Crop Yield Productivity Research Articles

Early-Stage Impacts of Irrigated Conservation Agriculture on Soil Physical Properties and Crop Performance in a French Mediterranean System

The Mediterranean region faces intensified climate change effects, increasing irrigation demands to sustain crop yields and increasing pressure on water resources. Adaptive management strategies such as conservation agriculture (CA) offer potential benefits for soil quality and water use efficiency. However, there is limited research on the short-term effects of this farming system under irrigated Mediterranean climatic conditions. This study aimed to explore the short-term impacts of conservation agriculture (no tillage, cover crops and crop rotation) on the soil properties, water flows and crop and water productivity in a French Mediterranean agrosystem of irrigated field crops, using a multifactorial approach. From 2021 to 2023, maize, sorghum and soybean were grown successively under either conventional tillage (CT) or conservation agriculture (CA), combined with sprinkler irrigation, subsurface drip irrigation or non-irrigated conditions. The dynamics of the surface soil properties (bulk density, penetration resistance, soil temperature), water flows (infiltration, soil evaporation) and agronomic indicators (leaf area index, crop yield, water productivity) were measured across the three cropping seasons. In the pedoclimatic conditions of the study, CA was shown to clearly impact the soil properties, water flows and crop yields, from the first year of adoption. CA practices caused an increased bulk density and soil resistance penetration, leading to decreased quasi-steady ponded infiltration in the surface horizon, particularly in the CA–subsurface drip and CA–non-irrigated conditions. These effects were also reflected in the leaf area index, crop yield and water productivity, with CA showing lower values compared to CT. Crop residues in CA reduced soil evaporation, particularly under sprinkler irrigation. However, this benefit diminished as the residues decomposed, leading to soil evaporation rates comparable to those observed in CT. Agronomic indicators were better under sprinkler irrigation than under subsurface drip irrigation. Overall, compaction emerged as a significant challenge in the adoption of CA, considering its negative impact on crop yields.

Abiotic Stress-Induced Chloroplast and Cytosolic Ca2+ Dynamics in the Green Alga Chlamydomonas reinhardtii.

Calcium (Ca2+)-dependent signalling plays a well-characterised role in the perception and response mechanisms to environmental stimuli in plant cells. In the context of a constantly changing environment, it is fundamental to understand how crop yield and microalgal biomass productivity are affected by external factors. Ca2+ signalling is known to be important in different physiological processes in microalgae but many of these signal transduction pathways still need to be characterised. Here, compartment-specific Ca2+ dynamics were monitored in Chlamydomonas reinhardtii cells in response to environmental stressors, such as nutrient availability, osmotic stress, temperature fluctuations and carbon sensing. An in vivo single-cell imaging approach was adopted to directly visualise changes of Ca2+ concentrations at the level of specific subcellular compartments, using C. reinhardtii lines expressing a genetically encoded ratiometric Ca2+ indicator. Hyper-osmotic shock caused cytosolic and chloroplast Ca2+ elevations, whereas high temperature and inorganic carbon availability primarily induced Ca2+ transients in the chloroplast. In contrast, hypo-osmotic stress only induced Ca2+ elevations in the cytosol. The results herein reported show that in Chlamydomonas cells compartment-specific Ca2+ transients are closely related to specific external environmental stimuli, providing useful guidance for studying signal transduction mechanisms exploited by microalgae to respond to specific natural conditions.

Climate Smart Agriculture in Food Insecurity Mitigation in Nigeria: A Conceptual Evaluation

