Adoption and Impacts of Zero-Tillage in the Rice-Wheat Zone of Irrigated Punjab, Pakistan

This study documents the adoption and impacts of zero-tillage (ZT) wheat in the ricewheat systems of Pakistan’s Punjab province primarily drawing on a detailed empirical survey of 458 rice-wheat farmers. Our random stratified sample revealed 19% to be ZT wheat adopters and a similar share of the wheat area in the surveyed communities to be under ZT. The study suggests that diffusion has stagnated and also flags the issue of disadoption (14%). ZT adopters, non-adopters, and disadopters differ significantly in terms of their resource bases, with adopters typically showing the most favorable values. ZT drastically reduces tractor operations in farmers’ ZT wheat fields from an average of 8 passes to a single pass, implying a saving of 7 tractor hours and 35 liters of diesel per hectare. ZT did not have any significant effect on the mean farmer estimated wheat yield of 3.3 tons per hectare. ZT also had no significant effect on water productivity for wheat or spillover effect on the subsequent rice crop. ZT primarily appears to be a cost-saving technology for wheat in Pakistan’s Punjab. Based on these findings, the study provides a number of recommendations for research and development in Pakistan Punjab’s rice-wheat systems.Wheat, Rice, Agricultural development, Drilling equipment, Economic analysis, Innovation adoption, Farming systems, Cropping patterns, Production costs, Zero tillage, Pakistan, Crop Production/Industries, E16, F08,

An Economic Analysis of the Abonera Maize Production System in the Atlantic Coast of Honduras

This paper compares the economics of the abonera maize production system, in which maize is grown in rotation with a green manure crop (velvetbean, Mucuna deeringiana), with traditional bush-fallow cultivation of maize in the Atlantic Coast area of Honduras. A probabilistic cost-benefit analysis of introducing velvetbean into the existing maize cropping pattern is carried out for the field, farm, and regional level. The probabilistic approach allows for a more comprehensive assessment of economic profitability, one which recognizes that farmers are interested in reducing production risk as well as obtaining increases in average net benefits. The analysis reveals that the abonera system provides significant returns to land and family labor over the six-year life cycle. The abonera is not only more profitable than the bush-fallow system but reduces the variability in economic returns, making second-season maize a less risky production alternative. Although the labor requirement per unit of land is smaller in the abonera system than that in the bush-fallow system, the larger area allocated to maize implies a net increase in labor requirements at the farm level. At the regional level, widespread adoption of the abonera system appears to have increased the importance of the second season in total maize production. Although a causal link to adoption of the abonera system cannot be established conclusively from the data, adoption of the system remains a likely explanation for the changes observed in aggregate maize production in the Atlantic Coast region. Land rental prices for sowing second-season maize also reflect the widespread impact of the abonera system.Crop Production/Industries,

Maize in China: Production Systems, Constraints, and Research Priorities

Crop Production/Industries, Research and Development/Tech Change/Emerging Technologies,

Adoption and Impacts of Zero-Tillage in the Rice-Wheat Zone of Irrigated Haryana, India

This study documents the adoption and impacts of zero-tillage (ZT) wheat in the rice-wheat systems of India’s Haryana State primarily drawing on a detailed empirical survey of 400 rice-wheat farmers. Our random stratified sample revealed 34.5% to be ZT wheat adopters and a quarter of the wheat area in the surveyed communities to be under ZT. The study suggests the potential for further diffusion but also flags the issue of disadoption (10%). ZT adopters, non-adopters, and disadopters differ significantly in terms of their resource bases, with adopters typically showing the most favorable values. ZT drastically reduces tractor operations in farmers’ ZT wheat fields from an average of 8 passes to a single pass, implying a saving of 6 tractor hours and 36 liters of diesel per hectare. At 4.4 tons per hectare, ZT achieved the highest wheat yields in the survey year, a significant 4.0% yield increase over conventional tillage. The higher yield and lower water use resulted in significantly higher water productivity indicators for ZT wheat. ZT did not have any significant spillover effect on the subsequent rice crop. The combination of a significant “yield effect” and “cost-saving effect” makes ZT adoption worthwhile and is the driving force behind its rapid spread and widespread acceptance, providing a much needed boost to economic returns to wheat cultivation. Based on these findings, the study provides a number of recommendations for research and development in Haryana’s rice-wheat systems.Wheat, Rice, Agricultural development, Innovation adoption, Drilling equipment, Farming systems, Zero tillage, Production costs, Credit, Income, India, Crop Production/Industries, E16, F08,

Rodent Biology and Management; Abstracts of papers presented at the International Conference on Rodent Biology and Management, held at Beijing, China, 5-9 October 1998

Farm Management,

A comprehensive dataset of vegetation states, fluxes of matter and energy, weather, agricultural management, and soil properties from intensively monitored crop sites in western Germany

