Single Crop Research Articles

Water Requirement of Naked Oats under Subsurface Drip Irrigation in the North Foot of Yinshan Mountain Based on Single Crop Coefficient Approach

In order to accurately and rapidly calculate the water requirement of naked oats under drip irrigation in the north foot of Yinshan Mountain, the study adopted the K c and calculation method for potential evapotranspiration recommended in document FAO56 and applied SCCA to calculate the water requirement of crops based on the deficient irrigation experiments. The results indicated that the water requirements of naked oats without drought influence was 383.8 mm, and the maximum daily average water requirement intensity was heading flowering, which was the critical period of crop water requirement, and the mean value of E T 0 in the whole growth period was 3.89 mm/d. After correction, K C of naked oats in the initial growth stage, crop development growth stage, mid-season growth stage, and late season growth stage was 0.34, 0.94, 1.05, and 0.36. The average K C of naked oats in the whole growth stage was 0.71. SCCA does not consider the influence of wetting depth in the initial growth period of crops and the correction of local irrigation in the mid-season and late season stage of crops. Therefore, when the irrigation quota of naked oats is 315 mm, the crop water requirement calculated by SCCA is 363.84 mm, which is about 10% different from the measured value. The results show that SCCA can be used to calculate the water requirement of naked oats under drip irrigation at the northern foot of Yinshan Mountain in Inner Mongolia, and the calculation error is within the allowable range. However, it is also necessary to consider the influence of different irrigation forms and plant height of crops on calculation value.

Does intercropping patterns of potato and safflower affect the density of Leptinotarsa decemlineata (Say), predators, and the yield of crops?

The impact of three intercrop patterns of potato (P), Solanum tuberosumL., and safflower (S), Carthamus tinctoriusL.: 4P:2S, 4P:4S, and 4P:8S (row ratios) along with single crops were examined on densities of the Colorado potato beetle (CPB),Leptinotarsa decemlineata(Say), biodiversity of predators, and yield profits over the growing season of potatoes in a randomized complete block design in 2019 and 2020 in Iran. The significant reduction in the densities of CPB (adults, eggs, and larvae) was seen in intercrops compared with single potato in either year. Accordingly, the damage index was decreased in intercrops than in single potato. Furthermore, intercrops resulted in an enhancement in the abundance of most predatory species of CPB, the Shannon diversity index (H΄), and the Pielou's evenness index (J'), especially in 4P:4S and 4P:8S than single potato. The values of R2 between the densities of CPB and the main predators were low (0.01 ≤ R2 ≤ 0.19) in June, whereas R2 values were significantly enhanced in July (0.13 ≤ R2 ≤ 0.71) and August (0.46 ≤ R2 ≤ 0.97). All intercrops delivered extra yield benefit compared with the single crops (LER ≥ 1.20 in 2019 and ≥ 1.18 in 2020). Our results disclosed that all intercrops, especially 4P:4S and 4P:8S could exercise in the controlling ofL. decemlineatain potato fields.

ALFACE E RABANETE EM MONOCULTIVO E CONSÓRCIO SOB DIFERENTES LÂMINAS DE ÁGUA EM AMBIENTE PROTEGIDO

ABSTRACT Vegetables intercropping of results in a better use of natural resources, water, light, and nutrients, when properly managed. The objective of this work was to evaluate the performance of lettuce and radish in single crop and intercropping systems under different irrigation water depths. The experiment was conducted in a protected environment at the State University of Maringá, in Maringá, Paraná, Brazil. A randomized block experimental design was used in a 4×2 factorial arrangement, with four replications. The first factor consisted of four irrigation water depths (60%, 80%, 100%, and 120% ETc), and the second factor consisted of two crop systems (single crop and intercrop). A drip irrigation system was used, consisting of constant water table lysimeters. The variables evaluated were: shoot fresh weight, root dry weight, and leaf area for the lettuce crop; total fresh weight, root fresh weight, and root diameter for the radish crop; and yield, water use efficiency, and land use efficiency index for both crops. Shoot fresh weight, leaf area, and yield of lettuce, and total fresh weight, root fresh weight, and yield of radish increased as the irrigation water depth applied was increased. Total fresh weight, root fresh weight, root diameter, and yield of the radish crop were higher in the intercropping system. The water use efficiency of both crops was higher in the single crop, and the land use efficiency index was higher in the intercropping system.

