Optimizing Growth and Yield in Mulched Cotton Through Aerated Subsurface Drip Irrigation in Southern Xinjiang by Yuxi Zhang, Baolin Yao, Peining Niu, Zhu Zhu, Yan Mo, Fayong Li, Sanmin Sun

“…The findings revealed that ASDI significantly promoted soil moisture depletion from 0 to 40 cm during the cotton flowering and boll opening stages. …”
Get full text

Effects of Sewage Sludge Compost on Carbon, Nitrogen, Phosphorus, and Sulfur Ratios and Soil Enzyme Activities in a Long-Term Experiment by Csilla Almási, Viktória Orosz, Timea Tóth, Mostafa M. Mansour, Ibolya Demeter, István Henzsel, Zsolt Bogdányi, Tamás András Szegi, Marianna Makádi

“…The results showed that basic soil parameters (pH, OM content, E4/E6 ratio, NO₃-NO₂-N, AL-P₂O₅, and soil moisture content) were increased, along with the SSC doses in soil for the rye. …”
Get full text

A novel agricultural drought index based on multi-source remote sensing data and interpretable machine learning by Hao Chen, Ni Yang, Xuanhua Song, Chunhua Lu, Menglan Lu, Tan Chen, Shulin Deng

“…Here, we used solar-induced chlorophyll fluorescence, water balance, soil moisture, and land surface temperature to develop a new integrated remote sensing drought index, namely interpretable machine learning drought index (IMLDI), based on the Bayesian optimized tree-based Light Gradient Boosting Machine and SHapley Additive exPlainations. …”
Get full text

Response of Soil Respiration to Snowfall in a Kubuqi Salix Plantation Forest of During Freeze-thaw Period by WANG Jixuan, LAN Xiaozhen, PEI Zhiyong, ZHANG Junyao, WANG Xinping, LI Ying, WANG Haichao, SUN Xiaotian, SUN Kai

“…Soil respiration was significantly correlated with soil temperature under each treatment, and the single factor model could explain 51%~68% of the variation in soil respiration (p<0.001), but the correlation between soil respiration and soil moisture was not significant. The two-factor composite model of soil temperature and moisture explained soil respiration better than the single factor model, and it explained 81% of the variation in soil respiration. …”
Get full text

Optimizing plant density to improve the soil microenvironment and enhance crop productivity in cotton/cumin intercropping systems by Humei Zhang, Humei Zhang, Liwen Tian, Xianzhe Hao, Nannan Li, Xiaojuan Shi, Feng Shi, Yu Tian, Wenbo Wang, Honghai Luo

“…Through a two-year field experiment, the effects of cotton-cumin intercropping on the soil moisture, temperature, salt, respiration rate, weed density, cotton yield formation and intercropping advantages were studied.Results and discussionCompared with the CK treatment, the ID2 treatment decreased the water content in the 0–30 cm soil layer by 8.3%, increased the water consumption by 9.1%, increased the soil temperature by 0.5°C, and decreased the electrical conductivity of the 0–15 cm soil layer by 17.7%. …”
Get full text

Effects of Brackish Water with Different Sodium-Potassium Ratios on Soil Water-Salt Characteristics and Winter Wheat Growth by GAO Weiqiang, ZHANG Tibin, TONG Jiankang, LIU Zhenyuan, LIANG Qing, KUANG Yuxin, CHENG Yu, FENG Hao

“…[Results] Compared with CK, the 0-40 cm soil moisture content under T1, T2 and T3 brackish water irrigation increased by 19%, 8% and 14% (p<0.05), respectively. …”
Get full text

Digital technologies for water use and management in agriculture: Recent applications and future outlook by Carlos Parra-López, Saker Ben Abdallah, Guillermo Garcia-Garcia, Abdo Hassoun, Hana Trollman, Sandeep Jagtap, Sumit Gupta, Abderrahmane Aït-Kaddour, Sureerat Makmuang, Carmen Carmona-Torres

“…UAV-mounted multispectral cameras) can accurately monitor soil moisture to optimise irrigation scheduling, while AI-driven models (e.g. random forest or neural networks) can predict groundwater recharge or forecast rainfall events. …”
Get full text

Elevation gradient effects on grassland species diversity and phylogenetic in the two-river source forest region of the Altai Mountains, Xinjiang, China by Jing Che, Jing Che, Mao Ye, Mao Ye, Qingzhi He, Qingzhi He, Guoyan Zeng, Guoyan Zeng, Miaomiao Li, Miaomiao Li, Weilong Chen, Weilong Chen, Xiaoting Pan, Xiaoting Pan, Jiaorong Qian, Jiaorong Qian, Yexin Lv, Yexin Lv

“…Further analysis reveals significant correlations between species diversity and environmental factors such as temperature, precipitation, forest cover, and soil moisture. However, no environmental factors were found to have a significant correlation with the phylogenetic indices.…”
Get full text

Cyberinfrastructure for machine learning applications in agriculture: experiences, analysis, and vision by Lucas Waltz, Sushma Katari, Chaeun Hong, Adit Anup, Julian Colbert, Anirudh Potlapally, Taylor Dill, Canaan Porter, John Engle, John Engle, Christopher Stewart, Hari Subramoni, Scott Shearer, Raghu Machiraju, Osler Ortez, Laura Lindsey, Arnab Nandi, Sami Khanal

“…The data collected and processed from this study were used to train ML models to make predictions of crop growth stage, soil moisture, and final yield.ResultsThe exercise of processing this dataset resulted in four CI components that can be used to provide higher accuracy predictions in the agricultural domain. …”
Get full text

