were sampled for pathogen colonization every 4 weeks after planting, and all plants were visually rated for disease severity every 2 weeks after symptom onset. In both seasons, low soil moisture significantly increased charcoal rot mortality among inoculated plants compared to optimal soil moisture by 16 and 24 percentage points, respectively. In the first season, mortality was significantly lower in the high compared to the optimal soil moisture treatment. Colonization of crowns was increased by low soil moisture among inoculated plants in the first season, but soil moisture did not influence root colonization in either year of the study. In the greenhouse, charcoal rot severity was highest in the low soil moisture treatment. These results indicate that soil moisture has a limited influence on colonization of strawberries by M. phaseolina and that maintaining optimal soil moisture can help prevent excess charcoal rot mortality.

Genotyping peculiarities of wheat photosynthesis light induction and productivity under the drought effect

Background. In agrocenoses, leaf light conditions are known to be unstable due to intermittent cloud cover and shading by other leaves or spikes. However, with a change in irradiance, photosynthesis does not reach its final value instantly, but with a certain delay. Due to this photosynthetic efficiency of leaves and crops is generally lower compared to stationary conditions. At the same time, the vast majority of works devoted to the problems of photosynthetic apparatus functioning under unstable light conditions do not take into account an adverse impact on photosynthesis of such a common stressor as drought. The aim of the present work was to study the peculiarities of flag leaves CO2 and H2O gas exchange parameters with changes in illumination under conditions of optimal and insufficient water supply in order to explore the pattern of drought effect on the photosynthetic induction processes in connection with productivity of wheat plants of different genotypes. Materials and Methods. The research was carried out on bread winter wheat varieties Yednist, Bohdana, Perlyna Podillia under conditions of pot experiment. Control plants were grown under an optimal soil moisture of 70 % field capacity (FC). In the experimental pots, soil drought was created at the level of 30 % FC for 7 days during the earing–flowering period, after that the soil moisture was restored to the optimal level. The parameters of flag leaf gas exchange were measured on the seventh day of drought. Components of plants grain productivity were determined after reaching full grain maturity. Results. It was found that according to the parameters of light induction curves of CO2 assimilation and transpiration, wheat plants of different genotypes under drought conditions are differentiated more clearly than under normal water supply. An increase in the limiting role of stomata in the induction of photosynthesis under drought conditions and changes in illumination was shown. Drought disrupts the coherence of stomatal conductance regulation in interaction with CO2 assimilation processes. This affects the light induction curves of photosynthesis and transpiration, and ultimately leads to a decrease in grain productivity. Conclusions. It was shown that in order to assess the efficiency of the photosynthetic apparatus in providing wheat plants with assimilates and maintaining their grain productivity under unfavorable conditions, the parameters of the response to the changes in illumination must be taken into account.

Rancang Bangun Sistem Kontrol Irigasi Otomatis Berbasis IoT untuk Tanaman Stevia

This research focuses on developing an IoT-based automatic irrigation control system for stevia plants to optimize plant growth and water usage efficiency. The system integrates ESP32 microcontroller with soil moisture sensors, DS18B20 temperature sensors, and DHT11 environmental sensors for comprehensive monitoring. Using Research and Development (R&D) methodology with an experimental approach, the system was designed and implemented to automatically control irrigation based on soil moisture levels. The results demonstrate that the system successfully maintains optimal soil moisture by activating the pump when moisture levels fall below 38% and deactivating it above 40%. Real-time monitoring through the Blynk platform enables remote observation and control of environmental parameters. The integration of multiple sensors with IoT technology provides an efficient solution for stevia plant irrigation management, offering potential applications in smart agriculture.

Optimizing residue return with soil moisture and nutrient stoichiometry reduced greenhouse gas fluxes in Alfisols

