Artificial Intelligence for Maximizing Agricultural Input Use Efficiency: Exploring Nutrient, Water and Weed Management Strategies

Agriculture plays a crucial role in the economy,and there is an increasing global emphasis on automating agri-cultural processes.With the tremendous increase in population,the demand for food and employment has also increased significantly.Agricultural methods traditionally used to meet these requirements are no longer ade-quate,requiring solutions to issues such as excessive herbicide use and the use of chemical fertilizers.Integration of technologies such as the Internet of Things,wireless communication,machine learning,artificial intelligence(AI),and deep learning shows promise in addressing these challenges.However,there is a lack of comprehensive documentation on the application and potential of AI in improving agricultural input efficiency.To address this gap,a desk research approach was used by utilizing peer-reviewed electronic databases like PubMed,Scopus,Goo-gle Scholar,Web of Science,and Science Direct for relevant articles.Out of 327 initially identified articles,180 were deemed pertinent,focusing primarily on AI’s potential in enhancing yield through better management of nutrients,water,and weeds.Taking into account researchfindings worldwide,we found that AI technologies could assist farmers by providing recommendations on the optimal nutrients to enhance soil quality and deter-mine the best time for irrigation or herbicide application.The present status of AI-driven automation in agricul-ture holds significant promise for optimizing agricultural input utilization and reducing resource waste,particularly in the context of three pillars of crop management,i.e.,nutrient,irrigation,and weed management.

Elevation, Slope Aspect and Integrated Nutrient Management Effects on Crop Productivity and Soil Quality in North-west Himalayas, India

On farm bio-resource recycling has been given greater emphasis with the introduction of conservation agriculture specifically withclimate change scenarios in the mid-hills of the north-west Himalaya region（NWHR）. Under this changing scenario, elevation, slope aspect and integrated nutrient management（INM） may affect significantly soil quality and crop productivity. A study was conducted during 2009-2010 to 2010-2011 at the Ashti watershed of NWHR in a rainfed condition to examine the influence of elevation, slope aspect and integrated nutrient management（INM） on soil resource and crop productivity. Two years of farm demonstration trials indicated that crop productivity and soil quality is significantly affected by elevation, slope aspect and INM. Results showed that wheat equivalent yield（WEY） of improved technology increased crop productivity by -20%-37% compared to the conventional system. Intercropping of maize with cowpea and soybean enhanced yield by another 8%-17%. North aspect and higher elevation increased crop productivity by 15%-25% compared to south aspect and low elevation（except paddy）. Intercropping of maize with cowpea and soybean enhanced yield by another 8%-15%. Irrespective of slope, elevation and cropping system, the WEY increased by -30% in this region due to INMtechnology. The influence of elevation, slope aspect and INM significantly affected soil resources（SQI） and soil carbon change（SCC）. SCC is significantly correlated with SQI for conventional（R2 = 0.65＊）, INM technology（R2 = 0.81＊） and for both technologies（R2 = 0.73＊）. It is recommended that at higher elevation.（except for paddy soils） with a north facing slope, INM is recommended for higher crop productivity; conservation of soil resources is recommended for the mid hills of NWHR; and single values of SCC are appropriate as a SQI for this region.

Strategies for Improving Enterprise Standardization Management of Tropical Crop Machinery

There are two categories of tropical crop machinery. One comprises operation machinery that is used for planting, managing and harvesting tropical crops, while the other comprises process machinery for processing tropical crops. Tropical crop machinery is distinguished from other agricultural machinery by the special crops that such machinery cultivates and processes.……

An optimized strategy of nitrogen-split application based on the leaf positional differences in chlorophyll meter readings

