Low-yield Fields Research Articles

A Review of Research on Obstacle Factor Reduction Techniques for Medium and Low Yield Fields

The proportion of low yield fields in China is large, and there are problems such as extensive utilization, low output rate, and poor soil quality. It is crucial to reduce obstacles and improve soil fertility and productivity in low yield fields. At present, the main obstacles to reducing soil acidification, salinization, nutrient imbalance, shallow tillage layer, continuous cropping obstacles, and soil erosion can improve soil quality and increase crop yield and quality. Future research should focus on developing more precise and efficient reduction technologies, introducing intelligent agricultural technologies for real-time monitoring and precise management, promoting soil nutrient management and integrated water and fertilizer technologies, and developing sustainable agricultural technologies to enhance farmland production potential and achieve efficient resource utilization.

Integrated management to achieve synergy in sugarcane production and quality in China

ContextSugar production in China is struggling to keep up with the increasing demand driven by rapid growth in sugar consumption. However, knowledge gap persists in terms of how to locate and concentrate the sugarcane production in advantageous areas to secure the production of high-quality sugarcane characterized by high sugar content, while also optimizing resource utilization. ObjectiveThe objective of the study was to explore the effects of environmental and management factors on sugarcane yield and quality (characterized by sugar content). Moreover, it sought to determine how China's future sugarcane needs could be met with fewer resource inputs through production optimization. MethodsThis study conducted a comprehensive search and compiled 411 groups of measured data from 64 peer-reviewed publications on sugarcane production in China. Additionally, a Random Forest model was developed based on trial data and farmer survey data to predict county-level sugarcane yield and quality in China. Taking into consideration China's projected sugarcane demand in 2030, this study proposed three sugarcane planting scenarios to explore potential pathways for future sugarcane production. These scenarios included: S0, where all sugarcane acreages maintain their current level of production; S1, where medium- and low-yield (or quality) fields transition into high- and medium-yield (or quality) fields; and S2, where all sugarcane acreages strive for both high yield and high quality. ResultsResults showed that overall field management could improve yield by 37.1 % and quality by 5.26 %. Soil organic matter (SOM), available phosphorus (AP), mean annual precipitation (MAP), and soil clay are the most important drivers of yield. pH, AP, total nitrogen (TN), and SOM are the most important drivers of quality. S2 scenario reduced land inputs by 11 %, nutrient inputs by 5 %, and irrigation inputs by 13 %, based on meeting future sugarcane demand in 2030. ConclusionsBy identifying and focusing on dominant planting areas, we can enhance the quality and efficiency of sugarcane cultivation as a response to China's future demand for sugarcane. This approach will not only meet future demands for sugarcane but also alleviate the dual pressures of limited resources and environmental concerns. SignificanceOur research provides a conceptual framework to enable China to meet its future sugar demand and consumption more efficiently and in an environmentally friendly manner, thereby conserving resources and reducing environmental impact.

Application of Metagenomics Technology in the Management of Middle and Low Yield Fields

Food security is an important guarantee for world peace and development, an important foundation for building a community with a shared future for mankind, and bears on the sustainable development, future and destiny of mankind. With the growth of population and the acceleration of urbanization, cultivated land resources are increasingly strained, and as an important part of cultivated land resources, the problems of unstable output and low utilization rate of medium and low yield land have gradually become prominent, which has become an important factor restricting the sustainable development of agriculture. In recent years, metagenomics technology, as a powerful research tool, has enhanced people's understanding of the composition, distribution and diversity of microorganisms in different environments, and has been widely applied in the field of farmland soil microorganisms. In this paper, the concept and technical process of metagenomics are reviewed, and the application and development prospect of metagenomics in soil microbial research in middle-low yield field management are reviewed.