Optimum soil moisture and high crop residue return (RR) can increase the active pool of soil organic carbon and nitrogen, thus modulating the magnitude of greenhouse gas (GHG) fluxes. To determine the effect of soil moisture on the threshold level of RR for the wheat production system, we analyzed the relationship between GHG fluxes and RR at four levels, namely 0, 5, 10, and 15 Mg ha−1 (R0, R5, R10, and R15) under two soil moisture content (80% FC and 100% FC) and three levels of nutrient management (NS0: no nutrient; NS1, NS2= 3x NS1). Nutrient input (N and P) in NS1 balanced the residue C/nutrient stoichiometry to achieve 30% stabilization of the residue C input in RR (R5). All RR treatments (cf. R0) were found to significantly reduce N2O emission in moderate soil moisture content (80% FC) by 22–56% across nutrient management due to enhanced soil C mineralization, microbial biomass carbon, and N immobilization. However, averaged across nutrient management, a linear increase in N2O emission was observed with increasing RR under 100% FC soil moisture. A significant decrease in CH4 emission by ca. 46% in most RR treatments was observed in 100% FC compared with the R0. The N2O emission was negatively correlated (p = <0.001) with nutrient stoichiometry. Partial least square (PLS) regression indicated that GHG emissions were more responsive (values > 0.8) to management variables (RR rate, nitrogen (N) input rate, soil moisture, and nutrient stoichiometry of C: N) and post-incubation soil properties (SMBC and NO3-N) in Alfisols. This study demonstrated that the mechanisms responsible for RR effects on soil N2O, CH4 fluxes, and carbon mineralization depend on soil moisture and nutrient management, shifting the nutrient stoichiometry of residue C: N: P.

Optimized Soil Moisture Mapping Strategies on the Tibetan Plateau Using Downscaled and Interpolated Maps as Mutual Covariates

Accurate high-resolution soil moisture maps are crucial for a better understanding of hydrological processes and energy cycles. Mapping strategies such as downscaling and interpolation have been developed to obtain high-resolution soil moisture maps from multi-source inputs. However, research on the optimization performance of integrating downscaling and interpolation, especially through the use of mutual covariates, remains unclear. In this study, we compared four methods—two standalone methods based on downscaling and interpolation strategies and two combined methods that utilize soil moisture maps as mutual covariates within each strategy—in a case study of daily soil moisture mapping at a 1 km resolution in the Tibetan Plateau. We assessed mapping performance in terms of prediction accuracy and differences in spatial coverage. The results indicated that introducing interpolated soil moisture maps into the downscaling strategy significantly improved prediction accuracy (RMSE: −5.94%, correlation coefficient: +14.02%) but was limited to localized spatial coverage (6.9% of grid cells) near in situ sites. Conversely, integrating downscaled soil moisture maps into the interpolation strategy resulted in only modest gains in prediction accuracy (RMSE: −1.07%, correlation coefficient: +1.04%), yet facilitated broader spatial coverage (40.4% of grid cells). This study highlights the critical differences between downscaling and interpolation strategies in terms of accuracy improvement and spatial coverage, providing a reference for optimizing soil moisture mapping over large areas.

Determination of Optimal Soil Moisture Depletion Levels for Sweet Basil (Ocimum basilicum L.) at Wondo Genet, Ethiopia

Determining allowable soil moisture depletion level is critical for determining proper irrigation scheduling. The study was conducted at Wondo Genet Agricultural Research Center, Ethiopia, latitude 8°25'59'', longitude 39°01'44''and altitude of 1800 m.a.s.l to determine optimal soil moisture depletion level for sweet basil (Ocimum basilicum L.). Six levels of soil moisture depletion (20, 30, 40, 50, 60 and 100% of total available water (TAW) of the soil), with three replication were used as treatments to evaluate the yield and yield component of sweet basil in randomized complete block design. Different levels of soil moisture depletion levels significantly affected all recorded yield and yield components of sweet basil including its water productivity. Significantly higher yield and yield components were associated with frequently irrigated treatment under lower soil moisture depletion levels before irrigation. However, when sweet basil was irrigated beyond 40% TAW lowest yield and yield components were recorded. Therefore, sweet basil could be irrigated when the soil moisture content is depleted by 40% of the total available water content in the soil to enhance yield and water use efficiency in the study area and similar agro ecologies.

Optimizing Soil Moisture, Mulching, and Spacing for Yield and Water Productivity in Irrigated Elephant Foot Yam (Amorphophallus paeoniifolius)