Modern rice production faces the dual challenges of increasing grain yields while reducing inputs of chemical fertilizer.However,the disequilibrium between the nitrogen(N)supplement from the soil and the demand for N of plants is a serious obstacle to achieving these goals.Plant-based diagnosis can help farmers make better choices regarding the timing and amount of topdressing N fertilizer.Our objective was to evaluate a non-destructive assessment of rice N demands based on the relative SPAD value(RSPAD)due to leaf positional differences.In this study,two field experiments were conducted,including a field experiment of different N rates(Exp.I)and an experiment to evaluate the new strategy of nitrogen-split application based on RSPAD(Exp.II).The results showed that higher N inputs significantly increased grain yield in modern high yielding super rice,but at the expense of lower nitrogen use efficiency(NUE).The N nutrition index(NNI)can adequately differentiate situations of excessive,optimal,and insufficient N nutrition in rice,and the optimal N rate for modern high yielding rice is higher than conventional cultivars.The RSPAD is calculated as the SPAD value of the top fully expanded leaf vs.the value of the third leaf,which takes into account the non-uniform N distribution within a canopy.The RSPAD can be used as an indicator for higher yield and NUE,and guide better management of N fertilizer application.Furthermore,we developed a new strategy of nitrogen-split application based on RSPAD,in which the N rate was reduced by 18.7%,yield was increased by 1.7%,and the agronomic N use efficiency was increased by 27.8%,when compared with standard farmers'practices.This strategy of N fertilization shows great potential for ensuring high yielding and improving NUE at lower N inputs.

Booming research on rice physiology and management in China： A bibliometric analysis based on three major agronomic journals

Rice research has always been the top priority in China and China produces the highest number of scientific journal papers on rice, particularly on rice genetics and breeding. In this study, we used a bibliometric approach to analyze the trends of papers published by Chinese researchers on rice physiology and management. Data were collected from three major agronomic journals（i.e., Agronomy Journal, Crop Science, and Field Crops Research） by searching in the Web of Science on September 8, 2017. A total of 186 rice papers were published by Chinese researchers on crop physiology and management in the three journals since their establishment. Yearly average number of such papers was 1.6, 6.5, and 21.0 for the periods of 1993–2005, 2006–2011, and 2012–2017, respectively. Their quality in terms of citation performance has also improved significantly in the recent decade. Huazhong Agricultural University, Yangzhou University, and Nanjing Agricultural University were leading organizations and published 54.4% of all 186 papers. Huang Min of Hunan Agricultural University and Peng Shaobing of Huazhong Agricultural University published the most number of rice papers on crop physiology and management as the first and corresponding authors, respectively. Yield potential and nitrogen-related research such as nitrogen use efficiency, nitrogen management, and plant nitrogen diagnosis have been the research focuses for rice crop. In recent years, research on global warming including high temperature stress, direct seeding, zero tillage, Bt rice, and critical nitrogen dilution curve were becoming popular. New research is emerging on yield gap, rice ratooning, and simplified and reduced-input practices in rice production.

Technical efficiency and its determinants of the various cropping systems in the purple-soiled,hilly region of southwestern China

This study examines the technical efficiency(TE) differences among typical cropping systems of smallholder farmers in the purple-soiled hilly region of southwestern China.Household-,plot-,and crop-level data and community surveys were conducted to explore TE levels and determinants of typical cropping systems by using a translog stochastic frontier production function.Results indicate significant difference in TE and its determinants among cropping systems.The mean TEs of the rice cropping system(R),the rice-rape cropping system(RR),the rice-rape-potato cropping system(RRP),and the oil cropping system(O) are0.86,0.90,0.84,and 0.85,respectively,which are over 1.17 times higher than those of the maize-sweet potato-other crop cropping system(MSO) and the maize-sweet potato-wheat cropping system(MSW) at0.78 and 0.69,respectively.Moreover,Technical inefficiency(TIE) of different cropping systems is significantly affected by characteristics of the household as well as plot.However,the impact of land quality,mechanical cultivation conditions,crop structure,farming system,farm radius,household type,cultivated land area per capita,and annual household income per capitalon TIE vary by cropping system.Additionally,output elasticity of land,labor,and capital,as a group,is greater than the one of agricultural machinery and irrigation.Finally,when household-owned effective agricultural labor is at full farming capacity,optimal plot sizes for the R,RR,RRP,MSO,MSW,and 0 cropping systems are 1.12hm^2,0.35 hm^2,0.25 hm^2,2.82 hm^2,1.87 hm^2,and 1.17hm^2,respectively.