Culturomics and Amplicon-Based Metagenomic Insights into the Bacteria of Soils with High Yield of Oryza sativa L. subsp. Japonica

The bacterial community in the paddy field agroecosystem has a pivotal role in the growth adaptability strategy of rice. Here, we studied the bacterial community structure composition of rhizosphere and non-rhizosphere soil samples from super rice in high-yield (920.99 kg/mu) and low-yield (785.30 kg/mu) fields of Japonica Chu 54 using both culturomics and amplicon-based metagenomics approaches. Using amplicon sequencing, a total of 54 phyla and 1167 genera of high-yield field bacteria were detected, while the low-yield field bacteria were distributed in 49 phyla and 865 genera. In addition, compared with low-yielding fields, there were significant differences in the composition and abundance of the same members in high-yielding fields. The node microorganisms in high-yield and low-yield fields were Anaeromyxobacterium and HSB_OF53-F07, respectively. Culturomics analysis unveiled a diverse array of bacterial taxa, encompassing four phyla, 113 genera, and 331 species, including 33 new undescribed lineages. The culturomics and high-throughput sequencing results indicate a widely adapted and highly abundant group of Exiguobacterium, which has broad prospects for application due to its extensive survival characteristics and plant growth-promoting functions. In summary, we analyze the bacterial community structure composition of rhizosphere and non-rhizosphere soil samples from super rice in high-yield and low-yield fields of Japonica Chu 54 using culturomics and amplicon sequencing techniques to better develop positive promotion strategies that adapt to its unique ecological environment.

Analysis of the Current Situation of Medium and Low Yield Fields in China

The area of medium to low yield farmland in China is huge and widely distributed. As a strategic reserve farmland resource, it is of great significance for ensuring food security. This article systematically reviews the problems of declining fertility, organic matter content, and biodiversity in China's medium and low yield fields, and clarifies the focus on the development of ecological improvement materials in the future. This helps to explore the path to improve green, high yield, and efficient production capacity in low to medium yield fields, and promote the achievement of food security and sustainable development goals.

Estimation of soil water and organic matter content in medium and low yield fields of Ningxia Yellow River Irrigation area based on hyperspectral information.

Accurately obtaining soil water and organic matter content is of great significance for improving soil qua-lity in croplands with medium to low yield. We explored the estimation effect of fractional order differentiation (FOD) combined with different spectral indices on soil water and organic matter content in medium and low yield croplands of Ningxia Yellow River Irrigation Area. After root mean square transformation of field measured hyperspectral reflectance, we used 0-2 FOD (with a step length of 0.25) to construct difference index (DI), ratio index (RI), product index (PI), sum index (SI), generalized difference index (GDI), and nitrogen planar domain index (NPDI) and to select the optimal spectral index based on the correlation coefficients between six spectral indices with soil water and organic matter contents. We constructed a model for estimating soil water and organic matter content based on partial least squares regression (PLSR) and support vector machine (SVM). The results showed that the correlation between soil water and organic matter content and spectral information was effectively improved after FOD transformation compared with the original spectrum, with maximum increases of 0.1785 and 0.1713, respectively. The soil water content sensitive bands were mainly in the range of 400-630 and 1350-1940 nm, while the sensitive bands of organic matter content were mainly at 460-850, 1530-1910, and 2060-2310 nm. The accuracy of SVM model was significantly higher than that of PLSR, and the soil water content estimation model based on 1.75-order NPDI-SVM reached the highest precision, with a validation determination coefficient (Rp2) of 0.970, root mean square error (RMSE) of 1.615, and relative percent deviation (RPD) of 4.211. The organic matter content estimation model based on 0.5 order DI-SVM had the best performance, with Rp2, RMSE and RPD of 0.983, 0.701 and 5.307, respectively. Our results could provide data and technological support for soil water and nutrient monitoring, quality improvement, and graphics creating in similar area with medium to low yield fields.

Effect of High-volume Straw Returning and Applying Bacillus on Bacterial Community and Fertility of Desertification Soil