Aims: To standardize crop spacing and irrigation requirements under different mulching situation for better yield and water productivity. Study Design: The experiment was designed in RBD with two replications. Place and Duration of Study: The experiment was conducted at Agronomic Research Station, Kerala Agriculture University (KAU), Chalakudy for three consecutive years from 2016 -17, 2017 – 18 and 2018 – 2019. Methodology: Study conducted with 18 treatments, includes three levels of irrigation, three types of mulching and with two different crop spacing. Observations on weed count and weed dry matter production were also taken to study the effect of different mulches on weed growth. Biometric observations of crop growth and yield were recorded. Results: Observations on biometric characters revealed that both the height and diameter of the crop canopy were significantly influenced by mulching and found to be highest in the plot where leaf was used as the mulching material and the yield of Amorphophallus during 2016 - 2017 showed that corm weight was greatly influenced by irrigation levels, mulching and spacing. Corm yield was lowest in the plot where irrigation frequency was once in three days (21.02 t/ha). Yield in leaf mulched plot was 38.11 t/ha while in plastic mulched and no mulched plots were 23.50 and 19.50 t/ha. Effect of treatments on water productivity and BC ratio showed that leaf mulching of the crop has significant effect. In leaf mulched plot, water productivity in 2016-17 was 2.03 while it was only 1.854 and 0.886 in 2017-18 and 2018-19. Similarly, BC ratio was highest for leaf mulched plot followed by no mulch and plastic mulch plot. Conclusion: The experimental results from 2016 -17, 2017 – 18 and 2018 – 2019, showed that Amorphophallus planted at a spacing of 90 cm x 90 cm, irrigated at a frequency of once in three days along with leaf mulching can increase the yield and water productivity along with effective control of weed population.

Pesticides trapping performance of vegetative filter strips in black soil region, Northeast China: controlled experiments and VFSMOD-W modeling

The Northeast black soil region in China is an important grain-producing area where various pesticides are extensively used to increase grain yields. However, this practice poses serious risks to the ecological health of soil and water systems, necessitating effective measures. Vegetative filter strips (VFS) are commonly used to mitigate agricultural diffuse pollutants, but their efficiency varies across different regions, requiring assessment. This study employed flume experiments, the VFSMOD-W model, and redundancy analysis (RDA) to evaluate the efficacy of VFS in runoff, sediment, and pesticide removal, as well as influencing factors. The results showed that VFS reduced outflow rate of runoff by 8 %–64 % and sediment by approximately 90 %, achieving load removal rates of 61 % and 95 % respectively. Pesticide load removal efficiency ranged from 37 % to 94 %, with higher efficiency for adsorbed pesticides like chlorpyrifos compared to water-soluble ones like atrazine. Interflow and vertical seepage were significant pathways for pesticide transport in VFS, with chlorpyrifos concentrations at 4 %–26 % and atrazine at 20 %–37 % of inflow concentrations. The VFSMOD-W model accurately predicted VFS efficiency (NSE > 0.90), and RDA results indicated that environmental factors could explain 86.7 % of the variation in VFS performance, with soil vertical saturated hydraulic conductivity (VKS) being the most influential factor, followed by rainfall intensity (T), saturated soil water content (OS), initial soil water content (OI), and filter slope for each segment (SOA). Optimizing soil moisture characteristic factors and increasing infiltration are crucial for VFS performance. Applying VFSMOD-W for precise VFS design can help reduce construction costs. In the future, long-term field monitoring and evaluation of VFS efficiency after implementation should be conducted in the black soil region of Northeast China to provide data supporting the improvement of VFSMOD-W simulation accuracy. This will also offer recommendations for the government in formulating VFS configuration schemes.

Variation of the nutritional content of different genotypes of Lotus corniculatus L. under optimum and sub-optimal soil moisture conditions throughout the seasons of the year

O Objective: To evaluate the leaf nutrient content of four accessions and one variety of Lotus corniculatus L. trefoil throughout the seasons of the year and under optimum and sub-optimal soil moisture content, established under a shade mesh in northern Mexico. Design/Methodology/Approach: During the 2021-2022 period, an experimental randomized block design, in a split-plot arrangement, with three replicates was established. The large plots had an optimum (26±1.5%) and sub-optimal (22±1.5%) soil moisture content. The small plots consisted of the trefoil accessions: 255301, 255305, 202700, 226792 origin code, and the Estanzuela Ganador variety. Results: At optimum soil moisture content, the 202700 accessions recorded a K deficiency throughout the year. Meanwhile, regardless of the soil moisture content, the 255301 accessions recorded a Mg and a Mn deficiency only in summer. N, P, Fe, and Mn recorded deficient contents: N and P throughout the year and Fe and Mn only in winter and spring. Study Limitations/Implications: These results could require a field validation, since the experiment was carried out in semi-controlled conditions, under shade mesh. Findings/Conclusions: Developing an adequate annual nutrition program for L. corniculatus L. that improves its forage productivity requires several key factors, including the behavior of the nutritional status (dependent on the type of nutrient), the growth stage of the plant, the season of the year, and the soil moisture content.