我国转基因作物的发展现状及安全管理

转基因作物是当今世界各国现代生物技术产业研究的热点,中国的转基因生物技术发展迅速,由于科学界对转基因作物对人类及生态环境利与弊的争论,政府应制定相应的政策、措施对其进行安全管理。本文论述了转基因作物在国际国内的发展现状,分析了转基因作物对人类及生态环境的利与弊以及关于我国转基因作物安全管理的几点思考。

DESIGN OF FARMLAND GIS FOR PRECISION AGRICULTURE

Precision Agriculture, also known as Precision Farming, or Prescription Farming, is a modern agriculture technology system, which brings ' precision' into agriculture system. All concepts of Precision Agriculture are established on the collection and management of variable cropland information. As the tool of collecting, managing and analyzing spatial data, GIS is the key technology of integrated Precision Agriculture system. This article puts forward the concept of Farmland GIS and designs Farmland GIS into five modules, and specifies the functions of the each module, which builds the foundation for practical development of the software. The study and development of Farmland GIS will propel the spreading of Precision Agriculture technology in China.

A Non-Destructive Time Series Model for the Estimation of Cherry Coffee Production

Coffee plays a key role in the generation of rural employment in Colombia.More than 785,000 workers are directly employed in this activity,which represents the 26%of all jobs in the agricultural sector.Colombian coffee growers estimate the production of cherry coffee with the main aim of planning the required activities,and resources(number of workers,required infrastructures),anticipating negotiations,estimating,price,and foreseeing losses of coffee production in a specific territory.These important processes can be affected by several factors that are not easy to predict(e.g.,weather variability,diseases,or plagues.).In this paper,we propose a non-destructive time series model,based on weather and crop management information,that estimate coffee production allowing coffee growers to improve their management of agricultural activities such as flowering calendars,harvesting seasons,definition of irrigation methods,nutrition calendars,and programming the times of concentration of production to define the amount of personnel needed for harvesting.The combination of time series and machine learning algorithms based on regression trees(XGBOOST,TR and RF)provides very positive results for the test dataset collected in real conditions for more than a year.The best results were obtained by the XGBOOST model(MAE=0.03;RMSE=0.01),and a difference of approximately 0.57%absolute to the main harvest of 2018.

Annual Rainfall and Dryland Cotton Lint Yield—Southern High Plains of Texas

Agriculture in the Texas High Plains (THP) is in a transition phase of producing crops with a diminishing supply of irrigation-water from the Ogallala aquifer to dryland production systems. This shift is driven by the fact that the depth to the water table of the Ogallala aquifer continues to increase. Dryland cotton production systems are prevalent in the southern counties of the THP and our purpose was to use the long-term dryland cotton lint yields from these counties as precursors of the future cotton production patterns that will emerge in this region. For this purpose, from 1972 to 2018, we calculated the ratio of dryland cotton lint yield per unit of annual rainfall at the county level. This ratio is called crop water productivity (CWP) and has units of mass per unit volume (g/m3). In our analysis, we used cotton lint yield data provided by the National Agricultural Statistics and rainfall data provided by the National Oceanic and Atmospheric Administration. Our results indicated that the three datasets used in our analysis, i.e., cotton lint yield, rainfall and CWP were all normally distributed. In this time period, 1972 to 2018, only one year 2011—a year with a record drought of 179 mm of rain failed to produce a dryland cotton crop in all the counties used in our analysis. The mean cotton lint yield ± standard deviation ranged from a high of 400 ± 175 kg/ha in Lubbock County to a low of 252 ± 144 kg/ha in Andrews County. However, the counties with the largest CWP > 90 g/m3 were Glasscock, Midland and Martin County. The importance of this result is that these counties are in the southern region of the THP and are subject to extreme environmental conditions and yet cotton producers manage to produce a cotton crop in most years. We conclude that management production methods used by these dryland producers represent the future schemes that will need to be adopted in other counties to sustain the emerging dryland cropping systems across the THP.

