Using PhenoCams to track crop phenology and explain the effects of different cropping systems on yield

Abstract The downside risk of crop production affects the entire supply chain of the agricultural industry nationally and globally. This also has a profound impact on food security, and thus livelihoods, in many parts of the world. The advent of high temporal, spatial and spectral resolution remote sensing platforms, specifically during the last five years, and the advancement in software pipelines and cloud computing have resulted in the collating, analysing and application of “BIG DATA” systems, especially in agriculture. Furthermore, the application of traditional and novel computational and machine learning approaches is assisting in resolving complex interactions, to reveal components of eco-physiological systems that were previously deemed either “too difficult” to solve or “unseen”. In this review, digital technologies encompass mathematical, computational, proximal- and remote sensing technologies. Here, we review the current state of digital technologies and their application in broad acre cropping systems globally and in Australia. More specifically, we discuss the advances in (i) remote sensing platforms, (ii) machine learning approaches to discriminate between crops, and (iii) the prediction of crop phenological stages from both sensing and crop simulation systems for major Australian winter crops. An integrated solution is proposed to allow accurate development, validation and scalability of predictive tools for crop phenology mapping at within-field scales, across extensive cropping areas.

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Bioecology of fall armyworm Spodoptera frugiperda (J. E. Smith), its management and potential patterns of seasonal spread in Africa

PLoS ONE ◽

10.1371/journal.pone.0249042 ◽

2021 ◽

Vol 16 (6) ◽

pp. e0249042

Author(s):

Saliou Niassy ◽

Mawufe Komi Agbodzavu ◽

Emily Kimathi ◽

Berita Mutune ◽

El Fatih M. Abdel-Rahman ◽

...

Keyword(s):

Data Collection ◽

Early Warning ◽

Spodoptera Frugiperda ◽

Negative Binomial ◽

Cropping Systems ◽

Fall Armyworm ◽

Sub Saharan Africa ◽

Maturity Stage ◽

Community Based ◽

Crop Phenology

Fall armyworm, Spodoptera frugiperda (J. E. Smith) has rapidly spread in sub-Saharan Africa (SSA) and has emerged as a major pest of maize and sorghum in the continent. For effective monitoring and a better understanding of the bioecology and management of this pest, a Community-based Fall Armyworm Monitoring, Forecasting, Early Warning and Management (CBFAMFEW) initiative was implemented in six eastern African countries (Ethiopia, Kenya, Tanzania, Uganda, Rwanda and Burundi). Over 650 Community Focal Persons (CFPs) who received training through the project were involved in data collection on adult moths, crop phenology, cropping systems, FAW management practices and other variables. Data collection was performed using Fall Armyworm Monitoring and Early Warning System (FAMEWS), a mobile application developed by the Food and Agricultural Organization (FAO) of the United Nations. Data collected from the CBFAMFEW initiative in East Africa and other FAW monitoring efforts in Africa were merged and analysed to determine the factors that are related to FAW population dynamics. We used the negative binomial models to test for effect of main crops type, cropping systems and crop phenology on abundance of FAW. We also analysed the effect of rainfall and the spatial and temporal distribution of FAW populations. The study showed variability across the region in terms of the proportion of main crops, cropping systems, diversity of crops used in rotation, and control methods that impact on trap and larval counts. Intercropping and crop rotation had incident rate 2-times and 3-times higher relative to seasonal cropping, respectively. The abundance of FAW adult and larval infestation significantly varied with crop phenology, with infestation being high at the vegetative and reproductive stages of the crop, and low at maturity stage. This study provides an understanding on FAW bioecology, which could be vital in guiding the deployment of FAW-IPM tools in specific locations and at a specific crop developmental stage. The outcomes demonstrate the relevance of community-based crop pest monitoring for awareness creation among smallholder farmers in SSA.