Further Evaluation of the performance of Shugor, Dubasi and Watish subtypes of Sudanese Desert sheep: Under Sedentary and Improved Production Systems

The present study was conducted in the National Sheep Research Station in Elhuda, Sudan where the sheep flocks are kept for scientific research purposes. The aim of the study is to evaluate two systems of sheep productivity namely: the prevailing annual single lamb cropping (sheer-sedentary) and induced three lamb cropping per two years to which feed supplementation is provided (improved – sedentary). Three subtypes: Shugor, Dubasi and Watish in Sudan Desert sheep were used for a three –lamp crops, per two years, in addition to feed supplementation, to represent an improved-sedentary system, (B) against a sheer sedentary (A), that represents an annual single-lamp-crop system. The improved sedentary was associated with reductions in the overall average values of the traits: ewes losses (1.95 vs 3.09%), ewe barrenness (17.30 vs 28.67%) and lambing interval (257.97 vs 353.50 days ), whereas it enhanced lambing rate (82.73 vs72.67 %), litter size at weaning measured: as lambs weaned per ewes exposed for breeding (1.01 vs 0.67) and as lambs weaned per ewes that actually lambed (1.12 vs 0.93) improved adjusted lamb weaning weight per ewe at 60 days of lamb age (13.62 vs 10.58 kg) , increased lamb survival rate (93.91 vs 75.63%) and eventually promoted productivity index (18.36 vs 5.25kg) of lambs weaned per ewe per year. These overall average values were calculated out of the mean values of the measured traits shown in tables (1 and 2) of the text. Furthermore, the comparison between the three subtype sheep groups for their performance as affected by the improved sedentary against the sheer - sedentary revealed similar trends of response as above, that culminated in the Shugor subtype having the greatest productivity index mean value (20.82 kg) as subsequently compared with that of either the subtype Dubasi (17.56 kg) or the Watish subtype (16.70 kg). It is concluded that these results do encourage the adoption and projection on the improved-sedentary system, specially, under the surroundings of irrigated agriculture land use to provide extra income to the welfare of the farmer.

Water footprint assessment of surface and subsurface drip fertigated cotton-wheat cropping system – A case study under semi-arid environments of Indian Punjab

The advanced methods of irrigation and nutrient supply may save huge quantity of costly inputs over the prevalent practice of surface flood (SF) irrigation and fertilizer broadcasting in Indian Punjab. Surface drip fertigation (SDF) and subsurface drip fertigation (SSDF) enables the combined application of fertilizer and irrigation for improving the input use efficiency in Cotton-Wheat cropping system (CWCS) over the SF. Though, both SDF and SSDF perform better than SF, but their suitability in reducing the water footprint (WF) of CWCS has been least assessed. Therefore, a 2 yr field study at two distinct agro-climatic zones has been conducted to quantify and compare the WF of SDF and SSDF in comparison to SF for CWCS under semi-arid environments. Results revealed that under SSDF, cotton and wheat crops consumed 32 and 37% lower water than respective SF, indicative of huge water saving over the prevalent practice. Contribution of green, blue and grey components towards total WF under SF was 42, 48 and 10% respectively for cotton, and 24, 59 and 18% for wheat. SSDF application at 80% crop evapotranspiration (ETc) along with 100% recommended dose of nitrogen remarkably reduced the WF without any yield loss for CWCS. Higher total WF for CWCS under SF (5.30 m³ kg⁻1) revealed it to be inferior as compared to SDF (3.71 m³ kg⁻1) and SSDF (3.52 m³ kg⁻1). Cotton alone consumed 65–78% of WFtotal of the CWCS, while the remaining 22–35% was attributed to wheat. A lowered WFtotal for CWCS under SDF and SSDF over that of SF elucidated them to be immensely helpful to conserve limited water resources under semi arid climates. A cropping system based assessment was much reliable option to obtain a clear indicator about the annual WF as compared to single crop based estimation. These results could be utilized to access the performance of alternative irrigation and cultivation systems for developing the WF reduction approach over extended geographical scale.