Development and evaluation of low-altitude remote sensing systems for crop production management

Precision agriculture accounts for within-field variability for targeted treatment rather than uniform treatment of an entire field.It is built on agricultural mechanization and state-of-the-art technologies of geographical information systems(GIS),global positioning systems(GPS)and remote sensing,and is used to monitor soil,crop growth,weed infestation,insects,diseases,and water status in farm fields to provide data and information to guide agricultural management practices.Precision agriculture began with mapping of crop fields at different scales to support agricultural planning and decision making.With the development of variable-rate technology,precision agriculture focuses more on tactical actions in controlling variable-rate seeding,fertilizer and pesticide application,and irrigation in real-time or within the crop season instead of mapping a field in one crop season to make decisions for the next crop season.With the development of aerial variable-rate systems,low-altitude airborne systems can provide high-resolution data for prescription variable-rate operations.Airborne systems for multispectral imaging using a number of imaging sensors(cameras)were developed.Unmanned aerial vehicles(UAVs)provide a unique platform for remote sensing of crop fields at slow speeds and low-altitudes,and they are efficient and more flexible than manned agricultural airplanes,which often cannot provide images at both low altitude and low speed for capture of high-quality images.UAVs are also more universal in their applicability than agricultural aircraft since the latter are used only in specific regions.This study presents the low-altitude remote sensing systems developed for detection of crop stress caused by multiple factors.UAVs,as a special platform,were discussed for crop sensing based on the researchers'studies.

The effects of phenolic acid on nitrogen metabolism in Populus 3 euramericana ‘Neva’

The declines in soil fertility and productivity in continuously cropped poplar plantations axe related to phenolic acid accumulation in the soil. Nitrogen is a vital life element for poplar and whether the accumulation of phenolic acid could influence nitrogen metabolism in poplar and thereby hinder continuous cropping is not clear. In this study, poplar cuttings of Populus × euramericana ‘Neva＇ were potted in vermiculite, and phenolic acids at three concentrations （032, 0.5X and 1.0X） were added according to the actual content （1.0X） in the soil of a second-generation poplar plantation. Each treatment had eight replicates. We measured gas exchange parameters and the activities of key enzymes related to nitrogen metabolism in the leaves. Leaf photosynthetic parameters varied with the concentration of phenolic acids. The net photosynthetic rate （PN） significantly decreased with increasing phenolic acid concentration, and non-stomatal factors might have been the primary limitation for PN- The activities of nitrate reductase （NR）, glutamine synthetase （GS） and glutamate synthase （GOGAT）, as well as the contents of nitrate nitrogen, ammonium nitrogen, and total nitrogen in the leaves decreased with increasing phenolic acid concentration. This was significantly and positively related to PN （P 〈 0.05）. The low concentration of phe- nolic acids mainly affected the transformation process of NO3- to NO2-, while the high concentration of phenolic acids affected both processes, where NO3- was transferred to NO2- and NH4＋ was transferred to glutamine （Gln）. Overall, phenolic acid had significant inhibitory effects on the photosynthetic productivity of Populus x euramericana ＇Neva＇. This was probably due to its influence on the activities of nitrogen assimilation enzymes, which reduced the amount of amino acids that were translated into protein and enzymes. Improving the absorption and utilization of nitrogen by plants could help to overcome the problems caused by continuous cropping.

