Crop Index Research Articles

Effect of Sowing Dates and Wheat Cultivars on Agro Meteorological Indices of Wheat under Conditions of North-western Himalayas, India

Climate change in recent times have presented a scenario of elevated susceptibility of wheat to rising temperatures. Agro-meteorological indices can present a scenario of variable response of wheat to diverse conditions. A field investigation was conducted in rabi season of 2016-17 at Research farm, Department of Agronomy, CSK Himachal Pradesh Krishi Vishvavidyalaya, Palampur to evaluate the influence of sowing dates and wheat cultivars on agro-meteorological indices such as growing degree days, photothermal units, Helio thermal units and phenothermal index of wheat crop. The field investigation involved five sowing dates (15th October, 30th October, 15th November, 30th November and 15th December) and wheat cultivars (HPW-349 and HPW-155) which were studied in a factorial randomized block design with three replications. The results of the investigation revealed that timely sown crop i.e., on 15th October recorded the highest values for agro-meteorological indices for both the wheat cultivars such as growing degree days, Helio thermal units, photothermal units and phenothermal index across various wheat development stages such as complete emergence, crown root initiation, tillering, ear emergence and physiological maturity. Therefore, timely sowing of wheat by 15th October was concluded to be the best for optimized agro-meteorological indices such as growing degree days, photothermal units, Helio thermal units and phenothermal index under conditions of North-Western Himalayas.

Examining the Effects of Magneto Priming on Rice and Determination of Crop Indices from Absorption Spectrum for Ecological Yield

Examining the Effects of Magneto Priming on Rice and Determination of Crop Indices from Absorption Spectrum for Ecological Yield

Technological Innovation to Increase The Cropping Index of Rice on Rainfed Fields At Labuhanbatu Regency

The study of technological innovations to increase the cropping index in Rainfed Rice Fields aims to increase farmers’ knowledge and skills regarding rice farming so that their rice fields can be planted with rice more than once a year. This activity was conducted in Selat Beting Village, Panai Tengah District, Labuhan Batu Regency in 2021. The assessment was carried out in one area, consisting of the Field Laboratory (LL) location and the Field School (SL) location. The Field Laboratory is a study area covering an area of 5 ha. The treatmen use in this study was variety, seeding methods, planting methods, fertilizer dosage and pest control.The results of this study shown that the production of demo-farm area was 6.65 t/ha, while non-demo-farm only produced 4.76 t/ha. Farmers in Selat Beting village can plant rainfed rice at least twice a year. Selat Beting Village farmers have been introduced to rice farming business insurance (AUTP). Farmers who try to insure their crops do not mind because they pay very low premiums and are affordable for farmers. Based on rainfall patterns in Labuhanbatu Regency, farmers can plant rice at least twice a year, where in certain months there is rainfall, but it is not sufficient to irrigate the fields, therefore they must be assisted with shallow well pumps.

Phenotyping Peanut Drought Stress with Aerial Remote-Sensing and Crop Index Data

Peanut (Arachis hypogaea L.) plants respond to drought stress through changes in morpho-physiological and agronomic characteristics that breeders can use to improve the drought tolerance of this crop. Although agronomic traits, such as plant height, lateral growth, and yield, are easily measured, they may have low heritability due to environmental dependencies, including the soil type and rainfall distribution. Morpho-physiological characteristics, which may have high heritability, allow for optimal genetic gain. However, they are challenging to measure accurately at the field scale, hindering the confident selection of drought-tolerant genotypes. To this end, aerial imagery collected from unmanned aerial vehicles (UAVs) may provide confident phenotyping of drought tolerance. We selected a subset of 28 accessions from the U.S. peanut mini-core germplasm collection for in-depth evaluation under well-watered (rainfed) and water-restricted conditions in 2018 and 2019. We measured morpho-physiological and agronomic characteristics manually and estimated them from aerially collected vegetation indices. The peanut genotype and water regime significantly (p < 0.05) affected all the plant characteristics (RCC, SLA, yield, etc.). Manual and aerial measurements correlated with r values ranging from 0.02 to 0.94 (p < 0.05), but aerially estimated traits had a higher broad sense heritability (H2) than manual measurements. In particular, CO2 assimilation, stomatal conductance, and transpiration rates were efficiently estimated (R2 ranging from 0.76 to 0.86) from the vegetation indices, indicating that UAVs can be used to phenotype drought tolerance for genetic gains in peanut plants.