Climate-Smart agriculture and its impact on food security have been topical issues in policy and food security discusses by successive governments in Nigeria however, the extent of its awareness among the farmers as a food insecurity mitigation measure has not been adequately represented in contemporary local literature hence the need for this research to ascertain the extent of awareness through: an examination of literary works by scholars in the field, assessing the extent of climate-smart procedures in agriculture and suggest where possible ideas to enhance its adoption. The study therefore evaluated secondary data and studies on the impacts of climate change on agriculture and how it can be mitigated through the adoption of climate smart approaches. Climate-Smart Agriculture is an emerging agricultural strategy initiated to tackle the consequences of climate change in food security and sustain agriculture. It involves the combination of approaches in the management of agricultural lands, forests, fisheries and livestock. The study in this regard took a holistic view of the adoption of climate smart agriculture by the farmers, its benefits and approaches and considered objectives such as accessing and assessing other scholars works and views on climate smart agricultural practices utilized by rural farmers in parts of Nigeria, discussing climate smart agriculture and food security, deliberating on climate smart agriculture and resource use efficiency and, viewing the constraining factors hampering the adoption of Climate Smart Agricultural practices in Nigeria. This is because climate change presently is one of the challenges and problems facing the world and an important factor in agricultural productivity. Variations in climatic factors will have ripple effects on crop yield and animal production. Farmers may have been facing weather variability and uncertainty patterns, however, the increasing pace of these uncertainties caused by climate change exacerbate food insecurity and hunger incidences and will require some degree of flexibility and rapid response capacity that climate smart agriculture offers. Building resilience in agricultural and farming practices will reduce the risk of food insecurity outside increasing the adaptive capacity and coping capabilities of the farmers.

Exploring the Linkages Between Land Degradation and Food Insecurity

Currently, two major challenges significantly threaten human civilisation: the degradation of land quality and the insufficient access to sustainable food supplies. They are becoming common in numerous places globally, especially in developing nations with elevated population growth rates. Prior studies have examined the impact of several types of land degradation, including soil erosion, waterlogging, stalinisation and desertification, on crop yield, water quality and agricultural productivity. This article comprehensively examines the interrelationship and reciprocal influence between land degradation and food insecurity, emphasising the intricate dynamics of elements contributing to both global challenges. The article analyses several types of land degradation, their direct and indirect effects on the foundations of food security, and how rising food demands exacerbate land degradation. The research advocates for collaborative initiatives at local, national, and global tiers to disrupt the detrimental cycle and establish a resilient, food-secure future.

Engineering Soil Quality and Water Productivity Through Optimal Phosphogypsum Application Rates

Water scarcity and soil degradation pose challenges to sustainable agriculture. Phosphogypsum, a low-cost solid waste, shows potential as a soil amendment, but its impact on water saving and soil quality need further study. This research assessed the effects of phosphogypsum application rates (CK: no phosphogypsum, 0.075%, 0.15%, 0.3% and 0.6%) on soil infiltration, water retention, salinity, soil quality, crop yield and irrigation water productivity (IWP) to identify the optimal rate. Phosphogypsum application altered pore structure and water potential gradients, slowing wetting front migration, increasing infiltration duration (102 to 158 min), cumulative infiltration (17.37 to 27.44 cm) (p < 0.05) and soil water content (18.25% to 24.33%) (p < 0.05) as the rate increased from CK to 0.6%. It also enhanced water retention by enhancing soil aggregation and reducing evaporation.By promoting the formation and stabilization of soil aggregates, phosphogypsum application (CK to 0.6%) reduced bulk density from 1.20 g/cm3 to 1.12 g/cm3 (p < 0.05), while porosity, available nitrogen and urease activity increased by 3.70%, 39.42% and 82.61%, respectively (p < 0.05). These enhancements provided a strong foundation for improved crop performance. Specifically, phosphogypsum enhanced yield through three pathways: (1) improving soil physical properties, which influenced soil nutrients and then improved enzyme activities; (2) directly affecting soil nutrients, which impacted enzyme activities and increased yield; and (3) directly boosting enzyme activities, leading to increased yield. The comprehensive benefits of phosphogypsum initially increased and then decreased, with an optimal application rate of 0.45% determined through TOPSIS, a method that ranks alternatives based on their proximity to an ideal solution, considering factors including soil quality, crop yield and IWP. These findings confirm the feasibility of phosphogypsum as an effective resource to enhance water efficiency and soil quality, promoting sustainable agricultural practices.