Effects of crop residue managements and tillage practices on variations of soil penetration resistance in sloping farmland of Mollisols

Soil penetration resistance(SPR)is one of the major indicators of soil physical properties.Crop residue managements,tillage practices and their interactions exert significant effects on the SPR.However,rare information is available in the sloping farmland of Mollisols.Field experiments were conducted to investigate the variations of the SPR as affected by crop residue managements and tillage practices on the sloping land in Northeast China from 2015 to 2019.The split-plot experiment was arranged with two crop residue managements(removed,REM and retained,RET),and three tillage practices(no tillage,NT;rotary tillage,RT;plow tillage,PT).SPR data in 0-80 cm soil depth was measured at the end of harvest of maize monoculture.Results showed that the two crop residue managements induced significant variations in the SPR at 0-15 cm,15-30 cm and 0-80 cm soil depths under NT,RT,and PT treatments,respectively.In comparison with RET treatment,the average values of the SPR under REM treatment were 10.9%and 8.9%higher in 45-60 cm and 60-80 cm soil depths,respectively.The average values of the SPR under PT treatment were 12.4%and 14.1%lower in 0-15 cm soil depth,and 23.9%and 10.4%lower in 15-30 cm soil depth than those under NT and RT treatments.However,the average value of the SPR under PT treatment was 11.2%and 22.0%higher in 60-80 cm soil depth than those under NT and RT treatments,respectively.The SPR generally decreased with the slope position declined in the deeper soil depth(except for the NT+RET treatment).The findings from this research can provide a scientific reference for the establishment of rational cultivation and the sustainable development of productivity on the sloping land of Mollisols in cold regions.

A new framework for GEOBIA: accurate individual plant extraction and detection using high-resolution RGB data from UAVs

Citrus(Citrus reticulata),which is an important economic crop worldwide,is often managed in a labor-intensive and inefficient manner in developing countries,thereby necessitating more rapid and accurate alternatives tofield surveys for improved crop management.In this study,we propose a novel method for individual tree segmentation from unmanned aerial vehicle remote sensing(RS)using a combination of geographic object-based image analysis(GEOBIA)and layer-adaptive Euclidean distance transformation-based watershed segmentation(LAEDT-WS).First,we use a GEOBIA support vector machine classifier that is optimized for features and parameters to identify the boundaries of citrus tree canopies accurately by generating mask images.Thereafter,our LAEDT workflow separates connected canopies and facilitates the accurate segmentation of individual canopies using WS.Our method exhibited an F1-score improvement of 10.75%compared to the traditional WS method based on the canopy height model.Furthermore,it achieved 0.01%and 1.38%higher F1-scores than the state-of-the-art deep learning detection networks YOLOX and YOLACT,respectively,on the test plot.Our method can be extended to detect larger-scale or more complex structured crops or economic plants by introducing morefinely detailed and transferable RS images,such as high-resolution or LiDAR-derived images,to improve the mask base map.

Evolution of soil and water conservation in rain-fed areas of China

Rain-fed(dryland)farming is an ancient agricultural production system in China.It occurs widely across almost the whole country,especially in the Northwest and North China.The semi-arid Loess Plateau is the most important region of rain-fed farming in China,but unfortunately,soil erosion on the Loess Plateau area is the highest in China,and indeed amongst the highest in the world.This highlights the necessity for developing practices that can reduce soil and water erosion,improve soil water use efficiency,improve crop productivity,and reduce rural poverty in the region.Many techniques of soil and water conservation are being used in rain-fed areas of China,including such systems as mulch,ridge and furrow systems.The Appendix describes a unique system of soil and water conservation,called Shatian.Modern research on conservation tillage(No Till),although essential for reducing erosion,increasing crop productivity,and ameliorating poverty,is just beginning in China.Modern conservation tillage research started in the1990s’with support from Australia and other countries.The procedures,however,were modified to be in accord with local conditions and prevailing farmer experiences.With 10 years of experimentation,results show that the most successful conservation practice on the Western Loess Plateau is no till with stubble retention.This technique helps to conserve soil water,increases soil organic carbon,improves soil structure and water infiltration,reduces soil and water erosion,and improves crop productivity and sustainability of rain-fed farming systems.However,its adoption rate remains low due to barriers such as traditional attitude,insufficient rural extension,and so forth.