This study was conducted to explore the fertilization potential of the high-volume straw returning mode in cooperation with Bacillus and other functional flora on desertification soil and to analyze the changing characteristics of soil carbon, nitrogen, and phosphorus components and functional activities of flora, so as to provide a basis for efficiently improving desertification soil fertility. A randomized block experiment was conducted, setting straw not returning to field (CK) and high-volume straw returning of 6.00 kg·m-2 (ST1), 12.00 kg·m-2 (ST2), 24.00 kg·m-2+(ST3), 6.00 kg·m-2+Bacillus (SM1), 12.00 kg·m-2+Bacillus (SM2), and 24.00 kg·m-2+Bacillus (SM3). In this study, we conducted a randomized block experiment to investigate the effect of the treatment for soil microbial and nutrient contents using 16S rRNA high-throughput sequencing and soil biochemical properties analysis. Our results showed that:① the α diversity of the soil bacterial community was significantly reduced by the combination of high-volume straw returning and Bacillus application. ② The single mode of high-volume straw returning significantly enriched Proteobacteria and decreased the relative abundance of Actinobacteriota, and the effect of the combined application of Bacillus on the variability of bacterial community structure was more significant. At the genus level, the relative abundance of beneficial bacteria such as Pseudomonas, Rhodanobacter, and Bacillus increased significantly. ③ The functional prediction based on FAPROTAX found that the high-volume straw returning combined with Bacillus could significantly improve the decomposition potential of soil flora to organic substances and the transformation potential of nitrogen components. ④ Compared with that in the control, the application of Bacillus with high-volume straw returning significantly increased the contents of soil organic matter, total phosphorus, and available phosphorus by 31.20-32.75 g·kg-1, 0.11-0.18 g·kg-1, and 29.69-35.09 mg·kg-1, respectively. In conclusion, the application of Bacillus in the sand-blown area with a high-volume straw returning can notably improve the contents of soil organic matter and phosphorus components, the functional activity of bacteria, and the abundance of beneficial bacteria, which is of great significance to the rapid improvement of soil fertility in the middle- and low-yield fields in arid areas.

Planning Spatial Layout of a Typical Salt Tolerant Forage of Sweet Sorghum in the Yellow River Delta via Considering Resource Constraints, Nitrogen Use Efficiency, and Economic Benefits.

In order to effectively address the issue of severe soil salinization in the coastal area of the Yellow River Delta, which has led to a significant number of medium and low-yield fields in this region, and to satisfy the rising demand for feed grain in China in recent years, a highly effective solution is to replace conventional crops by cultivating a specialized type of forage grass that can withstand high salinity levels and is well adapted to the local climate. This study proposed a spatial layout scheme for planting salt-tolerant forages, with the aim of providing a foundation for enhancing saline-alkali land and increasing resource utilization efficiency. The results showed that the climate conditions in the Yellow River Delta were suitable for planting sweet sorghum. With respect to soil salt content, the suitable planting regions for sweet sorghum can be classified into four categories: Suitable, moderately suitable, less suitable, and unsuitable, with soil salt concentrations of 2.62-5.25‱, 5.25-7.88‱, respectively. Concerning economic benefits, sweet sorghum's input-output ratio (74.4%) surpasses that of cotton in high saline-alkali zones, providing a significant advantage in comparison with traditional crops. In non-saline-alkali and light saline-alkali areas, the traditional winter wheat-summer maize planting system offers higher economic benefits and nitrogen use efficiency, so it is recommended to maintain this system as the dominant agricultural model. In moderately and severe saline-alkali zones, although one-season maize exhibits greater nitrogen efficiency, its economic benefits are lower than those of sweet sorghum. Hence, it is advisable to promote one-season maize in suitable regions and introduce salt-tolerant forage, such as sweet sorghum in other areas. This approach offers novel ideas and methods for crop spatial layout planning and addresses potential feed grain shortages in the region.

A GIS-based framework for local agricultural decision-making and regional crop yield simulation