Estimation of Water Interception of Winter Wheat Canopy Under Sprinkler Irrigation Using UAV Image Data

Canopy water interception is a key parameter to study the hydrological cycle, water utilization efficiency, and energy balance in terrestrial ecosystems. Especially in sprinkler-irrigated farmlands, the canopy interception further influences field energy distribution and microclimate, then plant transpiration and photosynthesis, and finally crop yield and water productivity. To reduce the field damage and increase measurement accuracy under traditional canopy water interception measurement, UAVs equipped with multispectral cameras were used to extract in situ crop canopy information. Based on the correlation coefficient (r), vegetative indices that are sensitive to canopy interception were screened out and then used to develop canopy interception models using linear regression (LR), random forest (RF), and back propagation neural network (BPNN) methods, and lastly these models were evaluated by root mean square error (RMSE) and mean relative error (MRE). Results show the canopy water interception is first closely related to relative normalized difference vegetation index (R△NDVI) with r of 0.76. The first seven indices with r from high to low are R△NDVI, reflectance values of the blue band (Blue), reflectance values of the near-infrared band (Nir), three-band gradient difference vegetation index (TGDVI), difference vegetation index (DVI), normalized difference red edge index (NDRE), and soil-adjusted vegetation index (SAVI) were chosen to develop canopy interception models. All the developed linear regression models based on three indices (R△NDVI, Blue, and NDRE), the RF model, and the BPNN model performed well in canopy water interception estimation (r: 0.53–0.76, RMSE: 0.18–0.27 mm, MRE: 21–27%) when the interception is less than 1.4 mm. The three methods underestimate the canopy interception by 18–32% when interception is higher than 1.4 mm, which could be due to the saturation of NDVI when leaf area index is higher than 4.0. Because linear regression is easy to perform, then the linear regression method with NDVI is recommended for canopy interception estimation of sprinkler-irrigated winter wheat. The proposed linear regression method and the R△NDVI index can further be used to estimate the canopy water interception of other plants as well as forest canopy.

Identification of Genetic Loci Associated with Bolting Time in Radish (Raphanus sativus L.) by QTL Mapping and GWAS

Bolting time is a critical trait that affects crop yield, adaptability, and overall productivity, making its regulation vital for agricultural success. In this study, we explored the genetic mechanisms controlling flowering time in radish (Raphanus sativus) via a combination of quantitative trait locus (QTL) analysis and genome-wide association study (GWAS). By developing an F2 population from a cross between the relatively late-bolting variety ‘L432’ and the early-bolting variety ‘L285’, we identified 12 QTLs associated with bolting time. Furthermore, a GWAS performed on 60 East Asian radish accessions revealed 14 candidate genes potentially involved in flowering and bolting regulation. FLOWERING LOCUS C (FLC2) was the major candidate gene explaining the early and late bolting types. One locus was commonly detected from QTL and GWAS on chromosome 4, where CONSTANS-like (COL4) is located. To validate these findings, SNP markers were designed and applied to F2 populations, revealing a correlation between marker presence and bolting phenotypes. These results offer valuable insights into the molecular control of bolting time in radish and identify candidate genes for use in marker-assisted breeding. These findings could enhance breeding efforts for optimizing bolting time in various radish markets.

Reclamation and Improvement of Saline Soils Using Organo–Mineral–Natural Resources, Treated Saline Water, and Drip Irrigation Technology

Reclamation and management of saline soil in arid regions fundamentally require more consideration to attain sustainable agriculture. Experiments were conducted at Abo-Kalam Farm, South Sinai, Egypt. Split-split-plot design experiments were carried out to study the effect of treatments on saline soil hydrophysical properties, sorghum, and cv. ‘Dorado’ plants during the summer season. Pea cv. ‘Entsar 3’ plants were cultivated during the winter season for the residual effect of treatments. Organo–mineral amendment (rice straw compost + mineral sulfur at different rates) was assigned as the main factor, natural rock or artificial fertilizers were assigned as subfactors, and humic acid at different rates was the sub-subfactor. Results showed that organo–mineral amendments improved the hydrophysical properties of the soil, plant nutrient uptake, crop yield, and crop water productivity; however, it diminished by 10 tons/fed (4200 m2) of compost plus 700 kg/fed of mineral sulfur. Therefore, it is recommended that economically using the combination of applying organic–mineral amendments of 4 tons/fed of compost plus 400 kg/fed of mineral sulfur and 5 kg/fed of humic acid plus natural rock fertilizer is the best safe management for reclamation and improvement of saline soils using partially treated saline irrigation water and natural resources.