AN AUTOMATED CROP MONITORING AND IRRIGATION SYSTEM WITH PREDICTIVE ANALYSIS

Background: The rising global population and decreasing agricultural land challenge the food supply, worsened by land degradation and water scarcity. Using IoT solutions, precision farming offers promise for addressing these issues by enhancing productivity, profitability, and environmental sustainability. The paper proposes an IoT-based automated monitoring and irrigation system with predictive analysis as a solution. Aims: To develop an IoT-based irrigation model with cloud computing, a mobile app for remote monitoring and irrigation control, and a predictive analysis method for forecasting weather conditions. Methods: IoT sensors are connected to a node MCU, and they monitor real-time temperature, humidity, and soil moisture. A water pump adjusts irrigation accordingly. Data is sent to ThingSpeak for visualization and Firebase for storage and is accessible via a mobile app. Predictive analysis combines sensor and historical weather data using the Random Forest algorithm to optimize irrigation. This determines the ideal irrigation frequency, duration, and timing based on predicted temperature and soil moisture levels, ensuring optimal soil moisture for plant growth. Results: The system exhibited encouraging outcomes. It displayed transformative potential by harnessing IoT, cloud computing, and predictive analytics. Offering precise soil moisture monitoring, instant data access, and tailored advice, the system can elevate crop management, streamline water consumption, and boost productivity among Indian farmers. Discussion: The automated crop monitoring and irrigation system has transformative potential in farming. Some future scope and enhancements may include broadening crop compatibility, integrating satellite data, enhancing pest monitoring, improving connectivity, enriching the mobile app, scaling up through partnerships, and refining the predictive models. Conclusions: The IoT-driven crop monitoring system revolutionizes Indian agriculture by optimizing irrigation and integrating weather forecasts. With mobile app enhancements and future improvements, it promises sustainable farming and empowerment for farmers.

LABORATORY DETERMINATION OF THE MAXIMUM DENSITY AND OPTIMAL HUMIDITY OF LARGE-BLOCK SOILS

he purpose of our field research was to develop and select a method of work on laying and compacting the material of large-block soils, ensuring the receipt and determination of maximum density and optimal soil moisture. On the basis of these studies, technical conditions for the construction of thrust prisms are further drawn up. This article presents the results of the work performed with a brief methodology of field and laboratory research. The article provides data characterizing the material intended for installation in the body of the dam. The currently existing methods for determining the control parameters of laying large-block soils are contradictory and require experimental work. A number of parameters are taken into account: grain composition, humidity, density. Therefore, the article considers a laboratory method for determining the maximum density and optimal humidity of stone material when laying in the body of the dam. The results of the research carried out on the development of our quarry area, the thickness of the uncompacted layer was determined, the choice of a sealing mechanism, the number of passes along one track, the determination of the density of dry soil in experimental field sites intended for use in filling the body of the dam, graphs of the required densities for full-scale grain composition are presented. The strength properties of the stone material were determined experimentally for the average grain composition and for the upper curve of the accepted “fish”

Farmland mulching and optimized irrigation increase water productivity and seed yield by regulating functional parameters of soybean (Glycine max L.) leaves