CONTEXTIn agricultural activities, the decision-making process is central to agricultural system management and subsequent crop yield. As a powerful tool in field-specific decision-making processes, crop simulation models have the potential to simulate crop yields on a large scale. However, their performance is often biased by the spatial heterogeneity of environment and management factors when applied over a large scale. OBJECTIVEThe major objectives of this study include: (1) Predicting and evaluating the annual yields of dominant crops with real rotation scenarios; (2) Locating fields with low crop yield and determining possible reasons; and (3) Evaluating the improvement for crop yield with different management strategies. METHODSThis study proposed a crop yield simulation framework at the regional level by coupling a cropping system model (CropSyst) with a geographic information system (QGIS) to provide more reliable information for the decision-making process. In the study of a cropland concentrated USGS sub-watershed (Hydrologic Unit Code: 031402030101) in Geneva County, Alabama, we estimated the annual yields of four regionally dominant crops (i.e., corn, cotton, soybean, and peanuts) from 2016 to 2018. Low yield fields were identified in the simulation results visualization. Moreover, four management strategies were tested at a field scale to improve annual yields. RESULTS AND CONCLUSIONSOverall, the simulated crop yields were significantly correlated with the recorded values (Pearson's r = 0.99). However, the performance of the regional model varied for different crops. The model achieved the best performance for soybean with a high index of agreement (0.93) and modeling efficiency (0.86). For cotton, the model achieved positive model efficiency (0.23) and a good index of agreement (0.59). For peanut and maize, the model fitted records well but not sensitive enough. According to the visualization of simulation results, we located fields with low yields. The low organic matter content and high sand percentage of the soil were the potential causes of the nitrogen deficiency, which leads to the low yield subsequently. In field scale tests, four proposed management strategies could increase the cotton yields as high as 74.4%. But some strategies would also increase greenhouse gas emissions at the same time. SIGNIFICANCEThis study bridges the gap between local cropping system models and the regional estimation of crop yields. The GIS-based crop simulation framework developed here demonstrates the potential of cropping system models to provide reliable information at a regional scale and hence significantly broadens their application in the agricultural decision-making process.

Effects of magnetic irrigation water treatment on growth and yield characteristics of Hibiscus sabdariffa L. under water deficit stress

Water deficit is one of the most important challenges for the agriculture, especially in the arid and semi-arid regions of the world.Due to the high potential of some medicinal plants for cultivation under environmental stresses, cultivation of these plants in the low-yield fields can be considered. Therefore, to reduce the negative effects of water deficit on the growth of Hibiscus sabdariffa L., a factorial experiment was conducted in a completely randomized design with three replications in the research greenhouse of agriculture faculty, Birjand University in 2017. The experimental treatments included the amount of irrigation water at four levels (100, 80, 60, and 40% of the field capacity) and irrigation treatment with magnetic water at three levels (non-magnetic water (control), magnetized water with one, and two times passing through the magnetic field). The results showed that the effects of irrigation water amount treatments on the all measured traits and magnetic irrigation treatments on the all traits except leaf number were significant. Also, the interaction effects of irrigation water amount × magnetic irrigation treatments were significant on the plant height, number of bolls per plant, fresh and dry weight of aerial parts, dry weight of roots, and dry weight of sepals. Reducing the amount of irrigation water from 100 to 40% of field capacity caused a decrease in the spade number, stem diameter, number of leaves, and fresh root weight by 34.7%, 23%, 40.6%, and 27.6%, respectively. The mean comparison of interaction effects of irrigation water amount × magnetic irrigation treatments showed that irrigation with double-magnetized water improved all the traits compared to the irrigation with non-magnetic water. Therefore, it seems that the application of magnetic irrigation can be considered as one of the strategies to reduce the negative effects of water deficit.

Progress and prospects of applied research on physical geography and the living environment in China over the past 70 years (1949–2019)

Physical geography is a basic research subject of natural sciences. Its research object is the natural environment which is closely related to human living and development, and China’s natural environment is complex and diverse. According to national needs and regional development, physical geographers have achieved remarkable achievements in applied basis and applied research, which also has substantially contributed to the planning of national economic growth and social development, the protection of macro ecosystems and resources, and sustainable regional development. This study summarized the practice and application of physical geography in China over the past 70 years in the following fields: regional differences in natural environments and physical regionalization; land use and land cover changes; natural hazards and risk reduction; process and prevention of desertification; upgrading of medium- and low-yield fields in the Huang-Huai-Hai region; engineering construction in permafrost areas; geochemical element anomalies and the prevention and control of endemic diseases; positioning and observation of physical geographical elements; and identification of geospatial differentiation and geographical detectors. Furthermore, we have proposed the future direction of applied research in the field of physical geography.