Assessing the status of soil seed bank in Parthenium hysterophorus invaded land use types and its social aspects in Lower Hare Watershed, Southern Ethiopia

In Ethiopia, Parthenium hysterophorus (P. hystrophorus) is an invasive alien plant affecting various ecosystems. P. hysterophorus displaced native plant species and caused a serious threat to biodiversity. This study aimed to assess soil seed bank of P. hysterophorus under major land use types and assess community perception towards the effects of P. hysterophorus on social aspects in lower Hare watershed. For this study, 210 soil samples were collected from fifteen transect lines in grassland, cropland, and forest land use types. Statistical analysis using three ways factorial ANOVA was used to analyze the difference in density of P. hysterophorus among various land uses soil depths, and sites (P < 0.05). For the perception of local communities regarding the effects of P. hysterophorus, a total of 117 respondents were used and semi-structured and close-ended questionnaires for data collection. It found that all factors: land use, site, and soil depth significantly affected the soil seed bank density in the lower Hare watershed (P < 0.05). Results indicated that mean density of seeds were the highest in croplands of other land use types. Meanwhile, the highest mean density of seeds was identified in 0-10 cm soil depth, but the lowest mean density of seeds was identified in 10-15 cm soil depth. The highest seeds were identified at Chano Cheliba, but the density of seeds the lowest in density at Kola Shera. 38.5% of households in Kola Shera, and 21.4% in Kola Cheliba, but 8.5% in Kola Doriga said that it had effects on ecosystem services such as crop yield and livestock production. There should be a need for increased awareness about the density of P. hysterophorus in various land uses and its impacts on native plant species. Seeking possible solutions such as biological and mechanical control methods are among the local people, researchers, and extension workers can use for the management of its invasion, and appropriate control measures can be designed to combat its further invasion and impacts on different land uses of the region.

Experimental and numerical evaluation of soil water and salt dynamics in a corn field with shallow saline groundwater and crop-season drip and autumn post-harvest irrigations

In areas with shallow saline groundwater, soil salts inevitably accumulate in the root zone during the growth period due to irrigation and upward movement of salts from the groundwater. In Northern China, autumn irrigation (AIR) with large amounts of water is commonly employed post-harvest to mitigate soil salt stress on crop growth in the subsequent year. Optimizing the total irrigation depth during both crop-growth and non-growth periods is challenging because of the movement of soil salts, which is influenced by their two-dimensional distribution around drippers and the impact of the winter freeze-thaw cycles, significantly affecting water flow and solute transport during winter. In this study, the HYDRUS-1D and HYDRUS-2D models were integrated and calibrated using experimental data collected from 2021 to 2023 in China's Ordos south bank irrigation area. This model integration was conducted to assess soil water and salt dynamics during the non-growth and corn-growth periods under different irrigation strategies: a) AIR with high (AH) and low (AL) irrigation depths, and b) drip irrigation (DIR) with high (DH), medium (DM), and low (DL) irrigation depths. The results indicated that HYDRUS effectively modeled the electrical conductivity of the saturation paste extract (ECe) across different irrigation strategies, yielding an average coefficient of determination (R2) and the root mean square errors (RMSE) of 0.87 and 0.53 dS m−1, respectively. Generally, ECe increased during the growth period with DIR and decreased during the non-growth period with AIR. For the 0–40 cm soil layer, ECe decreased by 5.7 % and 12 % for every 100 mm increase in the AIR and DIR depths, respectively. Compared with the AHDM and AHDL treatments, reducing an AIR depth and increasing a DIR depth resulted in lower ECe in the 0–40 cm layer during the growth period and higher crop yield (CY) and irrigation water productivity (WPI). Specifically, the average ECe in the 0–40 cm layer decreased by 4.8 % during the growth period in the ALDH treatment compared to the AHDM treatment, and CY and WPI increased by 7.2 % and 10.3 %, respectively. Additionally, the irrigation strategy was the most effective in reducing ECe when AIR accounted for 35 % of the total irrigation. This study suggested that combining low AIR and high DIR could enhance water and field productivity.