Partisipasi Petani dalam Program Indeks Pertanaman (IP) Padi 400 di Desa Kragan, Kecamatan Gondangrejo, Kabupaten Karanganyar

The Ministry of Agriculture conducted a program to increase the Rice Planting Index (IP) to 400 or commonly known as the IP400 program. One of the factors determining the success of the Rice Planting Index (IP) 400 program is the participation of farmers in following the program, because without active participation from farmers the program will not run smoothly. This study aims to assess the level of farmer participation, examine the factors that shape farmer participation, and analyze the relationship between the factors that shape farmer participation in the Rice 400 Cropping Index (IP) program in Kragan Village. Sampling was conducted using saturated sampling method (census) with a sample size of 30 respondents. Data analysis used the Spearman Rank Correlation Coefficient Test (rs) at the 95% confidence level. The results showed that the planning stage was in the medium category, while the implementation, utilization of results, and valuation stages were in the high category. The relationship between factors shaping farmer participation in the Rice 400 Planting Index (IP) program is that there is a significant relationship between non-formal education, personal experience of farmers in farming, the influence of people who are considered important, and land area with farmer participation in the IP Rice 400 program. Factors shaping farmer participation in the Rice 400 Planting Index (IP) program that do not have a significant relationship are the age of farmers and formal education of farmers.

Crop index insurance as a tool for climate resilience: lessons from smallholder farmers in Nigeria

Crop farmers in arid and semi-arid regions face a covariate risk that is of paramount importance, namely, the threat of catastrophic crop loss triggered by natural disasters and climate hazards. Such an occurrence not only jeopardizes the livelihoods of these farmers but may also lead to persistent poverty. Promoting sustainable development requires control over climate-related shocks, which negatively affect the most vulnerable population in the developing world. This study investigates the option of choosing crop area-yield index insurance to mitigate the adverse effects associated with climate stress. In addition, we assessed the amount farmers are willing to pay for an insurance product that insures yields below 70% of the local average in the study area. Our results show that access to extension services and economic association membership offers farmers social capital and encourages their decision to purchase index insurance. We also find that the long-run welfare impact of index insurance policy on vulnerable households could be significant as an alternative insurance mechanism to traditional insurance. This study contributes to filling the gaps on the uptake of index insurance and provide guidance to policymakers in their approach to mitigating the effects of climate change on crop production in Nigeria.

From frequency to intensity – A new index for annual large-scale cropping intensity mapping

Continuous population growth, global warming, extreme weather and local wars pose considerable challenges to agricultural production. Excessive agricultural intensification may lead to serious environmental problems such as water resources depletion and non-point source pollution. Sustainable agricultural intensification is a potential solution, and cropping intensity and its spatio-temporal patterns are of great significance to the planet hearth, human well-being and sustainable development of agriculture. However, traditional methods for cropping intensity mapping lack the deep analysis of crop phenology and failure to consider the spatial detail, spatial coverage and time continuity simultaneously. Existing cropping intensity indicators, such as cropping frequency or multiple crop index, have their limitations in China because of its diverse topographies and fragmented landscapes. In actual fact, few indicators for fine cropping intensity have been developed that address this problem. Time series vegetation index data contain meaningful vegetation phenology information. Information mining on these data can provide new insights for cropping intensity mapping. In this study, the concept of systematic mapping was put forward to measure cropping intensity with a fresh perspective. A new phenology-based cropping intensity index (PCII) was proposed to reach the goal of “from frequency to intensity” in cropping intensity mapping. Through thoroughly exploring the temporal spectral characteristics of croplands and considering the crop pattern as a whole, PCII set up the mapping between cropping intensity and land-cover types. The method can accurately map cropping intensity even though the study spanned a vast area, and can handle the effects of geographical differentiation caused by vegetation phenology differences. It can also precisely measure cropping intensity at the abundance level and reflect the heterogeneity within a pixel. It’s a novel method for annual fine cropping intensity mapping at large-scale and long-term.