In both arid and semi-arid regions, adopting field mulching can effectively optimize soil moisture distribution, enhance crop yields, and improve water productivity. While acknowledging its advantages, field mulching seems insufficient for maintaining high crop productivity due to the increasing frequency of extreme weather. Furthermore, drought often coincides with critical crop growth stages, necessitating the implementation of agricultural irrigation to ensure normal crop growth. Accordingly, we conducted a three-year field experiment from 2021 to 2023 including three typical field mulching methods (no mulching, NM; straw mulching, SM; plastic film mulching, FM) and three supplementary irrigation strategies (irrigated at the branching stage (V4), W1; irrigated at the pod-filling stage (R2), W2; irrigated at both the V4 and R2 stage, W3). Throughout the entire growth period, we monitored soil moisture conditions for each treatment, measured leaf physiological parameters at crucial growth stages, and assessed soybean yields and water productivity (WP). Our findings indicated that, relative to SM and NM, FM maintains optimal soil moisture balance, augments chlorophyll content, and enhances photosynthesis, resulting in an average yield increase of 17.0% and 38.3% over three growing seasons. Additionally, supplementary irrigation also significantly affects the growth and seed yield of soybean. FMW2 achieved the higher seed yield (4307.5 kg ha−1, 3-year averaged), had insignificant difference with the highest seed yield of 4568.6 kg ha−1, both significantly higher than other treatments. Similarly, the leaf area index, chlorophyll content, net photosynthetic rate (Pn) and transpiration rate (Tr) also presented insignificant difference between FMW2 and FMW3, while WUEleaf (Pn/Tr) of FMW2 obviously higher than that of FMW3. As a result, FMW2 achieved the highest WP of 12.2 kg ha−1 mm−1 over the three growing seasons, compared to the three-year average of the other treatments, the increase ranges from 5.6% to 46.7%. In summary, the FMW2 treatment optimized water distribution to meet the water demands of soybeans during the reproductive growth stages, achieving a beneficial balance between soybean seed production and WP by regulating leaf functional parameters. Future research will explore more specific irrigation scheduling techniques (e.g., precision irrigation, deficit irrigation, and sensor-based irrigation management systems) while integrating innovative agricultural film materials (e.g., biodegradable films) to further enhance crop resilience and productivity under evolving climatic conditions.

Impact of Drip Irrigation on Crop Growth, Yield, Water Productivity, and Weed Dynamics: A Review

The global water scenario indicates efficient water management practices are required to sustain agricultural productivity. The scarcity of groundwater resources is a global issue that is caused by increasing global population and climate change in the form of global warming. To alleviate the issue, the major water-consuming area implemented drip irrigation projects. It is recognized for its water-saving potential and gained prominence in crop cultivation. This study aimed to investigate the effect of drip irrigation on the growth, yield, water productivity, and weed dynamics of various crops. Results revealed that wheat under drip irrigation exhibited enhanced growth parameters, including increased plant height, leaf area index, and dry matter accumulation attributed to optimized soil moisture content. Drip irrigation significantly improved yield and yield attributes compared to traditional irrigation methods. Importantly, drip irrigation increased water productivity while reducing water use per unit of production. These findings highlight the potential of drip irrigation to reduce water shortages and increase crop output in the current global water context.

WSN-Driven Advances in Soil Moisture Estimation: A Machine Learning Approach

Soil moisture estimation is crucial for agricultural productivity and environmental management. This study explores the integration of Wireless Sensor Networks (WSNs) with machine learning (ML) and deep learning (DL) techniques to optimize soil moisture estimation. By combining data from WSN nodes with satellite and climate data, this research aims to enhance the accuracy and resolution of soil moisture estimation, enabling more effective agricultural planning, irrigation management, and environmental monitoring. Five ML models, including linear regression, support vector machines, decision trees, random forests, and long short-term memory networks (LSTM), are evaluated and compared using real-world data from multiple geographical regions, which includes a dataset from NASA’s SMAP project, supplemented by climate data, which employs both active and passive sensors for data collection. The outcomes demonstrate that the LSTM model consistently outperforms other ML algorithms across various evaluation metrics, highlighting the effectiveness of WSN-driven approaches to soil moisture estimation. The study contributes to the advancement of soil moisture monitoring technologies, offering insights into the potential of WSNs combined with ML and DL for sustainable agriculture and environmental management practices.

Plant Watering System Using ESP8266

Efficient water management is crucial for sustaining healthy plant growth, especially in environmentsprone to drought or excessive moisture. This paper presents a novel plant watering system designed to optimize water usage while ensuring adequate hydration for plants. The system incorporates sensors to measure soil moisture levelsand environmental conditions, such as temperature and humidity, enabling real-time monitoring and responsive watering. Utilizing a microcontroller-based control unit, the system autonomously regulates watering intervals and durations based on preset thresholds and plant specific requirements. By employing drip irrigation technology, water is delivered directly to the root zone, minimizing waste and promoting efficient absorption. Experimental results demonstrate the system's effectiveness in maintaining optimal soil moisture levels, fostering plant health, and conserving water resources. This innovative approach offers a sustainable solution for automated plant care, suitable for both indoor and outdoor cultivation environments.