Producing food sustainably

Producing food sustainably

Determination of Crop Evapotranspiration and Single Crop Coefficients of Maize Using by a Weighing Lysimeter in Mediterranean Region in Turkey

Today, accurate irrigation approaches are of great importance due to climate change and a decrease in water resources. FAO methodology based on reference evapotranspiration (ET0) and crop coefficients (Kc) are commonly used worldwide to determine crop water requirements (ETc). Kc values of different plants for different areas can be taken from FAO-56 and FAO-24. However, crop coefficients must be determined or calibrated for every relevant region because the climate conditions in the field and surrounding conditions may not be similar to the standard conditions. For this purpose, what crop evapotranspiration and crop coefficients would be in the case of timely (first crop) and late sowing (second crop) of maize were investigated in this study in Adana where the Mediterranean climate characteristics are prevalent during 2012 and 2013 years. A weighing lysimeter was used to obtain ETc and Kc of maize. ET0 was calculated using the FAO-56 Penman-Monteith (PM56) method. The results showed that the duration of initial, development, mid-season, and end-season growth stages for first crop maize was 22, 26, 43, and 37 days totaling 128 days, and for second crop maize, it was 14, 24, 42, and 38 days totaling 118 days. The ETc value of the second crop maize was 14% higher than that value of the first crop maize. The mean Kc values were 0.74, 0.92, 1.63, and 0.42 at the initial, development, mid-season, and end-season growth stages for the first crop maize, whereas they were determined as 0.46, 0.89, 1.68, and 0.92, respectively for the second crop maize.

Misconceptions of Reference and Potential Evapotranspiration: A PRISMA-Guided Comprehensive Review

One of the most important parts of the hydrological cycle is evapotranspiration (ET). Accurate estimates of ET in irrigated regions are critical to the planning, control, and regulation of agricultural natural resources. Accurate ET estimation is necessary for agricultural irrigation scheduling. ET is a nonlinear and complex process that cannot be calculated directly. Reference evapotranspiration (RET) and potential evapotranspiration (PET) are two primary forms of ET. The ideas, equations, and application areas for PET and RET are different. These two terms have been confused and used interchangeably by researchers. Therefore, terminology clarification is necessary to ensure their proper use. The research indicates that PET and RET concepts have a long and distinguished history. Thornthwaite devised the original PET idea, and it has been used ever since, although with several improvements. The development of RET, although initially confused with that of PET, was formally defined as a standard method. In this study, the Preferred Reporting Item for Systematic reviews and Meta-Analysis (PRISMA) was used. Equations for RET estimation were retrieved from 44 research articles, and equations for PET estimation were collected from 26 studies. Both the PET and RET equations were divided into three distinct categories: temperature-based, radiation-based, and combination-based. The results show that, among temperature-based equations for PET, Thornthwaite’s (1948) equation was mentioned in 12,117 publications, whereas among temperature-based equations for RET, Hargreaves and Samani’s (1985) equation was quoted in 3859 studies. Similarly, Priestley (1972) had the most highly cited equation in radiation-based PET equations (about 6379), whereas Ritchie (1972) had the most highly cited RET equations (around 2382) in radiation-based equations. Additionally, among combination-based PET equations, Penman and Monteith’s (1948) equations were cited in 9307 research studies, but the equations of Allen et al. (1998) were the subject of a significant number of citations from 23,000 publications. Based on application, PET is most often applied in the fields of hydrology, meteorology, and climatology, whereas RET is more frequently utilized in the fields of agronomy, agriculture, irrigation, and ecology. PET has been used to derive drought indices, whereas RET has been employed for single crop and dual crop coefficient approaches. This work examines and describes the ideas and methodologies, widely used equations, applications, and advanced approaches associated with PET and RET, and discusses future enhancements to increase the accuracy of ET calculation to attain accurate agricultural irrigation scheduling. The use of advanced tools such as remote sensing and satellite technologies, in addition to machine learning algorithms, will help to improve the accuracy of PET and RET estimates. Researchers will be able to distinguish between PET and RET in the future with the use of the study’s results.