A single control area policy as a threat to food security in West Lombok Regency

Land conversion from agriculture to non-agriculture is currently taking place, and it is suspected that it will become more massive if the single-area policy is enforced. The study aims to modify the formulation of the carrying capacity index of sustainable food-agriculture land in accordance with the single-control regional policy to maintain self-sufficiency in rice food. Primary data collection uses survey techniques, in-depth interviews, and focus group discussions. Secondary data was obtained by applying the desk study literacy method. The projected rice demand data of the population is multiplied by the average need for rice per person, while the food supply is calculated by average land productivity and annual cropping index. The land carrying capacity index can be modified from a production needs approach to a paddy field needs approach, and the land carrying capacity index can be used to analyze sustainable food needs. Food security in West Lombok District is able to return to self-sufficiency in food until 2030, but due to the policy of a single control area, food self-sufficiency is threatened with however, unless increasing the cropping index to 300% per annum.

Estimating Agricultural Cropping Intensity Using a New Temporal Mixture Analysis Method from Time Series MODIS

Agricultural cropping intensity plays an important role in evaluating the food security and the sustainable development of agriculture. The existing indicators measuring cropping intensity include cropping frequency and multiple cropping index. As a nominal measurement, cropping frequency classifies crop patterns into single-cropping and/or double-cropping and leads to information loss. Multiple cropping index is calculated on the basis of statistical data, ignoring the spatial heterogeneity within the administrative region. Neither of these indicators can meet the requirements of precision agriculture, and new methods for fine cropping intensity mapping are still lacking. Time series remote sensing data provide vegetation phenology information and reveal temporal development of vegetation, which can be used to facilitate the fine cropping intensity mapping. In this study, a new temporal mixture analysis method is introduced to estimate the abundance level cropping intensity from time series remote sensing data. By analyzing phenological characteristics of major land-cover types in time series vegetatiosacan indices, a novel feature space was constructed by using the selected PCA components, and three unique endmembers (double-cropping, natural vegetations and water bodies) were found. Then, a linear spectral mixture analysis model was applied to decompose mixed pixels by replacing spectral data with multi-temporal data. The spatio-temporal continuous, fine resolution, abundance level cropping intensity maps were produced for the North China Plain and the middle and lower reaches of the Yangtze River Valley. The experiments indicate a good result at both county and pixel level validation. The method of manually delineating endmembers can well balance the accuracy and efficiency. We also found the size of the study area has little effect on the unmixing accuracy. The results demonstrated that the proposed method can model cropping intensity finely at large scale and long temporal span, at the same time with high efficiency and ease of implementation.

Utilization of semi-intensive irrigated paddy fields and increasing farmers income on cropping patterns in support of ip400 technology in Central Sulawesi

Based on the agro-ecosystem and suitability of paddy fields, rice fields have high potential and opportunities to be developed in Central Sulawesi Province, but sometimes the yield is still below the average production. This research has been conducted from May 2021 to June 2022. The research location is Kaleke Village, West Dolo District, Sigi Regency, Central Sulawesi. This study aims to increase the Crop Index and harvested area to increase the production and income of farmers as well as the performance of farmer groups. Research on cropping patterns and alternation of varieties with Rice – Corn – Corn – Rice Cropping Patterns. The treatment area of 1 ha with the planting system used is: for each commodity using components, PTT Paddy rice PTT corn. While the feasibility of farming with an income analysis approach with an R/C ratio. The results showed that: (a) The design of agricultural technology innovations to increase the cropping index of rice crops with MT I results showed the production component of the Inpari 33 variety of rice tiles. R/C Ratio 2.11, on MT. II Jakarin variety corn with a yield of 5.0 tons/ha. R/C Ratio: 2.04, maize variety Sukmaraga MT.III average yield 6.3 tons with R/C Ratio: 2.01 and MT. IV rice variety Inpari 36 with a yield of 5 tons/ha GKP R/C Ratio: 1.59(c) Increasing the Crop Index and harvested area can increase farmers’ income and the performance of farmer groups on technology supporting IP400.

