Adoption Status of Direct Seeded Rice Technology by the Farmers of Punjab

Direct-seeded rice (DSR) is a possible alternative to conventional puddled transplantedrice, where rice crop is seeded directly in non-puddled fields. The study was conducted toascertain the adoption status of recommended practices of DSR. Personal interviews wereconducted to collect data from randomly selected 210 farmers from three districtsrepresenting different agro-climatic regions of Punjab. Study revealed that selected farmershad adopted DSR on 49.20 per cent of their total area under paddy cultivation. Slightlyhigher number of selected farmers had adopted Tar-Wattar, a new technique of DSR overdry soil method. Only 18.52 per cent respondents had applied first irrigation as perrecommendations of Tar-Wattar method, whereas majority (67.59%) had applied firstirrigation before 21 days. 26.67 per cent farmers had adopted most suitable variety PR-126 and sown it at recommended time. However, in case of other varieties, majority offarmers did not follow recommended time of sowing. A smaller number of farmers haveapplied zinc, iron and sulphur fertilizers to ameliorate micro nutrient deficiencies. Averageyield of others varieties and PR 126 were found to be nearly identical, but due to lessercost of cultivation in DSR as compared to transplanted rice, adopter farmers’ fetched highernet return.

Adaptation to saline intrusion for agriculture farming transformation in the coastal Ben Tre province, Vietnam

This study aimed to evaluate the adaptive capacity (AC) of agriculture farming transformation to improve for the adaptability by saline intrusion of those culture systems in the coastal Ben Tre province. The primary data was collected by questionnaires in three coastal districts of Ba Tri, Thanh Phu and Binh Dai with 178 households to distribute on agriculture land use transformations. An Object-Based Image Analysis (OBIA) and multi-temporal image analysis approach was developed to detect how LULC changes during 2010-2020 in the coastal Ben Tre province using Landsat TM and OLI data. The MODIS (MOD09 8-day reflectance) data was processed into monthly NDVI maps with the Time Series Product Tool software package and then used to classify regionally common rice crops LULC types using unsupervised classification by ISODATA algorithm. Based on primary data collection, evaluating adaptation measures was assessed the compilation of modification options based on a detailed description and criteria including human, society, infrastructure and natural conditions by standardized a weight ranges of adaptive indicators in the agriculture land use changes. The results detected five agriculture land use transformation including rice-shrimp crop rotation to aquaculture, single rice crop to aquaculture, double rice crop to perennial plant/orchards, double rice crop to rice-shrimp crop rotation, and triple rice crop to double rice crop. The adaptability of these transformations conducted the shrimp-rice crop rotation to aquaculture in Binh Dai of strongly high adaptability. Next is followed by double rice crops to orchards and double rice crops to rice-shrimp crop rotation with high adaptability while the rice-shrimp crop rotation to aquaculture is only moderate in Thanh Phu. The low adaptability levels were identified on single rice crop to aquaculture and triple rice crop to double rice crop transformations due to tolerant condition of saltwater for rice crop cultivation. The studies results can further contribute to support adaptation planning in these sectors by using, developing and streamlining this framework to additional and different socio-ecological contexts.

Monitoring Rice Crop and Paddy Field Condition Using UAV RGB Imagery

An effective crop management practice is very important to the sustenance of crop production. With the emergence of Industrial Revolution 4.0 (IR 4.0), precision farming has become the key element in modern agriculture to help farmers in maintaining the sustainability of crop production. Unmanned aerial vehicle (UAV) also known as drone was widely used in agriculture as one of the potential technologies to collect the data and monitor the crop condition. Managing and monitoring the paddy field especially at the bigger scale is one of the biggest challenges for farmers. Traditionally, the paddy field and crop condition are only monitored and observed manually by the farmers which may sometimes lead to inaccurate observation of the plot due the large area. Therefore, this study proposes the application of unmanned aerial vehicles and RGB imagery for monitoring rice crop development and paddy field condition. The integration of UAV with RGB digital camera were used to collect the data in the paddy field. Result shows that the early monitoring of rice crops is important to identify the crop condition. Therefore, with the use of aerial imagery analysis from UAV, it can help to improve rice crop management and eventually is expected to increase rice crop production.

Study of drought indices in relation to rice crop Production over some States of India

Drought monitoring indices used by India Meteorological Department (IMD) and National Remote Sensing Agency (NRSA) have been discussed in relation to crop estimates during kharif seasons of 1989 and 1990 for some States over India. It was found that index used IMD showed moderate to severe drought over certain areas during certain periods, while NRSA reported non-drought conditions. On the other hand, the preliminary estimated rice crop by the respective States during 1989 suggested higher values in four States and lower in one State, with reference to the mean values based, on the previous eight years data. A high degree of correlation between NRSA and IMD drought indices was found, which agree partially with the yield estimates during 1989.

Effect of weather on rice crop in Bhandara district. A curvilinear approach

Curvilinear technique has been applied to rice crop in Bhandara district (Maharashtra) to examine effects of rainfall, maximum temperature and relative humidity. Partial regression curves for estimating the rice yield by taking into account the .combined effect of these three factors have been worked out. It is observed that during the period of active growth rainfall is the most significant factor followed by maximum temperature and relative humidity in that order. The optimum value of total rainfall during the active growth phase was found as 1000 mm and those for maximum temperature and relative humidity as 30.5° C and 81% respectively.

A Review on Rice Crop Disease Classification Using Computational Approach

Rice is a significant cereal crop across the world. In rice cultivation, different types of sowing methods are followed, and thus bring in issues regarding sampling collection. Climate, soil, water level, and a diversified variety of crop seeds (hybrid and traditional varieties) and the period of growth are some of the challenges. This survey mainly focuses on rice crop diseases which affect the parts namely leaves, stems, roots, and spikelet; it mainly focuses on leaf-based diseases. Existing methods for diagnosing leaf disease include statistical approaches, data mining, image processing, machine learning, and deep learning techniques. This review mainly addresses diseases of the rice crop, a framework to diagnose rice crop diseases, and computational approaches in Image Processing, Machine Learning, Deep Learning, and Convolutional Neural Networks. Based on performance indicators, interpretations were made for the following algorithms namely support vector machine (SVM), convolutional neural network (CNN), backpropagational neural network (BPNN), and feedforward neural network (FFNN).