On the Use of SMAP Soil Moisture for Forecasting NDVI Over CONUS Cropland Regions

AbstractVegetation health forecasting (NDVI as a proxy) informs decision‐makers about the end of season crop yield productivity but is not well‐documented. This study tests improvements in vegetation health forecasting by developing a data‐driven Dynamic Agricultural Productivity Indicator (DAPI), which simultaneously incorporates satellite‐based root zone soil moisture (RZSM) and satellite‐based NDVI data. RZSM is estimated via data assimilation of satellite based SMAP SM dataset. We employ the proposed DAPI forecast across four cropland types in the CONUS, including corn, cotton, soybeans, and wheat. Results demonstrate superior performance of the DAPI forecasts compared to climatology‐based NDVI forecasts, with the largest improvements in water‐limited regions. DAPI shows particularly good performance during hydrologic disturbances such as floods and droughts. To this end, the DAPI approach is useful in estimating future vegetation health for identifying potential food‐insecure areas, predicting crop price changes, and projecting expected commodities market trends.

Impact of Different Drip Emitter Types on Hydraulic Performance and Wetted Zone Characteristics in Okra Cultivation

Drip irrigation system is the most efficient and economical method for irrigation vegetable production. The study aimed to design and evaluate the hydraulic performance of three different types of emitter namely Regular gauge (RG), Compensating pressure (CP) and non-compensating pressure (NCP) using okra as a test of a crop. This study was conducted at the experimental farm of the Faculty of Agricultural Science, Zamzam University in 2023. The treatments were laid out in a randomized complete block design (RCBD) with three replications. Parameters of hydraulic performance of drip emitters were average discharge (Qavg %), discharge variation (Qvar), coefficient uniformity (CU %), coefficient of manufacture variation (CV), emission uniformity (EU %) and statistical uniformity (US %). The results showed that the values of (CU%), (CV), (EU%), (US%) and percentage emitters clogging (Pclog%) were 99.52%, 0.49, 68.01%, 74.14%, 2.8% and 99.32%, 0.36, 52.06%, 63.47%, 1.65% and 99.09%, 0.26, 40.07%, 51.05%, 0.85% for non-compensating pressure (NCP), compensating pressure (CP) and regular gauge (RG respectively. It is considered coefficient uniformity (CU %), was good and found to be within the excellent range while discharge variation (Qvar) was found to be within the desirable range, emission uniformity (EU %), coefficient of manufacture variation (CV), and statistical uniformity (Us %) were found to be within the range of poor, low, acceptable and unacceptable. Thus, the study recommended the best type of emitter was regular gauge (RG), because it has the highest crop yield and water productivity as compared to other emitters, non-compensating pressure emitters (NCP) and compensating pressure emitters (CP)

Sulphur Fractions, Distribution, and Connections with Soil Attributes in the Gopalpur and Ishwardi Soil Series of Bangladesh

The deficiency of soil sulfur (S) is a prevalent issue in Bangladesh soils, posing a significant obstacle to enhancing crop yield and overall productivity. This study aimed to evaluate the distribution of different sulfur fractions across various soil depths in the Gopalpur and Ishwardi soil series, along with their relationships with other soil parameters. In both soil series, the sulfur fractions were ordered as follows: organic > adsorbed > available forms, with organic sulfur being the most abundant. Additionally, soil attributes such as pH, organic carbon, texture, and EC were assessed to understand their relationships with sulphur fractions. Results indicate significant variations in sulphur distribution between the two soils series, with organic sulphur dominating in Gopalpur soils and sulphate-sulphur prevailing in Ishwardi soils. Correlation analysis reveals strong associations between sulphur fractions and soil attributes, highlighting the influence of soil properties on sulphur dynamics. These findings provide valuable insights into sulphur cycling in agricultural soils of Bangladesh and underscore the importance of soil management practices for optimizing sulphur availability and crop productivity.