Detecting and Assessing Nondominant Farmland Area with Long-Term MODIS Time Series Images

While most land use and land cover (LULC) studies have focused on modeling, change detection and driving forces at the class or categorical level, few have focused on the subclass level, especially regarding the quality change within a class such as farmland. The concept of nondominant farmland area (NAF) is proposed in this study to assess within class variability and quantify farmland areas where poor environmental conditions, unsuitable natural factors, natural disasters or unsustainable management practices lead to poor crop growth and thus low yield. A 17-year (2000–2016) time series of the Normalized Difference Vegetation Index (NDVI) was used to develop a NAF extraction model with abnormal features in the NDVI curves and subsequently applied to Heilongjiang province in China. The NAF model was analyzed and assessed from three aspects: agricultural disasters, soil types and medium- and low-yield fields, to determine dominant factors of the NAF patterns. The results suggested that: (1) the NAF model was able to extract a variety of NAF types with an overall accuracy of ~80%. The NAF area accumulated more than 8 years in 17 years is 6.20 thousand km2 in Heilongjiang Province, accounting for 3.75% of the total cultivated land area; (2) the NAF had significant spatial clustering characteristics and temporal variability. 53.24% of the NAF accumulated more than 8 years in 17 years is mainly concentrated in the west of Heilongjiang Province. The inter-annual NAF variability was related with meteorological variations, topography and soil properties; and (3) the spatial and temporal NAF patterns seem to reflect a cumulative impact of meteorological disasters, poor farmland quality, and soil degradation on crop growth. The determinant factors of the observed NAF patterns differed across regions, and must be interpreted in the local context of topography, soil properties and meteorological environment. Spatial and temporal NAF variability could provide useful, diagnostic information for precision farmland management.

Exploring Options for Improving Potato Productivity through Reducing Crop Yield Gap in Loess Plateau of China Based on Grey Correlation Analysis

Differences in crop yield between different fields in the same region have existed for a long time. Methods for improving the productivity of low-yield fields are a hot topic in large-scale agriculture. This experiment was carried out in potato planting farmland and at a potato experimental station in the Loess Plateau in China to study the effects of soil moisture and soil nutrients on potato yield potential and yield gap. The relationships between potato yield and soil nutrient factors were analyzed using the grey correlation method. The grey correlation method is a new technique for performing prediction, relational analysis and decision-making in many areas. The results indicate that (1) the high-yield group at the potato experimental station (HE) was 72,678 kg/ha; the mean-yield group at the potato experimental station (ME) was 36,083 kg/ha; the high-yield group in the potato planting farmland (HF) was 34,259 kg/ha; and the mean-yield group in the potato planting farmland (MF) was 19,386 kg/ha. (2) The yield gap (YG1) between HF and MF was 14,873 kg/ha; the yield gap (YG2) between ME and the MF was 16,697 kg/ha; the yield gap (YG3) between HE and the MF was 53291 kg/ha. (3) The effects of soil moisture and nutrients on potato yield were ranked from large to small: soil available potassium content > soil nitrate nitrogen content > soil organic matter content > soil water content > soil available phosphorus content. The results of correlation analysis and grey correlation analysis showed that the available potassium had the strongest correlation with potato tuber yield. (4) The content of nitrate nitrogen was significantly correlated with the content of available potassium and available phosphorus, while the water content was significantly correlated with the content of organic matter. According to the influence of soil moisture and nutrients on the potato tuber yield, it is suggested that integrated water and fertilizer cultivation measures be implemented, and the input of potash fertilizer and nitrogen fertilizer be increased.