Data description paperThe development and validation of hydroecological land-surface models to simulate agricultural areas require extensive data on weather, soil properties, agricultural management, and vegetation states and fluxes. However, these comprehensive data are rarely available since measurement, quality control, documentation, and compilation of the different data types are costly in terms of time and money. Here, we present a comprehensive dataset, which was collected at four agricultural sites within the Rur catchment in western Germany in the framework of the Transregional Collaborative Research Centre 32 (TR32) "Patterns in Soil-Vegetation-Atmosphere Systems: Monitoring, Modeling and Data Assimilation". Vegetation-related data comprise fresh and dry biomass (green and brown, predominantly per organ), plant height, green and brown leaf area index, phenological development state, nitrogen and carbon content (overall > 17 000 entries), and masses of harvest residues and regrowth of vegetation after harvest or before planting of the main crop (> 250 entries). Vegetation data including LAI were collected in frequencies of 1 to 3 weeks in the years 2015 until 2017, mostly during overflights of the Sentinel 1 and Radarsat 2 satellites. In addition, fluxes of carbon, energy, and water (> 180 000 half-hourly records) measured using the eddy covariance technique are included. Three flux time series have simultaneous data from two different heights. Data on agricultural management include sowing and harvest dates as well as information on cultivation, fertilization, and agrochemicals (27 management periods). The dataset also includes gap-filled weather data (> 200 000 hourly records) and soil parameters (particle size distributions, carbon and nitrogen content; > 800 records). These data can also be useful for development and validation of remote-sensing products. The dataset is hosted at the TR32 database (https://www.tr32db.uni-koeln.de/data.php?dataID=1889, last access: 29 September 2020) and has the DOI https://doi.org/10.5880/TR32DB.39 (Reichenau et al., 2020).Peer reviewe

Polyurethane foam as a soilless growing media: demonstrating the importance of physical property optimisation

Introduction: Increasing adoption of hydroponics in food production has increased the demand for soilless growing media. Given the variety of crops and cultivation techniques used in soilless systems, optimising the physical properties of novel media for specific crops and systems presents an opportunity, as some growing media, such as mineral wool, provide only a limited set of physical properties. Polyurethane foams (PUFs), a promising soilless growing media, offer flexibility, as foams with a diverse range of physical properties can be produced. Methods: We examined 10 distinct PUF formulations with a range of physical properties (cell size [d], open cell fraction [peff], maximum water uptake height [Hmax], water uptake rate [Wur]) through germination and growth trials. Additionally, investigations into whether these media influence disease susceptibility were conducted by inoculating tomato plants with Pythium spp. Results and discussion: Germination trials using lettuce and tomato identified four PUF formulations as unsuitable. A small-scale growth trial demonstrated that the remaining formulations performed comparably to mineral wool (MW). Three of these formulations were tested in trials for lettuce and pak choi in a NFT system and for tomato using a dripper-fed system. Results indicated that two PUF formulations surpassed MW in vegetative growth in tomato trials (F04: d = 669 µm, peff = 0.694, Hmax = 2.94 cm, Wur = 0.023 cm s-1; F08: d = 624 µm, peff = 0.38, Hmax = 2.35 cm, Wur = 0.012 cm s-1) and two PUF formulations matched MW in lettuce yield in NFT trials (F04: properties detailed above; F07: d = 683 µm, peff = 0.897, Hmax = 3.07 cm, Wur = 0.055 cm s-1). Pak choi plants in foam displayed slightly lower yields than those in MW, although differences were not significant. All foam samples suppressed Pythium inoculation, as evidenced by no reduction in germination rates or seedling mass when compared to the uninoculated samples, warranting further investigation into disease suppression. These growth results suggest that growing media physical properties should be optimised according to both hydroponic technique and crop to maximise yields and that PUF media can aid in developing tailored growing media for specific crop and systems

Effects of trade liberalization on agriculture in Pakistan : commodity aspects

This country report is the second part of the Pakistan country study in the Asian regional project organized by the United Nations ESCAP CGPRT Centre, Bogor, Indonesia, entitled &ldquo;Effects of Trade Liberalization on Agriculture in Selected Asian Countries with Special Focus on CGPRT Crops (TradLib)&rdquo; launched in China, India, Indonesia, Japan, Malaysia, Pakistan, the Philippines, Thailand, Viet Nam, and South Korea. The report of the first part of this project entitled &ldquo;Effects of Trade Liberalization on Agriculture in Pakistan: Institutional and Structural Aspects&rdquo; has already been published. The major objective of the first part of the project was to highlight and analyse institutional aspects of trade liberalization, including a review/analysis on history of the trade regime, various trade-related government policies, infrastructure related to foreign trade, and analysis of trade-related indicators. The TradeLib project was completed in three years, and it is a continuation of the Centre&rsquo;s earlier project on &ldquo;Market Prospects of Upland Crop Products and Policy Analysis in Selected Asian Countries (MPUPA)&rdquo; implemented in seven Asian countries including, China, India, Indonesia, Pakistan, the Philippines, Thailand, and Viet Nam. The present study is the second part of the TradeLib project implemented in Pakistan, and it attempts to quantify the impact of trade liberalization on food commodities (wheat, rice and maize) at the national level. Also it includes a case study to determine the area specific impact of trade liberalization on these commodities in the rice-wheat areas of Punjab, Pakistan.&nbsp;</p