Propose and implement a Rule-Based System to Predict Crop Yield Production

Accurate meteorological forecasting plays a pivotal role in agricultural decision-making, particularly in determining crop yield potential and optimizing agricultural practices. This study investigates the application of data mining techniques in meteorological forecasting to enhance crop yield prediction accuracy Preliminary findings suggest that data mining techniques, including machine learning algorithms, neural networks, and ensemble methods, offer significant potential for improving the accuracy and reliability of meteorological forecasts for crop yield prediction. In conclusion, this study underscores the potential of data mining techniques in improving meteorological forecasting for crop yield potential assessment.

SCREENING OF RICE GERMPLASM AGAINST DROUGHT STRESS USING MORPHOLOGICAL PARAMETERS

Oryza sativa L. is a staple diet for billions of people in the world. Different rice varieties' drought stress responses and their effects on both qualitative and quantitative variables. Rice is the second main exportable product of Pakistan and the agriculture sector has shown remarkable growth, with the crop sector posting a growth of 6.58% in Fiscal year 2022. Drought have a bad effect on the vegetative and reproductive stages of crops. Drought stress can reduce crop yield production. The RCBD design, two-way ANOVA factorial analysis, Tukey test, Genetic advance and Heritability were used for this experiment. This study specifically focuses on the response of rice genotypes to drought stress and its effect on morphological parameters such as plant height, panicle length, stem diameter, flag leaf length and width, number of panicles per plant, and 1000-grain weight. Drought tolerance genotypes were screened out and used to the standard Index of IRRI to identify morphological processing in Rice Research Institute Kala Shah Kaku, Pakistan. Total 35 rice genotypes were sown under drought stress with checked variety. Six varieties perform better production under drought stress conditions. These varieties like Pokkoli, Vehari, Nonabokra, Kalomonk, PK10683, and Basmati 375 show better perform under drought stress. The findings of this research can contribute to the development of drought-tolerant rice varieties and enhance food security in drought-prone areas. The importance of qualitative parameters, such as panicle curvature and awning, is also explored, with potential implications for the visual appearance and market preferences of rice grains. Overall, this research provides valuable insights into the genetic basis and potential breeding strategies for improving drought tolerance in rice.

Potential Reduction of Spatiotemporal Patterns of Water and Wind Erosion with Conservation Tillage in Northeast China

Conservational tillage (NT) is widely recognized globally for its efficacy in mitigating soil loss due to wind and water erosion. However, a systematic large-scale estimate of NT’s impact on soil loss reduction in Northeast, China’s primary granary, remains absent. This study aimed to investigate the spatial and temporal variability of soil erosion under NT compared to conventional tillage (CT) in the black soil region and to analyze the underlying mechanisms driving these erosions. The Revised Universal Soil Loss Equation (RUSLE) and the Revised Wind Erosion Equation (RWEQ) models were employed, incorporating previously published plot/watershed data to estimate the potential reduction of water and wind erosion by NT in this region. Results indicated that under CT practices, water- and wind-induced soil losses were widely distributed in the arable land of Northeast China, with intensities of 2603 t km−2 a−1 and 34 t km−2 a−1, respectively. Furthermore, the erosive processes of water and wind erosion were significantly reduced by 56.4% and 91.8%, respectively, under NT practices compared to CT. The highest efficiency in soil conservation using NT was observed in the mountainous regions such as the Changbai Mountains and Greater Khingan Mountains, where water erosion was primarily driven by cropland slopes and wind erosion was driven by the wind speed. Conversely, the largest areas of severe erosion were observed in the Songnen Plain, primarily due to the significant proportion of arable land in this region. In the plain regions, water-induced soil loss was primarily influenced by precipitation, with light and higher levels of erosion occurring more frequently on long gentle slopes (0–3°) than on higher slope areas (3–5°). In the temporal dimension, soil loss induced by water and wind erosion ceased during the winter under both tillage systems due to snow cover and water freezing in the soil combined with the extremely cold climate. Substantial reductions were observed under NT from spring to autumn compared to CT. Ultimately, the temporal and spatial variations of soil loss under CT and NT practices were established from 2010 to 2018 and then projected onto a cropland map of Northeast China. Based on this analysis, NT is recommended as most suitable practice in the southern regions of Northeast China for maintaining soil health and crop yield production, while its suitability decreases in the northern and eastern regions.