Physiological and Productivity Responses in Two Chili Pepper Morphotypes (Capsicum annuum L.) under Different Soil Moisture Contents

The aim of this study was to explore some physiological and productivity responses of two chili pepper morphotypes (Capsicum annum L.) exposed to different soil moisture contents. A randomized block design in a split-plot arrangement with four replicates was used. The large plots (32 m long and 3.2 m width) were 25% ± 2 as the optimum soil moisture content (OSMC), and 20% ± 2 as the suboptimum soil moisture content (SSMC); the small plots (16 m long and 3.2 m width) were two chili pepper morphotypes: Jalapeño and Chilaca, respectively. Jalapeño plants showed more stability in relative water content (RWC), photosynthetic activity (µmol CO2/m2/s), and a relatively low transpiration (mmol H2O/m2/s) and stomatal conductance (µmol H2O/m2/s); therefore, it had a higher number of flowers per plant and number of fruits per plant, consequently recording a high fruit production of 3.94 and 2.99 kg/m2 in OSMC and SSMC, respectively. In contrast, the Chilaca chili showed low stability in water relative content (WRC), photosynthesis, and transpiration, going from OSMC to SSMC, as well as showed a lower yield in SSMC; however, all of that was compensated by its size and weight of the fruit per plant, with a yield of 4.95 kg/m2 in OSMC. Therefore, the Jalapeño chili pepper could be an option when the irrigation water is limited, and the Chilaca chili pepper when this resource is not limited.

Tillage Methods Change Nitrogen Distribution and Enzyme Activities in Maize Rhizosphere and Non-Rhizosphere Chernozem in Jilin Province of China

The tillage method in farming systems is essential to develop strategies to increase fertilizer uptake by plant roots and to avoid environmental pollution. The field study aimed to investigate the characteristics of nitrogen and enzyme activities in rhizosphere soil with different tillage methods. Four treatment plots applied with fertilizers were established: continuous rotary tillage (CR), plowing-rotary tillage (PR), continuous no-till (CN) and ploughing-no-till (PN). The total content of nitrogen in chernozem was high during early stages of plant growth, and then it decreased with the maize growth. In the rhizosphere soil, the total N accounted 1314.45, 1265.96, 1120.47, 1120.47, 1204.05 mg·kg−1 of CR, PR, CN, and PN, respectively, which were markedly greater than that of non-rhizosphere soil (1237.52, 1168.40, 984.51, 1106.49 mg·kg−1 of CR, PR, CN, and PN, respectively). At first growth stages, content of NH4+-N and NO3−-N in two soil regions was low, then increased gradually, which followed the order of CR < PR < PN < CN. The rhizosphere soil showed slightly higher concentration of NH4+-N and NO3−-N than non-rhizosphere. The soil enzymes were more active in the rhizosphere soil than that of non-rhizosphere during the whole maize growth stages. Due to minimal damage to the soil environment and optimal soil moisture and temperature, the urease and catalase activities were greatest in the rhizosphere for CN treatment. Therefore, CN was recommended to be used by farmers for the improvement of macronutrient availability and soil enzyme activities in the soil.

Multi-year vertical and life cycle impacts of C-N management on soil moisture regimes

Understanding the long-term impact of C-N management practices on soil moisture content (SMC) is crucial for sustainable agriculture, particularly in mitigating seasonal droughts and storm rainfall constraints. A multi-year (2014–2018) field experiment was conducted, with high-frequency measurements and consideration of a full life cycle, as well as multiple vertical layers (0–100 cm, with intervals of 20 cm). Treatments were arranged in a split plot design with nitrogen (N) fertilizer input (N80% and N60%) as the whole-plot factor, and Carbon (C) treatments (Corg=organic fertilizer, Cstraw=straw mulching and full returning, Cinteg= Corg + Cstraw) were considered as the split-plot factor. The results demonstrated the Cinteg treatment resulted in the highest increase in the five-year averaged SMC (approximately 6.60% greater than Corg), followed by the Cstraw treatment. Additionally, the N60% treatment resulted in significantly higher SMC compared to the N80% treatment, with a range of 1.71–4.12% increase across the life cycle. Furthermore, the research revealed that the average SMC increased the most during the jointing-heading period and the least during the heading-maturity period across all treatments. The vertical results indicated a higher efficiency in water retention within the shallow layers (0–20 cm, 20–40 cm) compared to the deeper layers (80–100 cm) for all treatments. The study recommends adopting integrated C-N management practices, considering life cycle periods and vertical layers, to optimize soil moisture content. It offers valuable insights for optimizing soil moisture management strategies, alleviating seasonal droughts, enhancing water-use efficiency, and fostering sustainable agricultural practices.