At Which Spatial Scale Does Crop Diversity Enhance Natural Enemy Populations and Pest Control? An Experiment in a Mosaic Cropping System

The importance of plant richness to enhance the presence, biodiversity and efficiency of natural enemies in agricultural systems has largely been studied and demonstrated these last decades. Planting and preserving non-crop plants or manipulating crop richness in fields are practices that have proven their efficiency. However, the impact of crop-richness continuity in space and time on pests and natural enemies at a landscape scale remains poorly studied. In a two-year study, we assessed the effect of crop richness (single crop vs. multiple crops) on pest and natural enemy abundance and spillover in a field experiment in north-east China. Overall, we found crop diversity had a limited impact on pest and natural enemy abundance at the spatial scale tested (0.025 vs. 0.2 ha). The total pest and natural enemy abundances were not different between single-crop and multi-crop plots in either year, and the community composition at the functional group level was mostly determined by the crop but not crop diversity. However, we found that crop diversity influenced the numeric response of ladybirds to aphids in wheat; their negative response (higher abundance where aphid abundance was lower, suggesting predation) was attenuated in multi-crop plots (no correlation of aphid and ladybird abundance, suggesting the use of alternative resources). This pattern was not found in maize. Finally, crop succession enhanced the spillover of ladybirds from wheat and maize to cotton plots but with limited benefits for aphid control. Because of these limited impacts, we hypothesized that crop diversity may benefit natural enemy populations and enhance pest control at larger spatial scales; while we found similar abundances of ladybirds between our small (0.025–0.2 ha) plots and in large (2 ha) close-by cotton fields, aphid abundances were more than ten times higher in large cotton fields. Our study highlights the need to accurately estimate the spatial scale at which crop biodiversity may benefit pest control, in relation to the ecology of the target pest and natural enemies.

Monitoring and Identification of Agricultural Crops through Multitemporal Analysis of Optical Images and Machine Learning Algorithms.

The information about where crops are distributed is useful for agri-environmental assessments, but is chiefly important for food security and agricultural policy managers. The quickness with which this information becomes available, especially over large areas, is important for decision makers. Methodologies have been proposed for the study of crops. Most of them require field survey for ground truth data and a single crop map is generated for the whole season at the end of the crop cycle and for the next crop cycle a new field survey is necessary. Here, we present models for recognizing maize (Zea mays L.), beans (Phaseolus vulgaris L.), and alfalfa (Medicago sativa L.) before the crop cycle ends without current-year field survey for ground truth data. The models were trained with an exhaustive field survey at plot level in a previous crop cycle. The field surveys begin since days before the emergence of crops to maturity. The algorithms used for classification were support vector machine (SVM) and bagged tree (BT), and the spectral information captured in the visible, red-edge, near infrared, and shortwave infrared regions bands of Sentinel 2 images was used. The models were validated within the next crop cycle each fifteen days before the mid-season. The overall accuracies range from 71.9% (38 days after the begin of cycle) to 87.5% (81 days after the begin cycle) and a kappa coefficient ranging from 0.53 at the beginning to 0.74 at mid-season

Actual Evapotranspiration for Sugarcane Based on Bowen Ratio-Energy Balance and Soil Water Balance Models with Optimized Crop Coefficients