The X-Factor in PE: Women in the Industry

Special Section: The Value and Future of Petroleum Engineering Employment of petroleum engineers is projected to grow 15% from 2016 to 2026, much faster than the average for all occupations. There is a strong movement within the industry and among the companies that comprise it to ensure that as this growth occurs, the percentage of women in the global workforce and in senior positions also grows. Increased gender diversity has been proven to benefit organizational performance through higher-quality teamwork, improved problem solving, greater creativity, and lower-risk decision making, as exemplified by the women interviewed for this article. Vicki Hollub, Occidental Petroleum Vicki Hollub, president and chief operating officer of Occidental Petroleum (Oxy), is the first female CEO of a major US oil company. She was appointed CEO in April 2016 during a severe downturn in the industry. Under Hollub, Oxy cut production costs in response to falling crude prices, but decided not to lay off employees, and focused instead on existing core operations in the Middle East, the US, and Colombia, and selling low-yield fields in the US and Middle East. Diana Hoff, Antero Resources Diana Hoff, vice president of operations for Antero Resources, says petroleum engineering has been a lifelong connection to her “pumper Grandpa” and a life’s work with meaning. Hoff began her career as a production engineer for Chevron in the US Gulf of Mexico, often supervising jobs such as wireline interventions and stimulations herself on site. Starting in production gave her the opportunity to interact with diverse groups across reservoir engineering, geoscience, drilling and completions, and joint ventures, and built a solid foundation in understanding the interactions among these groups and the needs of each to be effective. Karen Olson, Southwestern Energy Karen Olson, technology director for Southwestern Energy, is recognized for leading industry efforts to manage water use and become better stewards of fresh water. Her SPE Distinguished Lecture, “Freshwater Neutral: Managing Water Use and Giving Back to the Environment,” is based on her leading role in Southwestern Energy’s ECH2O— Energy Conserving Water—initiative to replenish or offset each gallon of fresh water used in hydraulic fracturing operations through conservation practices, projects, and technologies. Soma Chakraborty, Baker Hughes Soma Chakraborty is engineering technical leader for Baker Hughes, a GE company, an expert in nanotechnology, and a pioneer in its application in oilfield operations. Chakraborty, who holds a PhD in chemistry from the India Institute of Technology in Mumbai and completed a post-doctoral fellowship in nanotechnology at Rice University, joined Baker Hughes in 2008.

Some Thoughts on Using Biochar to Improve Albic Soil

Biochar of agricultural and forestry waste is one of the core ways to solve the greenhouse effect, and it is also the key measure to improve the land productivity of China’s low yield fields and realize the sustainable development of agriculture. Due to the large area of China’s albic soil, the long-term drought and flood disasters make it a typical low-yield field, which has not been effectively treated. Biochar provides new hope for improving low-yield albic soil. This paper introduces the basic properties of biochar, the albic soil formation mechanism, the low yield of albic soil factors and the improving theoretical basis of biochar. The paper introduces the technical features of the albic soil improvement and the advantages of the albic soil improvement by biochar. In the view of ascending low production potential, solving the greenhouse effect, achieving agricultural sustainable development, the application value and development prospects of albic soil improved by biochar are discussed.

Assessing causes of yield gaps in agricultural areas with diversity in climate and soils

Identification of causes of gaps between yield potential and producer yields has been restricted to small geographic areas. In the present study, we developed a novel approach for identifying causes of yield gaps over large agricultural areas with diversity in climate and soils. This approach was applied to quantify and explain yield gaps in rainfed and irrigated soybean in the North-Central USA (NC USA) region, which accounts for about one third of soybean global production. Survey data on yield and management were collected from 3568 producer fields over two crop seasons and grouped into 10 technology extrapolation domains (TEDs) according to their soil, climate, and water regime. Yield potential was estimated using a combination of crop modeling and boundary functions for water productivity and compared against highest producer yields derived from the yield distribution in each TED-year. Yield gaps were calculated as the difference between yield potential and average producer yield. Explanatory factors for yield gaps were investigated by identifying management practices that were concordantly associated with high- and low-yield fields. Management×TED interactions were then evaluated to elucidate the underlying causes of yield gaps. The chosen spatial TED framework accounted for about half of the regional variation in producer yield within the NC USA region. Across the 10 TEDs, soybean average yield potential ranged from 3.3 to 5.3 Mgha−1 for rainfed fields and from 5.3 to 5.6Mgha−1 for irrigated fields. Highest producer yields in each TED were similar (±12%) to the estimated yield potential. Yield gap, calculated as percentage of yield potential, was larger in rainfed (range: 15–28%) than in irrigated (range: 11–16%) soybean. Upscaled to the NC USA region, yield potential was 4.8Mgha−1 (rainfed) and 5.7Mgha−1 (irrigated), with a respective yield gap of 22 and 13% of yield potential. Sowing date, tillage, and in-season foliar fungicide and/or insecticide were identified as explanatory causes for yield variation in half or more of the 10 TEDs. However, the degree to which these three factors influenced producer yield varied across TEDs. Analysis of in-season weather helped interpret management×TED interactions. For example, yield increase due to advances in sowing date was greater in TEDs with less water limitation during the pod-setting phase. The present study highlights the strength of combining producer survey data with a spatial framework to measure yield gaps, identify management factors explaining these gaps, and understand the biophysical drivers influencing yield responses to crop management.