Gravel Mulching Significantly Improves Crop Yield and Water Productivity in Arid and Semi-Arid Regions of Northwest China: Evidence from a Meta-Analysis

In the arid and semi-arid regions of Northwest China, periodic rainfall deficits, high field evaporation, limited freshwater resources, and high irrigation costs restrict crop yield and water productivity (WP). Gravel mulching (GM), a traditional agricultural tillage management practice widely used in arid and semi-arid regions, improves crop yield and WP. However, the combined impacts of GM on crop yield and WP are unclear. This study aimed to examine the effects of GM on crop yield and WP under different factors and to find the most critical regional factors and gravel characteristics that affect crop yield and WP. To quantitatively assess the impact of GM on crop yield and WP, this study performed a meta-analysis, a regression analysis, and a path analysis of 185 yield comparisons and 130 WP comparisons from 30 peer-reviewed scientific reports. This study found that GM significantly increased crop yield and WP by an average of 29.47% and 28.03%, respectively. GM was reported with the highest response percentages (I) of crop yield and WP in regions whose average annual precipitation (AAP) was 200–400 mm, average annual temperature (AAT) was 0–9 °C, and altitude (A) was >1000 m. Overall, AAP, AAT, and A had significant effects on the I of crop yield (p < 0.001), but AAT and A had an insignificant impact on the I of crop WP (p > 0.05). Gravel size (GS), the amount of gravel mulching (AGM), the degree of gravel mulching (DGM), and the gravel mulching thickness (GMT) had a significantly positive impact on crop yield and WP (p < 0.05). The stepwise multiple linear regression analysis results indicated that the primary regional factors influencing yield were AAT and A, contributing 43.14% and 53.09%, respectively. GMT and GS were identified as significant gravel characterization factors impacting yield, contributing 82.63% and 17.37%, respectively. AAP and GMT were the main regional factors and gravel characterization factors affecting WP. Furthermore, the I values for cash crop yield and WP were higher than that for food crops, and moderate fertilization and irrigation would increase the I values of yield and WP. The benefits of GM are strongly correlated with the planting year. This study’s results show that GM generally improves crop yield and WP, although the extent of this impact varies based on different conditions. These findings are not only useful in relation to their direct applicability to other countries worldwide but also due to their potential to provide new ideas for agricultural practices in similar crop-growing environments.

Utility of AI Based Soil Testing in Agriculture

ABSTRACT The soil plays crucial role in any kind of agricultural crops. Depending upon the different ingredients of the soil the nature of crops to be farmed is decided.Optimizing agricultural practices is crucial for countries like India to address economic growth and escalating food demands. Historical challenges stemming from diverse weather conditions, geographical variations, conventional farming methods, and economic uncertainties have hindered improved crop yields. The dearth of information on crop yield productivity has also resulted in significant economic losses. In response, the adoption of advanced agricultural technologies such as smart farming, digital agriculture, and Data Analytics has become imperative. These innovations provide valuable insights into factors influencing crop yields, best-fit crops for a certain area, and enabling accurate predictions. With precise crop yield forecasts, farmers can develop tailored cultivation plans, implement efficient crop health monitoring systems, and manage yields effectively, thereby transforming agriculture into a highly profitable venture. This paper delves into the applications of technological advancements in agriculture, focusing on areas such as Digital Agriculture, Crop Management, and Crop Protection, and Data Analytics, with the aim of contributing to the optimization of agricultural practices and bolstering the economic impact of the agricultural sector. KEYWORDS: Agriculture, Artificial Intelligence, Machine learning, crop prediction

Unveiling Superabsorbent Hydrogels Efficacy Through Modified Agronomic Practices in Soybean–Wheat System Under Semi‐Arid Regions of South Asia