Test of Use of Goat Manure on Growth and Yield of Basil (Ocimum Sanctum L.)

This study aims to determine the effect of the use of goat manure on the growth and yield of basil plants. This research was carried out on campus land, Modong Village, Tulangan District, Sidoarjo Regency from December 2022 to February 20223. This study used a Group Randomized Design (RAK) with a single fak tor, namely fermented goat shrimp solid fertilizer consisting of 7 treatments, namely: 10 tons / ha, 12.5 tons / ha, 15 tons / ha, 17.5 tons / ha, 20 tons / ha, 22.5 tons / h a , 25 tons / ha. Data analysis uses variant analysis (Anova) and if there is a difference, further tests of Honest Real Difference (BNJ) 5% and 1% are carried out. From the observations, the results showed a real effect on the observation of plant height aged 7 HST in P7 treatment and crop index measurement in P4 treatment and also had a very real effect on measuring the wet weight of plants in P3 treatment.

Analysis of the spatial-temporal evolution of Green and low carbon utilization efficiency of agricultural land in China and its influencing factors under the goal of carbon neutralization

Agricultural land is the most basic input factor for agricultural production and an essential component of terrestrial ecosystems, which plays a vital role in achieving carbon neutrality. Giving full play to the carbon-neutral contribution of agricultural land is a crucial part of China's economic transformation and green development. It incorporates carbon and pollution emissions from agricultural land use into the unexpected outputs of the Green and Low-carbon Utilization Efficiency of Agricultural Land (GLUEAL) evaluation system. The study utilized several advanced analytical tools, including the super-efficient Slacks-Based Measure (SBM) model, Exploratory Spatial-Temporal Data Analysis (ESTDA) method, Geodetector, and Geographically and Temporally Weighted Regression (GTWR) model. The objective was to examine the spatial-temporal evolution of GLUEAL and identify the factors that influenced it in all 31 provinces of China from 2005 to 2020. The results show that: (1) The overall spatial-temporal evolution of GLUEAL showed an increasing trend, but the disparity between provinces and regions became wider. (2) Most provinces have not yet made significant spatial and temporal jumps. They have high spatial cohesion with specific "path-dependent" characteristics. (3) The Geodetector results reveal that the Number of Rural Labor Force with Higher Education (NRLFHE) and Technology Support for Agriculture (TSA) have insufficient explanatory power on average for GLUEAL. Agricultural Economic Development Level (AEDL), Urbanization Level (UL), Multiple Crop Index (MCI), Planting Structure (PS), Degree of Crop Damage (DCD), Financial support for agriculture (FSA), and Agricultural mechanization level (AML) had stronger explanatory power on average for GLUEAL and were important factors influencing GLUEAL levels. (4) The average influence of AEDL, UL, FSA, and AML on GLUEAL changed from negative to positive. The average influence of MCI and DCD on GLUEAL was negative, and the average influence of PS on GLUEAL changed from positive to negative. This study provides a comprehensive description of the spatial and temporal evolution of GLUEAL in China. It reveals the key factors influencing GLUEAL and analyzes their spatial variations and impact patterns. These findings offer robust evidence for government policymakers to formulate policy measures for sustainable agricultural development and optimized resource allocation, promoting the transformation of agricultural land towards green and low-carbon practices and advancing the achievement of sustainable development goals.

Estimating fall‐harvested alfalfa (Medicago sativa L.) yield using unmanned aerial vehicle–based multispectral and thermal images in southern California