Study on the Synergistic Regulation Model for <i>Lycium barbarum</i> Berries Under Integrated Irrigation and Fertigation in Northwest Arid Regions by Yanlin Ma, Huile Lv, Yanbiao Wang, Yayu Wang, Minhua Yin, Yanxia Kang, Guangping Qi, Rong Zhang, Jinwen Wang, Junxian Chen

“…The coordinated application of water and nitrogen significantly influenced yield and efficiencies (<i>p</i> < 0.05) by modifying rhizosphere conditions such as soil moisture, temperature, salinity, and enzyme activities. …”
Get full text

Eco-friendly sustainable farming: Enhancing summer tomato (Lycopersicon esculentum mill.) yield with jute non-woven agro textile Mulch by Nilimesh Mridha, Dipak Nayak, Ashok Yadav, Tilak Mondal, Rakesh Kr Ghosh, Manik Bhowmick, Atul Singha, D.P. Ray, B.S. Manjunatha, Avijit Das, D.B. Shakyawar, Sourav Paul, Amit Das, Santanu Mukherjee, Ravinder Kumar

“…Jute non-woven fabrics of higher thickness with lower water flow and transmissivity increase soil moisture content over no mulch (∼70 %) and plastic mulch (∼9.3 %). …”
Get full text

CAMELS-IND: hydrometeorological time series and catchment attributes for 228 catchments in Peninsular India by N. K. Mangukiya, K. B. Kumar, P. Dey, S. Sharma, V. Bejagam, P. P. Mujumdar, P. P. Mujumdar, A. Sharma, A. Sharma

“…Notably, CAMELS-IND includes available observed streamflow and catchment mean time series of 19 meteorological forcings, including precipitation, maximum, minimum, average temperature, long-wave and short-wave radiation flux, <span class="inline-formula"><i>U</i></span> and <span class="inline-formula"><i>V</i></span> components of wind, relative humidity, evaporation rates from canopy and soil surface, actual and potential evapotranspiration, and soil moisture of four layers (covering depth up to 3 m below ground) for detailed hydrometeorological studies. …”
Get full text

The effect of groundwater depth on topsoil organic matter mineralization during a simulated dry summer in northwestern Europe by A. Françoys, A. Françoys, O. Mendoza, J. Hu, P. Boeckx, W. Cornelis, S. De Neve, S. Sleutel

“…However, the net effect on topsoil C mineralization is complex and warrants further investigation, including the integration of processes related to fluctuations in soil moisture following rewetting.</p>…”
Get full text

Forest fire hazard assessment based on forest typology by Volodymyr P. Voron, Andriy D. Kuzyk, Sergiy V. Ivashyniuta, Yilia R. Tsipan

“…When assessing the potential fire hazards, a contradiction arises because the fire risk is minimal in wet hygrotopes, but on the other hand, the total supply of terrestrial combustible materials is greater in forest types with excessive soil moisture, where organic matter decomposes. In these conditions, along with the accumulation of fallen needles and branches, an important factor in the fire hazard is also the role of the live ground cover. …”
Get full text

Wireless Sensor Network of Typical Land Surface Parameters and Its Preliminary Applications for Coarse-Resolution Remote Sensing Pixel by Baocheng Dou, Jianguang Wen, Xiuhong Li, Qiang Liu, Jingjing Peng, Qing Xiao, Zhigang Zhang, Yong Tang, Xiaodan Wu, Xingwen Lin, Dongqin You, Hua Li, Li Li, Yelu Zeng, Erli Cai, Jialin Zhang

“…Time series observations of typical land surface parameters, including UVR, PAR, SWR, LWR, albedo, and land surface temperature (LST) from RadNet, multilayer soil moisture and soil temperature from SoilNet, and fraction of vegetation cover (FVC), clumping index (CI), and leaf area index (LAI) from VegeNet, have been obtained and shared on the web. …”
Get full text

La flore sauvage du boulevard Dr Henri-Henrot à Reims/Durocortorum : approche carpologique de l’environnement du site et des productions de denrées végétales by Véronique Matterne, Clémence Pagnoux

“…For 45 of the 49 grasslands, the soil moisture sensitivity index is around an average of 6 (hygrophytes) and range from 3 to 9, so they are more likely to have been wet grasslands, possessing variable soil quality and water content. …”
Get full text

Canopy structure modulates the sensitivity of subalpine forest stands to interannual snowpack and precipitation variability by M. Berkelhammer, G. F. M. Page, G. F. M. Page, F. Zurek, C. Still, C. Still, M. S. Carbone, M. S. Carbone, W. Talavera, L. Hildebrand, J. Byron, K. Inthabandith, A. Kucinski, M. Carlson, K. Foss, W. Brown, R. W. H. Carroll, A. Simonpietri, M. Worsham, I. Breckheimer, I. Breckheimer, A. Ryken, R. Maxwell, R. Maxwell, D. Gochis, M. S. Raleigh, E. Small, K. H. Williams, K. H. Williams

“…Using the sap velocity data along with supporting measurements of soil moisture and snow depth, we propose three mechanisms that lead to stand density modulating the tree-level response to changing seasonality of precipitation: </p><ol><li> <p id="d2e396"><span id="page702"/>Topographically mediated convergence zones have consistent access to recharge from snowmelt which supports denser stands with high water demands that are more reliant and sensitive to changing snow.…”
Get full text