Evapotranspiration is an important parameter to evaluate soil water deficit and water use efficiency, especially in locations with irregularly distributed precipitation. The aim of this study was to assess the daily actual evapotranspiration (ETa) estimated by the Thornthwaite and Mather soil water balance adapted for crops (ThM) and by the dual Kc method with the crop coefficients optimized from inverse modeling and by the adjustment suggested in the FAO-56 bulletin. The models were optimized and evaluated with actual evapotranspiration determined by the Bowen ratio – energy balance method (ETβ) for sugarcane at full canopy closure grown in Alagoas state, northeastern Brazil. The objective function of the inverse problem was defined in terms of ETβ and ETa estimated by the ThM or dual Kc method by optimizing the single crop coefficient (Kc) and the basal crop coefficient Kcb, respectively. Optimized Kc (1.05) and Kcb (1.03) were lower than those adjusted by the Kc FAO56 method (Kc = 1.25 or Kcb = 1.20), with optimized Kc slightly higher than the Kc obtained experimentally (1.01 ± 0.08). ETa estimated by the ThM and dual Kc method with optimized crop coefficients had similar high precision (r2 > 0.79) and accuracy (dm > 0.93 and RMSE < 0.30 mm d−1). However, using the coefficients adjusted from the FAO56 method overestimated ETa in both models.

Monitoring Key Wheat Growth Variables by Integrating Phenology and UAV Multispectral Imagery Data into Random Forest Model

Rapidly developing remote sensing techniques are shedding new light on large-scale crop growth status monitoring, especially in recent applications of unmanned aerial vehicles (UAVs). Many inversion models have been built to estimate crop growth variables. However, the present methods focused on building models for each single crop stage, and the features generally used in the models are vegetation indices (VI) or joint VI with data derived from UAV-based sensors (e.g., texture, RGB color information, or canopy height). It is obvious these models are either limited to a single stage or have an unstable performance across stages. To address these issues, this study selected four key wheat growth parameters for inversion: above-ground biomass (AGB), plant nitrogen accumulation (PNA) and concentration (PNC), and the nitrogen nutrition index (NNI). Crop data and multispectral data were acquired in five wheat growth stages. Then, the band reflectance and VI were obtained from multispectral data, along with the five stages that were recorded as phenology indicators (PIs) according to the stage of Zadok’s scale. These three types of data formed six combinations (C1–C6): C1 used all of the band reflectances, C2 used all VIs, C3 used bands and VIs, C4 used bands and PIs, C5 used VIs and PIs, and C6 used bands, Vis, and PIs. Some of the combinations were integrated with PIs to verify if PIs can improve the model accuracy. Random forest (RF) was used to build models with combinations of different parameters and evaluate the feature importance. The results showed that all models of different combinations have good performance in the modeling of crop parameters, such as R2 from 0.6 to 0.79 and NRMSE from 10.51 to 15.83%. Then, the model was optimized to understand the importance of PIs. The results showed that the combinations that integrated PIs showed better estimations and the potential of using PIs to minimize features while still achieving good predictions. Finally, the varied model results were evaluated to analyze their performances in different stages or fertilizer treatments. The results showed the models have good performances at different stages or treatments (R2 &gt; 0.6). This paper provides a reference for monitoring and estimating wheat growth parameters based on UAV multispectral imagery and phenology information.

Effect of fertigation with different pH and EC levels on selected physical soil properties

In this study, the effects of fertigation with different pH and EC level on soil physical properties such as aggregate formation (AF), aggregate stability (AS) and available water content (AWC) of soil were investigated. In the study, single crop tomato (Solanum lycopersicum, Anıt F1) was grown under cover for two consecutive years. A total of six fertigation applications (F1: pH 7.2/EC 2.0; F2: pH 7.2/EC 3.5; F3: pH 6.5/EC 2.0; F4: pH 6.5/EC 3.5; F5: pH 5.0/EC 2.0 and F6: pH 5.0/EC 3.5) were created, two different EC levels and three different pH levels. Fertigation applications were applied to the soil in three replications and the study was carried out in 18 plots in total. Based on our results, the effect of fertigation applications on the AF of the soil and the AWC during the year was not significant. On the contrary, the effect of fertigation on AS has occurred at different levels and degrees of importance in terms of the effect between years. Fertigation F5, which has a pH 5.0/EC 2.0 levels, caused a significant increase in the stability of 2-1 mm aggregates.