Energy-efficient oil extraction by sucker rod borehole pumps in low-yield fields

The efficiency of balanced drives, chain drives, and linear rack and pinion drives is compared for sucker rod pumps. An approach to energy-efficient oil extraction using the kinetic energy of the descending drilling stem is developed, and the corresponding mathematical model is derived. The results of numerical modeling are outlined.

Establishing Lettuce Leaf Nutrient Optimum Ranges Through DRIS Analysis

A survey of 78 commercial iceberg and romaine lettuce (Lactuca sativa L.) fields in the coastal valleys of central California was conducted in 2004–2005. Whole leaf samples were collected at early heading and again within 1 week of harvest. Diagnosis and Recommendation Integrated System (DRIS) leaf concentration norms were calculated for N, P, K, Ca, Mg, S, B, Zn, Mn, Fe, and Cu. Iceberg and romaine lettuce had sufficiently similar leaf nutrient concentrations that the data were combined in the DRIS calculations. Optimum leaf nutrient ranges were developed using data from high-yield fields in which all nutrients were in balance according to the DRIS approach. The DRIS-derived optimum ranges for K and Ca were substantially lower than previously published leaf sufficiency ranges, whereas for the other nutrients, the DRIS optimum ranges were in close agreement. Cu was the nutrient most frequently below the optimum range in low-yield fields. Comparison of leaf nutrient concentrations with soil nutrient availability and grower fertilization practices suggested that significant improvement in fertilizer management was possible.

Cotton Pest Management Strategies and Related Pesticide Use and Yield

The use of pesticides is an integral part of pest management for cotton (Gossypium hirsutum L.) production. However, in response to environmental and public safety concerns, alternative pest management strategies focused to reducing pesticide usage is becoming more important. The objective of this study is to evaluate various pest control practices as substitutes or complements to pesticides in maintaining or enhancing cotton yields. A tobit model is estimated using data from the 1994 USDA Cropping Practices Survey of cotton producers in the six major cotton-producing states to assess the effects of pest control strategies on yield and pesticide use in cotton production. Statistical tests were performed to assess the significance of differences between (i) high and low integrated pest management (IPM) fields, (ii) high and low pesticide use fields, and (iii) high and low yield fields, in terms of yield, pesticide use, use of individual IPM practices, and use of tillage and irrigation. High IPM fields had significantly higher yield, lower yield risk, and higher use of pesticide treatments than low IPM fields. High pesticide use fields generally used more IPM practices and had higher yield and lower yield risk than low pesticide use fields. High yield fields had lower yield risk, used significantly more IPM practices, but also used more pesticide treatments per acre than low yield fields.

Modification of agriculture landscape in three-river area in Xizang

The three-river area (the middle drainage area of the Yarlung Zangbo River between its tributaries of the Lhasa River and the Nyangqu River) is a rapid economic development area in Xizang(Tibet) Autonomous Region. As the weather in this area is frigid with frequent wind and little rain, the eco-environment condition is extremely bad, and the resistance and rehabilitation ability of the landscape system is weak. Therefore, in the implementation of agriculture development program in the area, it is not advisable to adopt the traditional method of changing grassland to agriculture land, instead, the agriculture landscape in the area should be modified. The primary contents of the modification plan are to improve the middle and low-yield fields to the high-yield fields with irrigation system, to transform the dry land on the slopes, uneven land, dry and low-yield fields to forest or grassland. So the problem of food demand will be solved and the degenerating trend of eco-environment will be controlled.