ABSTRACTThe sustainability of global agriculture at higher productivity level is a concern owing to climate change, serious environmental footprints, dipping factor productivity and shrinking availability of natural resources, especially. The situation is worsening in the ‘Food Bowl of India’—Indo‐Gangetic plains (IGP) by several amalgamated factors, such as declining groundwater, unpredictable precipitation owing to climate change and cultivation of heavy water duty crops. To neutralise these issues, a field experiment was executed for the period 2019–2021 to assess the efficacy of indigenous hydrogels (P‐hydrogel and Superabsorbent polymer hydrogel‐1118) and their application methods viz., seed treatment, slurry application and soil application on crop yield and water productivity, soil moisture dynamics and profitability in a soybean–wheat cropping system under irrigation and rainfed conditions. In both study years (2019–2020 and 2020–2021), due to higher seed germination percentage, irrigation application together with seed treatment and slurry application of superabsorbent polymer hydrogel‐1118 improved system productivity by 8.1%–26.7% and system water productivity by 17.6%–33.8% over control. Wheat grain yield was enhanced by 8.0% (2019–2020) to 32.2% (2020–2021) due to superabsorbent polymer hydrogel‐1118 hydrogel with 10 cm lesser use of irrigation water compared with control (no‐hydrogel). Soil moisture content in 0–15 cm soil layer was also found higher by 1.8%–2.4% in superabsorbent polymer hydrogel‐1118 and P‐hydrogel slurry‐applied plots. Therefore, higher gross profitability (31.8%), net profitability (89.8%) and B:C (26.9%) in wheat could be attributed to increased crop yields when seeds were treated with superabsorbent polymer hydrogel‐1118. Therefore, the utilisation of modified hydrogel application, in the form of seed treatment (seed coating) and slurry application has demonstrated improvement in seed germination, crop yield and water productivity and made soybean–wheat cultivation more economical. This approach presents a feasible solution to achieving a viable production system of soybean and wheat crops by reducing irrigation amounts in the IGP of India, as well as other comparable ecological places worldwide.

Additional organic and bacterium fertilizer input regulated soybean root architecture and dry matter distribution for a sustainable yield in the semi-arid Region of China.

In the dryland area of the Loess Plateau in northwest China, long-term excessive fertilization has led to soil compaction and nutrient loss, which in turn limits crop yield and soil productivity. To address this issue, we conducted experiments using environmentally friendly organic fertilizer and bacterium fertilizer. Our goal was to investigate the effects of additional organic and bacterium fertilizer inputs on soil water migration, crop root architecture, and yield formation. We implemented six different fertilizer strategies, namely: Nm (mulching, N 30 kg/ha), NPK1m (mulching, N 60 kg/ha; P 30 kg/ha; K 30 kg/ha), NPK2m (mulching, N 90 kg/ha; P 45 kg/ha; K 30 kg/ha), NPKOm (mulching, N 90 kg/ha; P 45 kg/ha; K 30 kg/ha; organic fertilizer 2 t/ha), NPKBm (mulching, N 60 kg/ha; P 30 kg/ha; K 30 kg/ha; bacterium fertilizer 10 kg/ha), and N (N 30 kg/ha; no mulching). The results revealed that the addition of bacterium fertilizer (NPKBm) had a positive impact on soybean root system development. Compared with the other treatments, it significantly increased the total root length, total root surface area, and total root length density by 25.96% ~ 94.89%, -19.63% ~ 36.28%, and 9.36% ~ 28.84%, respectively. Furthermore, NPKBm enhanced soil water consumption. In 2018, water storage during the flowering and podding periods decreased by 12.63% and 19.65%, respectively, while water consumption increased by 0.97% compared to Nm. In 2019, the flowering and harvest periods decreased by 23.49% and 11.51%, respectively, while water consumption increased by 0.65%. Ultimately, NPKBm achieved high grain yield and significantly increased water use efficiency (WUE), surpassing other treatments by 76.79% ~ 78.97% and 71.22% ~ 73.76%, respectively. Subsequently, NPK1m also exhibited significant increases in yield and WUE, with improvements of 35.58% ~ 39.27% and 35.26% ~ 38.16%, respectively. The use of bacterium fertilizer has a profound impact on soybean root architecture, leading to stable and sustainable grain yield production.