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Use of MODIS EVI to map crop phenology, identify cropping systems, detect land use change and drought risk in Ethiopia – an application of Google Earth Engine

European Journal of Remote Sensing ◽

10.1080/22797254.2020.1786466 ◽

2020 ◽

Vol 53 (1) ◽

pp. 176-191

Author(s):

Kefyalew Sahle Kibret ◽

Carsten Marohn ◽

Georg Cadisch

Keyword(s):

Land Use ◽

Land Use Change ◽

Cropping Systems ◽

Google Earth ◽

Drought Risk ◽

Crop Phenology ◽

Modis Evi ◽

Google Earth Engine

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Devising fertiliser recommendations for diverse cropping systems in a region: the case of low-input bean/maize intercropping in a tropical highland of Haïti

Agronomie ◽

10.1051/agro:2003046 ◽

2003 ◽

Vol 23 (7) ◽

pp. 673-681 ◽

Cited By ~ 9

Author(s):

C. Clermont-Dauphin ◽

J. M. Meynard ◽

Y. M. Cabidoche

Keyword(s):

Cropping Systems ◽

Low Input

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Growth and Economic Profitability of Castor Cultivation in the Semi-arid Zone of Haryana

Indian Journal of Economics and Development ◽

10.35716/ijed/ns20-011 ◽

2020 ◽

pp. 300-305

Keyword(s):

Arid Zone ◽

Cropping Systems ◽

Descriptive Analysis ◽

Market Price ◽

Transportation Cost ◽

Castor Seed ◽

Production Constraints ◽

Net Profit ◽

Semi Arid ◽

Extract Information

The present study was carried out in three districts viz; Rewari, Sirsa and Hisar of Haryana state. A survey of 60 sampled farms was conducted to extract information pertaining to various expenses incurred in cultivation of castor and output attained as well as to ascertain the perception of farmers for various problems encountered in production and marketing of castor seed. The descriptive analysis was employed to draw valid inferences from the study. The results revealed that net profit accrued from cultivation of castor seed was ₹ 46331 ha -1 in the study area. The value of B: C ratio of castor cultivation was more than one and also higher as compared to prevalent cropping systems indicated that cultivation of castor seed is economical viable entity. However, production constraints like retention of F2 seed in the field over year, grain scattering, shortage of irrigation water, frost effect on crop yield and marketing constraints like absence of MSP, higher transportation cost sale of castor seed in distant markets, frequent fluctuation in market price, non-availability of processing units were observed.

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Comparative Effect of Groundnut (Arachis hypogea l.) Genotypes on Yield and N Fixation in Sudan and Northern Guinea Savannahs of Nigeria

10.36265/njss.2019.290208 ◽

2019 ◽

pp. 61-67

Keyword(s):

Agricultural Research ◽

Cropping Systems ◽

Block Design ◽

Dry Weight ◽

Field Trials ◽

Yield Potential ◽

N Fixation ◽

Maize Crop ◽

Significant Interaction Effect ◽

Pod Yield

Recognition of high yielding and nitrogen (N) fixing groundnut genotypes and desegregating them in the cereal-based cropping systems common in savannah regions will enhance food security and reduce the need for high N fertilizers hence, minimize the high cost and associated environmental consequences. Field trials were conducted during the 2015 growing season at the Research Farms of Bayero University Kano (BUK) and Institute for Agricultural Research (IAR), Ahmadu Bello University, Samaru-Zaria to assess the yield potential and Biolog- ical N fixation in 15 groundnut genotypes (ICG 4729, ICGV-IS 07823, ICGV-IS 07893, ICGV-IS 07908, ICGV- SM 07539, ICGV- SM 07599, ICGV-IS 09926, ICGV-IS 09932, ICGV-IS 09992, ICGV-IS 09994, SAMNUT-21, SAMNUT-22, SAMNUT-25, KAMPALA and KWANKWAS). The groundnut genotypes and reference Maize crop (SAMMAZ 29) were planted in a randomized complete block design in three replications. N difference method was used to estimate the amount of N fixed. The parameters determined were the number of nodules, nod- ule dry weight, shoot and root dry weights, pod, and haulm yield as well as N fixation. The nodule dry weight, BNF, haulm, and pod yield were statistically significant (P<0.01) concerning genotype and location. Similarly, their interac- tion effect was also highly significant. ICGV-IS 09926 recorded the highest nod- ule dry weight of 2.07mg /plant across the locations while ICGV-IS 09932 had the highest BNF value of 140.27Kg/ha. Additionally, KAMPALA had the high- est haulm yield, while ICGV-IS 07893 had the highest pod yield across the loca- tions with a significant interaction effect. The result shows that ICGV-IS 07893 and ICGV-IS 09932, as well as ICGV-IS 09994 and SAMNUT – 22, were the best genotypes concerning BNF, haulm and pod yield in the Northern Guinea and Sudan Savannahs of Nigeria respectively with the potential for a corresponding beneficial effect.

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