AbstractThis study aims to evaluate the efficacy of simple linear, multiple, and robust regression methods to predict fall‐harvested alfalfa (Medicago sativa L.) yield using unmanned aerial vehicle (UAV)‐acquired multispectral and thermal images. Four alfalfa fields in southern California were selected, and a composite dataset containing 180 ground truth sampling points was formed to build and test the performance of the regression models. The UAV was flown in September 2020, 5–29 days before the ground truth data collection. A total of nine crop indices, canopy temperature, and the difference between canopy temperature and air temperature were used as input predictors. Among the simple linear models, the model with normalized difference vegetation index as input showed a strong performance (coefficient of determination [R2] = 0.76; root mean square error [RMSE] = 170.29 kg ha−1; and mean absolute error [MAE] = 132.18 kg ha−1). A multiple linear regression model with three input predictors showed the highest accuracy with R2 = 0.83, RMSE = 142.99 kg ha−1, and MAE = 109.30 kg ha−1. The top‐performing models accurately estimated mean yield at the field level and differentiated fields with low and high alfalfa productivity. Including canopy temperature‐related inputs did not improve the yield prediction power of the models. The error in the yield prediction increased as the days between UAV flights and field harvest increased. Results here suggested that UAV‐based remote sensing has the potential to estimate fall‐harvested alfalfa yield in southern California.

ANALISIS KEBUTUHAN ALAT DAN MESIN PERTANIAN UNTUK MENDUKUNG INDEKS PERTANAMAN 200 DI LAHAN RAWA LEBAK


 This study aims to analyze the need for agricultural machinery to support a cropping index of 200 in swampy land. This research was conducted in August 2021 in Muara Abab Village, Rantau Bayur District, Banyuasin Regency, South Sumatra Province. This study used a descriptive-tabular method, while collecting primary data using survey techniques and semi-structured interviews. Secondary data collection was obtained through a literature study conducted to collect data on institutions and policies supporting the development of agricultural tools and machinery. The data obtained was processed descriptively and analyzed to see farmers income and the data is presented in the form of tabulations. The results showed that the total income of lebak swamp farmers was IDR 8,963,625.00/ha/year. To support the activities of the index cropping 200, it is necessary to add additional agricultural equipment such as 5 units of 2-wheeled tractors, 1 unit of 4-wheeled tractors, 9 units of water pumps, 5 units of combine harvesters, 14 units of threshers and dryer as much as 2 units.
 
 Keywords: agricultural machinery, swampy land, cropping index 200, productivity

Analysis of Effect on Pesticide Drift Reduction of Prevention Plants Using Spray Drift Tunnel

With rising concerns about pesticide spray drift by aerial application, this study attempt to evaluate aerodynamic property and collection efficiency of spray drift according to the leaf area index (LAI) of crop for preventing undesirable pesticide contamination by the spray-drift tunnel experiment. The collection efficiency of the plant with ‘Low’ LAI was measured at 16.13% at a wind speed of 1 m·s-1. As the wind speed increased to 2 m·s-1, the collection efficiency of plant with the same LAI level increased 1.80 times higher to 29.06%. For the ‘Medium’ level LAI, the collection efficiency was 24.42% and 43.06% at wind speed of 1 m·s-1 and 2 m·s-1, respectively. For the ‘High’ level LAI, it also increased 1.24 times higher as the wind speed increased. The measured results indicated that the collection of spray droplets by leaves were increased with LAI and wind speed. This also implied that dense leaves would have more advantages for preventing the drift of airborne spray droplets. Aerodynamic properties also tended to increase as the LAI increased, and the regression analysis of quadric equation and power law equation showed high explanatory of 0.96－0.99.

The role of peer imitation in agricultural index insurance adoption: Findings from lab‐in‐the‐field experiments in Kyrgyzstan

AbstractFrequent climate shocks require farmers in developing countries to increase their resilience. Although index insurance is often discussed as a promising climate adaptation strategy, take‐up rates are still low. This study primarily explores the role of peer behavior as peer imitation in the demand for three marketable and unsubsidized crop index insurance options. Furthermore, the influence of trust and understanding is investigated. We collected data in lab‐in‐the‐field experiments among farmers in Kyrgyzstan, where index insurance is planned for imminent implementation. Applying ordered logit estimations, our results show significant and strong peer imitation effects. Imitation attitudes decrease with own insurance experience and received insurance payouts, but intensify with peer size, insurance trust and practical insurance understanding. While trust robustly increases index insurance adoption, understanding effects only gain significance in the dynamic perspective. These findings underline the importance of community‐based extension treatments and trust toward the uptake of innovative agricultural technologies in the first steps of dissemination.