Oil Palm: A Global History

Oil Palm: A Global History

Impact of energy flow on dry deciduous forest of Barnawapara Wildlife Sanctuary of Central of India

The present paper, based on a study of five village ecosystems, assesses the energy efficiency of rain-fed agriculture in a dry tropical environment and the impact of agricultural activity on the surrounding natural ecosystems. Energy flow in the forest villages of Barnawapara Wildlife Sanctuary of Central India, along with it’s impact on the surrounding forests have been assessed and documented. Energy requirements such as firewood, food, fodder, and kerosene were inventoried. Energy efficiency was determined by calculating output-input ratio. Paddy was cultivated as single rainfed crop and except or rice all the food items in the villages were imported from the market. About 75-80% and 95-100% of the fodder and firewood needs were met from the forests, respectively. The use of firewood and kerosene in the study villages were 132 kg day -1 and 2 l day -1 . Firewood consumption was 185 x 10 5 KJ yr -1 ha -1 of cultivated land. Kerosene use ranged from 5 to 14 x 10 5 KJ yr -1 ha -1 . Fodder from the forests used for the livestock ranged between 324 to 606 x 10 5 KJ yr -1 ha -1 of cultivated land. The energy efficiency was 2.67 for all the cropped area. The illegal felling and lopping of trees was found to be increasing in concentric circles in and around the villages along with grazing, resulting into a savanna like situation. The study recommends conservation of forests by establishing fuel wood plantations, woodlots and pastures. For fulfilling the fodder requirements, village pastures should be developed with a mixture of grasses and legumes. All possible encouragement of reduction of livestock population needs to be given. Systematic fuel-wood plantations of fast-growing plants within the villages or their immediate environs would surely reduce the stress on the natural forests. Integration of fodder, fuel, and food, production through agroforestry and silvipasture systems needs to be experimented with and, when found effective, duly popularized. This may reduce the need for areas to be put under fodder and fuel-wood production. To reduce the existing levels of fuel-wood consumption, public awareness needs to be generated about the low efficiency of existing cooking practices and the pollution hazards from wood-burning. By the introduction of efficient wood-burning stoves it would be possible to reduce fuel-wood consumption. Possibilities of substitution of fuel-wood by other sources of energy—such as solar energy and kerosene— should be taken into consideration. Above all, efforts have to be made for alternative and complementary means of livelihood of the villagers—for the coupled optimal use of available man-days and economic well-being.

Leaf Disease Detection and Prevention Application

Abstract: Agriculture is the backbone of an economy. Farmers play a vital role in strengthening the economy of any country. Due to the diseases a crop undergoes due to various reasons, Food security is compromised and affects the crop production. A crop disease not only affects a single crop but tends to spread to the neighboring crops as well. Detection and cure of such diseases becomes very difficult for a farmer. This problem can be fixed by using an application that uses a Machine Learning system, which takes leaf image as an input and detects the disease suffered by any particular crop and shows the possible cure. Also considering the farmer’s location, Crops that are suitable to grow in the particular location can be displayed.

Rapid classification of tef [Eragrostis tef (Zucc.) Trotter] grain varieties using digital images in combination with multivariate technique

Varieties of a single crop type may vary in several attributes affecting the choice at different spots of the food supply chain. This paper demonstrates a rapid classification of ten tef [Eragrostis tef (Zucc.) Trotter] grain varieties based on image processing and multivariate data analysis. Extreme Gradient Boosted Tree Discriminant Analysis (EGBDA) was applied for the variety-based classification. The developed classification model achieved a remarkable classification performance with 97% of prediction accuracy and 99% of precision. A less complex classification model using eighteen selected variables also achieved similar classification performance. The developed technique can authenticate tef varieties at the research and industrial level. Although the finding of this study is remarkable, it is essential to incorporate additional tef varieties into the model and consider other sources of variation such as agroecology as an extension of this finding.