Extensive literature search on cropping practices of host plants of some harmful organisms listed in Annex II A II of Directive 2000/29/EC

The European Commission is currently seeking advice from EFSA (Mandate M-2012-0272) to assess for Arabis mosaic virus, Raspberry ringspot virus, Strawberry latent ringspot virus, Tomato black ring virus, Strawberry mild yellow edge virus, Strawberry crinkle virus, Daktulosphaira vitifoliae, Eutetranychus orientalis, Parasaissetia nigra, Clavibacter michiganensis spp. michiganensis, Xanthomonas campestris pv. vesicatoria, Didymella ligulicola and Phytophthora fragariae the risk to plant health for the EU territory and to evaluate the effectiveness of risk reduction options in reducing the level of risk. In addition, the Panel is requested to provide an opinion on the effectiveness of the present EU requirements against these organisms laid down in Council Directive 2000/29/EC. As a consequence EFSA needs insight in the cropping practices of Citrus spp., Fragaria x ananassa, Ribes spp., Rubus spp., Vaccinium spp., Humulus lupulus, Vitis vinifera, Prunus armeniaca, P. avium, P. cerasus, P. domestica and P. persica, which are host plants for these pests. An extensive and systematic literature search was done in which scientific and grey/technical literature was retrieved from the 28 EU Member States, Iceland and Norway. All references were stored in EndNote libraries, separately for scientific literature and grey/technical literature. For each reference information is provided on the source/search strategy, the crop, the country, the topic (cropping practice, propagation, protection or irrigation (only for Citrus)) and protected cultivation vs. field production. Yields of references depended on the crop and on the country. Over 27,000 references were provided to EFSA. This allows EFSA to quickly find information on crop production, both indoors and outdoors, of all crops that were studied in this extensive literature search. The data can be used by EFSA for the present mandate, but are also an excellent basis for other current and future mandates

Pipe and Instrumentation Tag Extraction with Multimodal Large Language Models

LAUREA MAGISTRALEQuesta tesi esplora lo sviluppo di un nuovo approccio per automatizzare l’estrazione di tag da un’area evidenziata di diagrammi di tubazioni e strumentazione (Piping and Instru- mentation Diagram) o (P&ID) utilizzando Multimodal Large Language Models (MLLMs). I P&ID sono fondamentali per rappresentare il controllo e la strumentazione dei processi industriali, tuttavia l’estrazione manuale di informazioni rilevanti è laboriosa e soggetta a errori. Questa ricerca affronta queste sfide utilizzando una metodologia strutturata che sfrutta la comprensione multimodale avanzata dei MLLM, combinata con Image process- ing e Prompt engineering, per ottimizzare il processo di estrazione dei tag P&ID. Il fulcro di questo lavoro si concentra sul miglioramento della capacità del modello di rilevare ed estrarre accuratamente i tag da diagrammi complessi attraverso l’attenta preparazione e manipolazione dei dati di input. Sfruttando la capacità dei MLLMs per la comprensione contestuale e il riconoscimento di pattern, l’approccio migliora sia l’efficienza che la precisione. I risultati sperimentali dimostrano che l’approccio sviluppato migliora significativamente l’accuratezza e la velocità dell’estrazione dei tag, superando i metodi manuali tradizionali. Consente l’estrazione flessibile di informazioni dai diagrammi semplicemente modificando il prompt, eliminando la necessità di training un nuovo modello o di fine-tuning uno pre- trained, il che per questo compito potrebbe essere piuttosto costoso sia in termini di tempo che di costi. Inoltre, associa in modo univoco i tag estratti ai loro sottosistemi pertinenti, una capacità assente nei metodi precedenti. I risultati hanno potenziali implicazioni per i settori che si affidano alla documentazione del controllo di processo, fornendo un percorso verso una maggiore efficienza e affidabilità nell’estrazione di informazioni critiche.This thesis explores the development of a novel approach for automating the extraction of tags from a highlighted area of Piping and Instrumentation Diagrams (P&IDs) using multimodal large language models (MLLMs). P&IDs are crucial for representing the control and instrumentation of industrial processes, yet manual extraction of relevant information is labor-intensive and prone to errors. This research tackles these challenges by using a structured methodology that harnesses the advanced multimodal understanding of MLLMs, combined with image processing and prompt engineering, to optimize the P&ID tag extraction process. The core of this work focuses on enhancing the model’s ability to accurately detect and extract tags from complex diagrams through the careful preparation and manipulation of input data. By leveraging Multimodal large language models’ capacity for contex- tual understanding and pattern recognition, the approach improves both efficiency and precision. Experimental results demonstrate that the developed approach significantly enhances the accuracy and speed of tag extraction, outperforming traditional manual methods. It allows flexible extraction of information from diagrams by just modifying the prompt, eliminating the need for training a new model or fine-tuning a pretrained one which for this task could be quite expensive both in terms of Time and cost. Additionally, it uniquely associates the extracted tags with their relevant subsystems, a capability absent in previous methods. The findings have potential implications for industries that rely on process control docu- mentation, providing a pathway to greater efficiency and reliability in extracting critical information