Agriculture productivity and level of agricultural devel-opment in Eastern Uttar Pradesh of the Middle Ganga Plain

Agriculture is the primary source of occupation for the Indian rural people who directly or indirectly depend on agriculture. Today, India is facing two most vital problems which is di-rectly related to agriculture. The first one is to fulfil the growing demand of the ever-increasing population for food and other agricultural products, and the second is widespread disparities in agriculture development. This paper has attempted the measurement of agriculture productivity and the level of agricultural development in Eastern Uttar Pradesh of the Middle Ganga Plain. Taking into consideration this idea in mind, the present study attempts to calculate first the land productivity (per ha NSA) based on three indices viz. (i) Standardized crop Index(Isyi)(ii) Weight Crop Equivalent index (Iwei) and (iii) Cropping intensity index(Ici) and then labor productivity (per agricultural worker) with the help of agricultural worker index (Iewi). After this results here also calculate the level of agricultural development on the basis of 27 variables by the Z score method. The study area of Jaunpur is situated in Eastern Uttar Pradesh of the Middle Ganga Plain. The total area of the district is 4038 km2 having a population of 44, 94,204 persons. Several factors like water logging, salinity, relief variation, etc., and different modern agro-input have resulted in remarkable spatial disparity in agriculture productivity and level of development.

Cropping Scenario in Water User Associations (WUAs) Managed Groundwater Irrigation System’s Command Area in West Bengal

The groundwater irrigation, catering to more than 60 per cent of total irrigation in India, has significantly contributed to food grains production. Participatory irrigation management programme has been implemented transferring irrigation management to WUAs. Present study was undertaken during 2019 to explore cropping scenario in groundwater irrigation command under jurisdiction of WUAs in Burdwan district of West Bengal covering a random sample of 120 farmers. It is revealed that paddy was the major crop in both kharif and summer season. During rabi season, potato was grown in larger areas followed by mustard. While all 120 farmers had grown paddy as single crop in kharif season, 100 and 82 farmers have cultivated potato and mustard in rabi season and 75 farmers have grown boro rice during summer season. Cultivated land utilization index value was more than 50 per cent. Crop diversity index (CDI) value of 36 per cent showed lack of crop diversification in groundwater irrigation command areas that warrants need of bringing more areas under different crops. Multiple cropping index of 176 per cent showed a higher cropping intensity in groundwater irrigation command. Thus, Extension advisory services need to promote crop diversification in groundwater irrigation command areas through proper crop planning and capacity building of WUAs.

Blockchain-Based Approach for Crop Index Insurance in Agricultural Supply Chain

Blockchain-Based Approach for Crop Index Insurance in Agricultural Supply Chain

The Transformation of Rice Crop Technology in Indonesia: Innovation and Sustainable Food Security

The growth of the Indonesian population has led to an increase in the demand for rice, which the country has yet to satisfy. Indonesia needs a comprehensive strategy that integrates meaningful efforts to increase its agricultural production. This study aims to review the examined trends in rice yield in Indonesia for 70 years after Indonesia’s independence (1945–2016) followed by the identification of the application technology and factors that contribute to increasing rice yields to forecast sustainable food security scenarios up to 2030. This article reviews the results of research on rice production technology in Indonesia from 1945 to 2016, and the outlook for 2030. This paper examines the main points of the Indonesian transformation of rice technology: improvement of rice varieties, integrated crop management, innovations in agricultural machinery, and the Integrated Cropping Calendar Information System (ICCIS). We found that transformation has helped Indonesia increased its rice yields from 3 t ha−1 prior to 1961 to 4.6 t ha−1 in 1985, stagnated in 1990, and increased again in 2017 to 5.46 t ha−1. The increase in yield was sustained by an increase in the harvested area owing to cropping index (CI) innovation. Food security and sustainable development remain the primary goals of Indonesia’s agricultural sector. The application of appropriate technologies and institutional innovations can assist Indonesia in achieving its food security. Therefore, the transformation of technological innovations will continue to be an essential driver of future agricultural growth, including greater use of crop varieties, machinery, and land/institutional reforms.