Comprehensive assessment of heavy metals in soil-crop system based on PMF and evolutionary game theory

The traditional assessment of farmland environmental quality usually focuses on soil heavy metals, but ignores agricultural produce safety. It is urgent to comprehensively assess the effects of farmland environmental quality based on soil quality and produce safety. To fill this gap, the comprehensive assessment method was improved based on previous studies, which was used to assess the pollution level of heavy metals in soil-crop system of Shenyang, Liaoning Province, Northeast China. In addition, this study also made a comprehensive analysis of pollution sources based on positive matrix factorization (PMF) model, and discussed soil-crop system income stability by evolutionary game theory. The mean concentrations of As, Cd, Cr, Hg, Pb, Cu, Zn, and Ni in soil exceeded the corresponding Shenyang soil background values (5.68 %, 14.36 %, 57.61 %, 7.86 %, 30.32 %, 5.21 %, 211.72 %, 171.88 %). The results showed that about 28.28 % of paired soil-crop points were polluted by heavy metals, especially rice-soil points. Furthermore, heavy metals in crops may be transmitted less from soil and more from other environmental media. The PMF analysis results showed that there were six pollution sources in study area, and the major contributor of pollution were agricultural activities, traffic-related activities, and industrial activities. In farmland environment protection, the only stable strategy is soil-crop system, and soil-crop system is better than the benefits of single soil or crop from the perspective of benefits. This study provides a scientific and reliable method to combine soil quality with produce safety to assess the risk of heavy metals in farmland.

Demand Analysis for Cereal Crops in Ethiopia

Cereals are common in Ethiopian diets, but the people’s consumption habits are complex, with no single crop dominating. Empirical analysis of cereal crop household demand is required to quantify household responses to cereal crop value changes and individual income changes. A purpose of this study is to assess demand for major cereal crops in Ethiopia using secondary data from Ethiopian Social Economic Survey 2018/19 (ESS) with 1700 households of cereal-growing consumers. This paper utilises descriptive statistics and Almost Ideal Demand System (AIDS) model to estimate demand parameters for major cereal crops. The empirical results showed that crop prices themselves, prices of other crops and demographic factors influence the share of grain expenditure. The estimated income elasticity of all sampled cereals is positive, and the Marshallian (unpaid) price elasticity is elastic while the compensated cross-price elasticity was inelastic. Household response to cereal crop demand decreases as commodity prices rise. Teff was the most price-sensitive commodity and classified as a luxury good because its income elasticity value was greater than one. Wheat, maize, and sorghum were designated as necessities, and all of the cereal crops studied in this work are considered normal goods. According to the study, the magnitude of price elasticity is greater than the expenditure elasticity of cereal crops. This implies that price has a greater influence than income. As a result, price regulation policies would be more effective than income targeting policies. Furthermore, the positive expenditure elasticity suggests that as income rises, so will demand for cereal crops. Policies aimed at increasing income would increase demand for cereals.

Identification of 'Start of Season' in Major Rainfed Crops of Tamil Nadu, India Using Remote Sensing Technology

Cropping seasons are the seasons in which a particular crop is grown. Identification of cropping seasons is crucial for successful cropping in rainfed areas. This research study focuses on the identification of major rainfed crop growing seasons in rainfed areas of Tamil Nadu using remote sensing technology. The MODIS (Moderate-Resolution Image Spectroradiometer) satellite product MOD13Q1 is utilized to produce NDVI (Normalized Difference Vegetation Index) of the study region. Then the NDVI values for each rainfed ground truth point were extracted and the value was used to produce a line graph representing the crop growing period. Likewise, multiple lines were produced for major rainfed crops: Rice, Maize, Pearl millet, Sorghum, Groundnut, Moth bean, Cotton and Chilli. The result reveals that the Maize and Cotton growing season starts in June-July, mostly single crop per year. Rice, Pearl millet, Sorghum and Chilli are also grown as a single crop per year, sowing by the month of October-November. Besides, there was a double-cropping area of Groundnut- Black gram and Groundnut-Moth Bean raised during June-July and October-November respectively.